AI&DS46303 -Software Engineering

UNIT – 1
Unit I:
Software and Software Engineering: The Nature of Software, The Unique Nature of WebApps,
Software Engineering, The Software Process, Software Engineering Practice, Software Myths
Process Models: A Generic Process Model, Process Assessment and Improvement, Prescriptive
Process Models, Specialized Process Models, The Unified Process, Personal and Team Process
Models, Process Technology, Product and Process.

Agile Development: Agility, Agility and the Cost of Change, Agile Process, Extreme
Programming, Other Agile Process Models

1.0 SOFTWARE AND SOFTWARE ENGINEERING

What is it? Computer software is the product that software professionals build and then
support over the long term. It encompasses programs that execute within a computer of
any size and architecture, content that is presented as the computer programs execute,
and descriptive information in both hard copy and virtual forms that encompass virtually
any electronic media. Software engineering encompasses a process, a collection of
methods (practice) and an array of tools that allow professionals to build high quality
computer software.

Who does it? Software engineers build and support software, and virtually everyone in the
industrialized world uses it either directly or indirectly.

Why is it important? Software is important because it affects nearly every aspect of our
lives and has become pervasive in our commerce, our culture, and our everyday activities
Software engineering is important because it enables us to build complex systems in a
timely manner and with high quality.

What are the steps? You build computer software like you build any successful product,
by applying an agile, adaptable process that leads to a high-quality result that meets the
needs of the people who will use the product. You apply a software engineering approach.

What is the work product? From the point of view of a software engineer, the work
product is the set of programs, content (data), and other work products that are computer
software. But from the user’s viewpoint, the work product is the resultant information that
somehow makes the user’s world better.
 AI&DS46303 -Software Engineering

1.1 THE NATURE OF SOFTWARE

Today, software takes on a dual role. It is a product, and at the same time, the vehicle
for delivering a product. As a product, it delivers the computing potential embodied by
computer hardware or more broadly, by a network of computers that are accessible by
local hardware.

As the vehicle used to deliver the product, software acts as the basis for the control of
the computer (operating systems), the communication of information (networks), and
the creation and control of other programs (software tools and environments).

Software delivers the most important product of our time—information. It transforms

personal data so that the data can be more useful in a local context; it manages
business information to enhance competitiveness; it provides a gateway to worldwide
information networks, and provides the means for acquiring information in all of its
forms.

The role of computer software has undergone significant change over the last half-
century. Dramatic improvements in hardware performance, profound changes in
computing architectures, vast increases in memory and storage capacity, and a wide
variety of exotic input and output options, have all precipitated more sophisticated and
complex computer-based systems. Sophistication and complexity can produce dazzling
results when a system succeeds, but they can also pose huge problems for those who
must build complex systems.

1.1.1 Defining Software: Software is:

(1) instructions (computer programs) that when executed provide desired features,
function, and performance;
(2) data structures that enable the programs to adequately manipulate information, and
(3) descriptive information in both hard copy and virtual forms that describes the
operation and use of the programs.

Software has characteristics that are considerably different than those of hardware:

1. Software is developed or engineered: it is not manufactured in the classical sense.

Although some similarities exist between software development and hardware
manufacturing, the two activities are fundamentally different. In both activities, high
quality is achieved through good design, but the manufacturing phase for hardware can
introduce quality problems that are nonexistent (or easily corrected) for software.
Software projects cannot be managed as if they were manufacturing projects.
 AI&DS46303 -Software Engineering

2. Software doesn’t “wear out.”: Figure 1.1 depicts failure rate as a function of time
for hardware. The relationship, often called the “bathtub curve,” indicates that hardware
exhibits relatively high failure rates early in its life; defects are corrected and the failure
rate drops to a steady-state level (hopefully, quite low) for some period of time. As time
passes, however, the failure rate rises again as hardware components suffer from the
cumulative effects of dust, vibration, abuse, temperature extremes, and many other
environmental maladies.

Stated simply, the hardware begins to wear out. Software is not susceptible to the
environmental maladies that cause hardware to wear out. In theory, therefore, the
failure rate curve for software should take the form of the “idealized curve” shown in
Figure 1.2. Undiscovered defects will cause high failure rates early in the life of a
program. However, these are corrected and the curve flattens as shown. The idealized
 Software Engineering Lecture notes

curve is a gross oversimplification of actual failure models for software. However, the
implication is clear—software doesn’t wear out. But it does deteriorate.

3. Although the industry is moving toward component-based construction, most

software continues to be custom built: As an engineering discipline evolves, a
collection of standard design components is created. The reusable components have
been created so that the engineer can concentrate on the truly innovative elements of a
design, that is, the parts of the design that represent something new.

A software component should be designed and implemented so that it can be reused in

many different programs. Modern reusable components encapsulate both data and the
processing that is applied to the data, enabling the software engineer to create new
applications from reusable parts.

1.1.2 Software Application Domains: Today, seven broad categories of computer

software present continuing challenges for software engineers:

System software—a collection of programs written to service other programs. Some

system software (e.g., compilers, editors, and file management utilities) processes
complex, but determinate, information structures. Other systems applications (e.g.,
operating system components, drivers, networking software, telecommunications
processors) process largely indeterminate data.

Application software—stand-alone programs that solve a specific business need.

Applications in this area process business or technical data in a way that facilitates
business operations or management/technical decision making.

Engineering/scientific software—has been characterized by “number crunching”

algorithms. Applications range from astronomy to volcanology, from automotive stress
analysis to space shuttle orbital dynamics, and from molecular biology to automated
manufacturing.

Embedded software—resides within a product or system and is used to implement and

control features and functions for the end user and for the system itself.

Product-line software—designed to provide a specific capability for use by many

different customers. Product-line software can focus on a limited and esoteric
marketplace or address mass consumer markets.

Web applications—called “WebApps,” this network-centric software category spans a

wide array of applications. In their simplest form, WebApps can be little more than a set
of linked hypertext files that present information using text and limited graphics.
SAHE, Dept. of AI&DS
 Software Engineering Lecture notes

Artificial intelligence software—makes use of nonnumerical algorithms to solve

complex problems that are not amenable to computation or straightforward analysis.
Applications within this area include robotics, expert systems, pattern recognition
(image and voice), artificial neural networks, theorem proving, and game playing.

New Challenges

Open-world computing—the rapid growth of wireless networking may soon lead to

true pervasive, distributed computing. The challenge for software engineers will be to
develop systems and application software that will allow mobile devices, personal
computers, and enterprise systems to communicate across vast networks.

Net sourcing—the World Wide Web is rapidly becoming a computing engine as well as
a content provider. The challenge for software engineers is to architect simple and
sophisticated applications that provide a benefit to targeted end-user markets
worldwide.

Open source—a growing trend that results in distribution of source code for systems
applications so that many people can contribute to its development.

1.1.3 Legacy Software: These older programs—often referred to as legacy software.

Legacy software systems . were developed decades ago and have been continually
modified to meet changes in business requirements and computing platforms. Legacy
software is characterized by longevity and business criticality.

Unfortunately, there is sometimes one additional characteristic that is present in legacy

software—poor quality. Legacy systems sometimes have inextensible designs,
convoluted code, poor or nonexistent documentation, test cases and results.

Legacy systems often evolve for one or more of the following reasons:
• The software must be adapted to meet the needs of new computing environments or
technology.
• The software must be enhanced to implement new business requirements.
• The software must be extended to make it interoperable with other more modern
systems or databases.
• The software must be re-architected to make it viable within a network environment.
 Software Engineering Lecture notes

1.2 THE UNIQUE NATURE OF WEBAPPS

The following attributes are encountered in the vast majority of WebApps.

Network intensiveness. A WebApp resides on a network and must serve the needs of
a diverse community of clients. The network may enable worldwide access and
communication (i.e., the Internet) or more limited access and communication (e.g., a
corporate Intranet).
Concurrency. A large number of users may access the WebApp at one time. In many
cases, the patterns of usage among end users will vary greatly.
Unpredictable load. The number of users of the WebApp may vary by orders of
magnitude from day to day. One hundred users may show up on Monday; 10,000 may
use the system on Thursday.
Performance. If a WebApp user must wait too long, he or she may decide to go
elsewhere.
Availability. Although expectation of 100 percent availability is unreasonable, users of
popular WebApps often demand access on a 24/7/365 basis. Users in Australia or Asia
might demand access during times when traditional domestic software applications in
North America might be taken off-line for maintenance.
Data driven. The primary function of many WebApps is to use hypermedia to present
text, graphics, audio, and video content to the end user. In addition, WebApps are
commonly used to access information that exists on databases that are not an integral
part of the Web-based environment
Content sensitive. The quality and aesthetic nature of content remains an important
determinant of the quality of a WebApp.
Continuous evolution. Unlike conventional application software that evolves over a
series of planned, chronologically spaced releases, Web applications evolve
continuously. It is not unusual for some WebApps (specifically, their content) to be
updated on a minute-by-minute schedule or for content to be independently computed
for each request.
Immediacy. Although immediacy—the compelling need to get software to market
quickly—is a characteristic of many application domains, WebApps often exhibit a time-
to-market that can be a matter of a few days or weeks.
Security. Because WebApps are available via network access, it is difficult, if not
impossible, to limit the population of end users who may access the application. In order
to protect sensitive content and provide secure modes of data transmission, strong
security measures must be implemented throughout the infrastructure that supports a
WebApp and within the application itself.
Aesthetics. An undeniable part of the appeal of a WebApp is its look and feel. When an
application has been designed to market or sell products or ideas, aesthetics may have
as much to do with success as technical design.
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1.3 SOFTWARE ENGINEERING

Software engineering encompasses a process, methods for managing and engineering

software, and tools.

In order to build software that is ready to meet the challenges of the twenty-first century,
few simple realities are:

• Software has become deeply embedded in virtually every aspect of our lives, and as a
consequence, the number of people who have an interest in the features and functions
provided by a specific application has grown dramatically.
• The information technology requirements demanded by individuals, businesses, and
governments grow increasing complex with each passing year. The complexity of these
new computer-based systems and products demands careful attention to the
interactions of all system elements. It follows that design becomes a pivotal activity.
• Individuals, businesses, and governments increasingly rely on software for strategic
and tactical decision making as well as day-to-day operations and control. If the
software fails, people and major enterprises can experience anything from minor
inconvenience to catastrophic failures.
• As the perceived value of a specific application grows, the likelihood is that its user
base and longevity will also grow. As its user base and time-in-use increase, demands
for adaptation and enhancement will also grow. It follows that software should be
maintainable.

The IEEE has developed a more comprehensive definition when it states:

Software Engineering: (1) The application of a systematic, disciplined, quantifiable
approach to the development, operation, and maintenance of software; that is, the
application of engineering to software. (2) The study of approaches as in (1).

Layered Technology: Software engineering is a layered technology. Referring to

Figure 1.3, any engineering approach (including software engineering) must rest on an
 Software Engineering Lecture notes

organizational commitment to quality. Total quality management, Six Sigma, and similar
philosophies foster a continuous process improvement culture, and it is this culture that
ultimately leads to the development of increasingly more effective approaches to
software engineering. The bedrock of software engineering is a quality focus.

The foundation for software engineering is the process layer. The software engineering
process is the glue that holds the technology layers together and enables rational and
timely development of computer software. Process defines a framework that must be
established for effective delivery of software engineering technology.

The software process forms the basis for management control of software projects and
establishes the context in which technical methods are applied, work products (models,
documents, data, reports, forms, etc.) are produced, milestones are established, quality
is ensured, and change is properly managed.

Software engineering methods provide the technical how-to’s for building software.
Methods encompass a broad array of tasks that include communication, requirements
analysis, design modeling, program construction, testing, and support. Software
engineering methods rely on a set of basic principles that govern each area of the
technology and include modeling activities and other descriptive techniques.

Software engineering tools provide automated or semi automated support for the
process and the methods. When tools are integrated so that information created by one
tool can be used by another, a system for the support of software development, called
computer-aided software engineering, is established.

1.4 The software Process

A process defines who is doing what when and how to reach a certain goal.
A process is a collection of activities, actions, and tasks that are performed when
some work product is to be created. An activity strives to achieve a broad objective and
is applied regardless of the application domain, size of the project, complexity of the
effort, or degree of rigor with which software engineering is to be applied. An action
encompasses a set of tasks that produce a major work product. A task focuses on a
small, but well-defined objective (e.g., conducting a unit test) that produces a tangible
outcome.

A process is not a rigid rather it is an adaptable approach to choose the appropriate set
of work actions and tasks. The intent is always to deliver software in a timely manner
and with sufficient quality to satisfy those who have sponsored its creation and those
who will use it.
 Software Engineering Lecture notes

A process framework establishes the foundation for a complete software engineering

process by identifying a small number of framework activities that are applicable to all
software projects, regardless of their size or complexity. In addition, the process
framework encompasses a set of umbrella activities that are applicable across the
entire software process. A generic process framework for software engineering
encompasses five activities:
Communication. Before any technical work can commence, it is critically important to
communicate and collaborate with the customer. The intent is to understand
stakeholders’ objectives for the project and to gather requirements that help define
software features and functions.
Planning. The planning activity creates a “map” called a software project plan—defines
the software engineering work by describing the technical tasks to be conducted, the
risks that are likely, the resources that will be required, the work products to be
produced, and a work schedule.
Modeling. You create a “sketch” of the thing so that you’ll understand the big picture. A
software engineer does the same thing by creating models to better understand
software requirements and the design that will achieve those requirements.
Construction. This activity combines code generation and the testing that is required to
uncover errors in the code.
Deployment. The software is delivered to the customer who evaluates the delivered
product and provides feedback based on the evaluation.

These five generic framework activities can be used during the development of small,
simple programs, the creation of large Web applications, and for the engineering of
large, complex computer-based systems. The details of the software process will be
quite different in each case, but the framework activities remain the same.

That is, communication, planning, modeling, construction, and deployment are applied
repeatedly through a number of project iterations. Each project iteration produces a
software increment that provides stakeholders with a subset of overall software features
and functionality.

Software engineering process framework activities are complemented by a number of

umbrella activities. In general, umbrella activities are applied throughout a software
project.

Typical umbrella activities include:

Software project tracking and control—allows the software team to assess progress
against the project plan and take any necessary action to maintain the schedule.
Risk management—assesses risks that may affect the outcome of the project or the
quality of the product.
 Software Engineering Lecture notes

Software quality assurance—defines and conducts the activities required to ensure

software quality.
Technical reviews—assesses software engineering work products in an effort to
uncover and remove errors before they are propagated to the next activity.
Measurement—defines and collects process, project, and product measures that assist
the team in delivering software that meets stakeholders’ needs; can be used in
conjunction with all other framework and umbrella activities.
Software configuration management—manages the effects of change throughout the
software process.
Reusability management—defines criteria for work product reuse (including software
components) and establishes mechanisms to achieve reusable components.
Work product preparation and production—encompasses the activities required to
create work products such as models, documents, logs, forms, and lists.

1.5 Software Engineering Practice

Generic framework activities—communication, planning, modeling, construction, and

deployment—and umbrella activities establish a skeleton architecture for software
engineering work. Practices are as follows
1. Understand the problem (communication and analysis).
2. Plan a solution (modeling and software design).
3. Carry out the plan (code generation).
4. Examine the result for accuracy (testing and quality assurance).

Understand the problem. It’s worth spending a little time to understand, answering a
few simple questions:
• Who has a stake in the solution to the problem? That is, who are the stakeholders?
• What are the unknowns? What data, functions, and features are required to properly
solve the problem?
• Can the problem be compartmentalized? Is it possible to represent smaller problems
that may be easier to understand?
• Can the problem be represented graphically? Can an analysis model be created?

Plan the solution. Now you understand the problem and you can’t wait to begin coding.
Before you do, slow down just a bit and do a little design:
• Have you seen similar problems before? Are there patterns that are recognizable in a
potential solution? Is there existing software that implements the data, functions, and
features that are required?
• Has a similar problem been solved? If so, are elements of the solution reusable?
• Can sub problems be defined? If so, are solutions readily apparent for the sub
problems?
 Software Engineering Lecture notes

• Can you represent a solution in a manner that leads to effective implementation? Can
a design model be created?

Plan the solution. Now you understand the problem (or so you think) and you can’t
wait to begin coding. Before you do, slow down just a bit and do a little design:
• Have you seen similar problems before? Are there patterns that are recognizable in a
potential solution? Is there existing software that implements the data, functions, and
features that are required?
• Has a similar problem been solved? If so, are elements of the solution reusable?
• Can sub problems be defined? If so, are solutions readily apparent for the sub
problems?
• Can you represent a solution in a manner that leads to effective implementation? Can
a design model be created?

Examine the result. You can’t be sure that your solution is perfect, but you can be sure
that you’ve designed a sufficient number of tests to uncover as many errors as possible.
• Is it possible to test each component part of the solution? Has a reasonable testing
strategy been implemented?
• Does the solution produce results that conform to the data, functions, and features that
are required? Has the software been validated against all stakeholder requirements?

1.5.2 General Principles: David Hooker has proposed seven principles that focus on
software engineering practice as a whole. They are as following.

The First Principle: The Reason It All Exists

A software system exists for one reason: to provide value to its users. Before specifying
a system requirement, before noting a piece of system functionality, before determining
the hardware platforms or development processes, ask yourself questions such as:
“Does this add real value to the system?” If the answer is “no,” don’t do it. All other
principles support this one.
The Second Principle: KISS (Keep It Simple, Stupid!)
There are many factors to consider in any design effort. All design should be as simple
as possible, but no simpler. This facilitates having a more easily understood and easily
maintained system. Indeed, the more elegant designs are usually the more simple
ones. The payoff is software that is more maintainable and less error-prone.
The Third Principle: Maintain the Vision
A clear vision is essential to the success of a software project. Without one, a project
almost unfailingly ends up. Compromising the architectural vision of a software system
weakens and will eventually break even the well-designed systems. Having an
empowered architect who can hold the vision and enforce compliance helps ensure a
very successful software project.
The Fourth Principle: What You Produce, Others Will Consume
 Software Engineering Lecture notes

Design, keeping the implementers in mind. Code with concern for those that must
maintain and extend the system. Someone may have to debug the code you write, and
that makes them a user of your code. Making their job easier adds value to the system.
The Fifth Principle: Be Open to the Future
A system with a long lifetime has more value. Never design yourself into a corner.
Always ask “what if,” and prepare for all possible answers by creating systems that
solve the general problem, not just the specific one. This could very possibly lead to the
reuse of an entire system.

The Sixth Principle: Plan Ahead for Reuse

Planning ahead for reuse reduces the cost and increases the value of both the reusable
components and the systems into which they are incorporated.
The Seventh principle: Think!
This last principle is probably the most overlooked. Placing clear, complete thought
before action almost always produces better results. When you think about something,
you are more likely to do it right.

1.6 Software myths

Today, most knowledgeable software engineering professionals recognize myths for

what they are—misleading attitudes that have caused serious problems for managers
and practitioners alike. However, old attitudes and habits are difficult to modify, and
remnants of software myths remain.

Management myths. Managers with software responsibility, like managers in most

disciplines, are often under pressure to maintain budgets, keep schedules from slipping,
and improve quality. Like a drowning person who grasps at a straw, a software manager
often grasps at belief in a software myth, if that belief will lessen the pressure.
Myth: We already have a book that’s full of standards and procedures for building
software. Won’t that provide my people with everything they need to know?
Reality: The book of standards may very well exist, but is it used? Are software
practitioners aware of its existence? Does it reflect modern software engineering
practice? Is it complete? Is it adaptable? Is it streamlined to improve time-to-delivery
while still maintaining a focus on quality? In many cases, the answer to all of these
questions is “no.”
Myth: If we get behind schedule, we can add more programmers and catch up
Reality: Software development is not a mechanistic process like manufacturing. In the
words of Brooks “adding people to a late software project makes it later.” At first, this
statement may seem counterintuitive. However, as new people are added, people who
were working must spend time educating the newcomers, thereby reducing the amount
of time spent on productive development effort. People can be added but only in a
planned and well coordinated manner.
 Software Engineering Lecture notes

Myth: If I decide to outsource the software project to a third party, I can just relax and let
that firm build it.
Reality: If an organization does not understand how to manage and control software
projects internally, it will invariably struggle when it outsources software projects.

Customer myths. A customer who requests computer software may be a person at the
next desk, a technical group down the hall, the marketing/sales department, or an
outside company that has requested software under contract. In many cases, the
customer believes myths about software because software managers and practitioners
do little to correct misinformation. Myths lead to false expectations and, ultimately,
dissatisfaction with the developer.
Myth: A general statement of objectives is sufficient to begin writing programs—we can
fill in the details later.
Reality: Although a comprehensive and stable statement of requirements is not always
possible, an ambiguous “statement of objectives” is a recipe for disaster. Unambiguous
requirements are developed only through effective and continuous communication
between customer and developer.
Myth: Software requirements continually change, but change can be easily
accommodated because software is flexible.
Reality: It is true that software requirements change, but the impact of change varies
with the time at which it is introduced. When requirements changes are requested early
the cost impact is relatively small.16 However, as time passes, the cost impact grows
rapidly—resources have been committed, a design framework has been established,
and change can cause upheaval that requires additional resources and major design
modification.

Practitioner’s myths. Myths that are still believed by software practitioners have been
fostered by over 50 years of programming culture. During the early days, programming
was viewed as an art form. Old ways and attitudes die hard.
Myth: Once we write the program and get it to work, our job is done.
Reality: Someone once said that “the sooner you begin ‘writing code,’ the longer it’ll
take you to get done.” Industry data indicate that between 60 and 80 percent of all effort
expended on software will be expended after it is delivered to the customer for the first
time.
Myth: Until I get the program “running” I have no way of assessing its quality.
Reality: One of the most effective software quality assurance mechanisms can be
applied from the inception of a project—the technical review. Software are a “quality
filter” that have been found to be more effective than testing for finding certain classes
of software defects.
Myth: The only deliverable work product for a successful project is the working
program.
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Reality: A working program is only one part of a software configuration that includes
many elements. A variety of work products provide a foundation for successful
engineering and, more important, guidance for software support.
Myth: Software engineering will make us create voluminous and unnecessary
documentation and will invariably slow us down.
Reality: Software engineering is not about creating documents. It is about creating a
quality product. Better quality leads to reduced rework. And reduced rework results in
faster delivery times.

PROCESS MODELS

What is it? When you work to build a product or system, it’s important to go through
a series of predictable steps—a road map that helps you create a timely, high-quality
result. The road map that you follow is called a “software process.”
Who does it? Software engineers and their managers adapt the process to their
needs and then follow it. In addition, the people who have requested the software
have a role to play in the process of defining, building, and testing it.
Why is it important? Because it provides stability, control, and organization to an
activity that can, if left uncontrolled, become quite chaotic. However, a modern
software engineering approach must be “agile.” It must demand only those activities,
controls, and work products that are appropriate for the project team and the product
that is to be produced.
What are the steps? At a detailed level, the process that you adopt depends on the
software that you’re building. One process might be appropriate for creating software
for an aircraft avionics system, while an entirely different process would be indicated
for the creation of a website.
What is the work product? From the point of view of a software engineer, the work
products are the programs, documents, and data that are produced as a
consequence of the activities and tasks defined by the process.

1.7 A GENERIC PROCESS MODEL

The software process is represented schematically. Framework activity is populated by

a set of software engineering actions. Each software engineering action is defined by a
task set that identifies the work tasks that are to be completed, the work products that
will be produced, the quality assurance points that will be required, and the milestones
that will be used to indicate progress.
 Software Engineering Lecture notes

Generic process framework for software engineering defines five framework activities—
communication, planning, modeling, construction, and deployment. In addition, a set of
umbrella activities—project tracking and control, risk management, quality assurance,
configuration management, technical reviews, and others—are applied throughout the
process.

Process flow—describes how the framework activities and the actions and tasks that
occur within each framework activity are organized with respect to sequence and time
and is illustrated in Figure 2.2.

A linear process flow executes each of the five framework activities in sequence,
beginning with communication and culminating with deployment (Figure 2.2a). An
iterative process flow repeats one or more of the activities before proceeding to the next
(Figure 2.2b). An evolutionary process flow executes the activities in a “circular”
manner. Each circuit through the five activities leads to a more complete version of the
software (Figure 2.2c). A parallel process flow (Figure 2.2d) executes one or more
activities in parallel with other activities.
 Software Engineering Lecture notes

1.7.1 Defining a Framework Activity: A software team would need significantly more
information before it could properly execute any one of these five activities
(Communication, Planning, Modeling, Construction, Deployment) as part of the software
process. For a small software project requested by one person (at a remote location)
with simple, straightforward requirements, the communication activity might encompass
little more than a phone call with the appropriate stakeholder. Therefore, the only
necessary action is phone conversation, and the work tasks (the task set) that this
action encompasses are:
1. Make contact with stakeholder via telephone.
2. Discuss requirements and take notes.
3. Organize notes into a brief written statement of requirements.
4. E-mail to stakeholder for review and approval.
If the project was considerably more complex with many stakeholders, each with
a different set of requirements, the communication activity might have six distinct
actions: inception, elicitation, elaboration, negotiation, specification, and
validation. Each of these software engineering actions would have many work tasks
and a number of distinct work products.
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1.7.2 Identifying a Task Set: Each software engineering action can be represented by
a number of different task sets—each a collection of software engineering work tasks,
related work products, quality assurance points, and project milestones. You should
choose a task set that best accommodates the needs of the project and the
characteristics of your team.

1.7.3 Process Patterns

A process pattern describes a process-related problem that is encountered during
software engineering work, identifies the environment in which the problem has been
encountered, and suggests one or more proven solutions to the problem. Stated in
more general terms, a process pattern provides you with a template. Ambler has
proposed a template for describing a process pattern:
Pattern Name. The pattern is given a meaningful name describing it within the context
of the software process
Type. The pattern type is specified. They are three types:
1. Stage pattern—defines a problem associated with a framework activity for the
process.
2. Task pattern—defines a problem associated with a software engineering action or
work task and relevant to successful software engineering practice
3. Phase pattern—define the sequence of framework activities that occurs within the
process, even when the overall flow of activities is iterative in nature.
Initial context. Describes the conditions under which the pattern applies.
Problem. The specific problem to be solved by the pattern.
Solution. Describes how to implement the pattern successfully.
Resulting Context. Describes the conditions that will result once the pattern has been
successfully implemented. Upon completion of the pattern.
Related Patterns. Provide a list of all process patterns that are directly related to this
one.
Known Uses and Examples. Indicate the specific instances in which the pattern is
applicable.

1.8 PROCESS ASSESSMENT AND IMPROVEMENT

A number of different approaches to software process assessment and improvement

have been proposed.
Standard CMMI Assessment Method for Process Improvement (SCAMPI)—
provides a five-step process assessment model that incorporates five phases: initiating,
diagnosing, establishing, acting, and learning. The SCAMPI method uses the SEI CMMI
as the basis for assessment.
 Software Engineering Lecture notes

CMM-Based Appraisal for Internal Process Improvement (CBA IPI)— provides a

diagnostic technique for assessing the relative maturity of a software organization; uses
the SEI CMM as the basis for the assessment.
SPICE (ISO/IEC15504)—a standard that defines a set of requirements for software
process assessment. The intent of the standard is to assist organizations in developing
an objective evaluation of the efficacy of any defined software process.
ISO 9001:2000 for Software—a generic standard that applies to any organization that
wants to improve the overall quality of the products, systems, or services that it
provides. Therefore, the standard is directly applicable to software organizations and
companies.

1.9 PRESCRIPTIVE PROCESS MODELS

Prescriptive process models define a prescribed set of process elements and a

predictable process work flow. Prescriptive process models were originally proposed to
bring order to the chaos of software development.

All software process models can accommodate the generic framework activities, but
each applies a different emphasis to these activities and defines a process flow that
invokes each framework activity in a different manner.

1.9.1 The Waterfall Model: There are times when the requirements for a problem are
well understood—when work flows from communication through deployment in a
reasonably linear fashion. The waterfall model, sometimes called the classic life cycle,
suggests a systematic, sequential approach6 to software development that begins with
customer specification of requirements and progresses through planning, modeling,
construction, and deployment, culminating in ongoing support of the completed software
(Figure 2.3).

A variation in the representation of the waterfall model is called the V-model.

Represented in Figure 2.4, the V-model depicts the relationship of quality assurance
 Software Engineering Lecture notes

actions to the actions associated with communication, modeling, and early construction
activities. As a software team moves down the left side of the V, basic problem
requirements are refined into progressively more detailed and technical representations
of the problem and its solution. Once code has been generated, the team moves up the
right side of the V, essentially performing a series of tests (quality assurance actions)
that validate each of the models created as the team moved down the left side.7 In
reality, there is no fundamental difference between the classic life cycle and the V-
model. The V-model provides a way of visualizing how verification and validation
actions are applied to earlier engineering work.

The waterfall model is the oldest paradigm, the problems that are sometimes
encountered when the waterfall model is applied are:
1. Real projects rarely follow the sequential flow that the model proposes. Although the
linear model can accommodate iteration, it does so indirectly. As a result, changes can
cause confusion as the project team proceeds.
2. It is often difficult for the customer to state all requirements explicitly. The waterfall
model requires this and has difficulty accommodating the natural uncertainty that exists
at the beginning of many projects.
 Software Engineering Lecture notes

3. The customer must have patience. A working version of the program(s) will not be
available until late in the project time span. A major blunder, if undetected until the
working program is reviewed, can be disastrous.

1.9.2 Incremental Process Models: The incremental model delivers a series of

releases, called increments, that provide progressively more functionality for the
customer as each increment is delivered.

There are many situations in which initial software requirements are reasonably well
defined, but the overall scope of the development effort precludes a purely linear
process. In addition, there may be a compelling need to provide a limited set of software
functionality to users quickly and then refine and expand on that functionality in later
software releases. In such cases, you can choose a process model that is designed to
produce the software in increments.

The incremental model combines elements of linear and parallel process flows.
Referring to Figure 2.5, the incremental model applies linear sequences in a staggered
fashion as calendar time progresses. Each linear sequence produces deliverable
“increments” of the software in a manner that is similar to the increments produced by
an evolutionary process flow.

When an incremental model is used, the first increment is often a core product. That is,
basic requirements are addressed but many supplementary features remain
undelivered. The core product is used by the customer. As a result of use and/or
evaluation, a plan is developed for the next increment. The plan addresses the
modification of the core product to better meet the needs of the customer and the
 Software Engineering Lecture notes

delivery of additional features and functionality. This process is repeated following the
delivery of each increment, until the complete product is produced.
The incremental process model focuses on the delivery of an operational product with
each increment. Early increments are stripped-down versions of the final product, but
they do provide capability that serves the user and also provide a platform for evaluation
by the user. Incremental development is particularly useful when staffing is unavailable
for a complete implementation by the business deadline that has been established for
the project.

1.9.3 Evolutionary Process Models: Evolutionary process models produce an

increasingly more complete version of the software with each iteration.

Software, like all complex systems, evolves over a period of time. Business and product
requirements often change as development proceeds, making a straight line path to an
end product unrealistic; tight market deadlines make completion of a comprehensive
software product impossible, but a limited version must be introduced to meet
competitive or business pressure.
.
Evolutionary models are iterative. They are characterized in a manner that enables you
to develop increasingly more complete versions of the software. The two common
evolutionary process models are presented here.

Prototyping: Often, a customer defines a set of general objectives for software, but
does not identify detailed requirements for functions and features. In other cases, the
developer may be unsure of the efficiency of an algorithm, the adaptability of an
operating system, or the form that human-machine interaction should take. In these,
and many other situations, a prototyping paradigm may offer the best approach.

Regardless of the manner in which it is applied, the prototyping paradigm assists you
and other stakeholders to better understand what is to be built when requirements are
fuzzy.

The prototyping paradigm (Figure 2.6) begins with communication. You meet with other
stakeholders to define the overall objectives for the software, identify whatever
requirements are known, and outline areas where further definition is mandatory. A
Prototyping iteration is planned quickly, and modeling occurs. A quick design focuses
on a representation of those aspects of the software that will be visible to end users.

The quick design leads to the construction of a prototype. The prototype is deployed
and evaluated by stakeholders, who provide feedback that is used to further refine
requirements. Iteration occurs as the prototype is tuned to satisfy the needs of various
 Software Engineering Lecture notes

stakeholders, while at the same time enabling you to better understand what needs to
be done.

Prototyping can be problematic for the following reasons:

1. Stakeholders see what appears to be a working version of the software, unaware that
there is pending work.
2. As a software engineer, you often make implementation compromises in order to get
a prototype working quickly.

The Spiral Model. Originally proposed by Barry Boehm, the spiral model is an
evolutionary software process model that couples the iterative nature of prototyping with
the controlled and systematic aspects of the waterfall model. Boehm describes the
model in the following manner:

The spiral development model is a risk-driven process model generator that is used to
guide multi-stakeholder concurrent engineering of software intensive systems. It has
two main distinguishing features. One is a cyclic approach for incrementally growing a
system’s degree of definition and implementation while decreasing its degree of risk.
The other is a set of anchor point milestones for ensuring stakeholder commitment to
feasible and mutually satisfactory system solutions.

Using the spiral model, software is developed in a series of evolutionary releases.

During early iterations, the release might be a model or prototype. During later
iterations, increasingly more complete versions of the engineered system are produced.
 Software Engineering Lecture notes

A spiral model is divided into a set of framework activities defined by the software
engineering team. Each of the framework activities represent one segment of the spiral
path illustrated in Figure 2.7.

As this evolutionary process begins, the software team performs activities that are
implied by a circuit around the spiral in a clockwise direction, beginning at the center.
Risk is considered as each revolution is made. Anchor point milestones—a combination
of work products and conditions that are attained along the path of the spiral—are noted
for each evolutionary pass.

The first circuit around the spiral might result in the development of a product
specification; subsequent passes around the spiral might be used to develop a
prototype and then progressively more sophisticated versions of the software. Each
pass through the planning region results in adjustments to the project plan. Cost and
schedule are adjusted based on feedback derived from the customer after delivery. In
addition, the project manager adjusts the planned number of iterations required to
complete the software.

Unlike other process models that end when software is delivered, the spiral model can
be adapted to apply throughout the life of the computer software. The spiral model is a
realistic approach to the development of large-scale systems and software. Because
software evolves as the process progresses, the developer and customer better
understand and react to risks at each evolutionary level.

1.9.4 Concurrent Models: The concurrent development model, sometimes called

concurrent engineering, allows a software team to represent iterative and concurrent
elements of any of the process models. Figure 2.8 provides a schematic representation
 Software Engineering Lecture notes

of one software engineering activity within the modeling activity using a concurrent
modeling approach. The activity—modeling—may be in any one of the states noted at
any given time. Similarly,
other activities, actions, or tasks (e.g., communication or construction) can be
represented in an analogous manner. All software engineering activities exist
concurrently but reside in different states.

Concurrent modeling defines a series of events that will trigger transitions from state to
state for each of the software engineering activities, actions, or tasks. For example,
during early stages of design, an inconsistency in the requirements model is uncovered.
This generates the event analysis model correction, which will trigger the requirements
analysis action from the done state into the awaiting changes state. Concurrent odeling
is applicable to all types of software development and provides an accurate picture of
the current state of a project.
 Software Engineering Lecture notes

1.10 SPECIALIZED PROCESS MODELS

These models tend to be applied when a specialized or narrowly defined software

engineering approach is chosen.

1.10.1 Component-Based Development: Commercial off-the-shelf (COTS) software

components, developed by vendors who offer them as products, provide targeted
functionality with well-defined interfaces that enable the component to be integrated into
the software that is to be built. The component-based development model incorporates
many of the characteristics of the spiral model. It is evolutionary in nature, demanding
an iterative approach to the creation of software. However, the component-based
development model constructs applications from prepackaged software components.

Modeling and construction activities begin with the identification of candidate

components. These components can be designed as either conventional software
modules or object-oriented classes or packages of classes. Regardless of the
technology that is used to create the components, the component-based development
model incorporates the following steps

1. Available component-based products are researched and evaluated for the

application domain in question.
2. Component integration issues are considered.
3. A software architecture is designed to accommodate the components.
4. Components are integrated into the architecture.
5. Comprehensive testing is conducted to ensure proper functionality.

The component-based development model leads to software reuse, and reusability

provides software engineers with a number of measurable benefits.

1.10.2 The Formal Methods Model: The formal methods model encompasses a set of
activities that leads to formal mathematical specification of computer software. Formal
methods enable you to specify, develop, and verify a computer-based system by
applying a rigorous, mathematical notation. A variation on this approach, called
cleanroom software engineering, is currently applied by some software development
organizations.

When formal methods are used during design, they serve as a basis for program
verification and therefore enable you to discover and correct errors that might otherwise
go undetected.
 Software Engineering Lecture notes

Although not a mainstream approach, the formal methods model offers the promise of
defect-free software. Yet, concern about its applicability in a business environment has
been voiced:
• The development of formal models is currently quite time consuming and
expensive.
• Because few software developers have the necessary background to apply
formal methods, extensive training is required.
• It is difficult to use the models as a communication mechanism for technically
unsophisticated customers.

1.10.3 Aspect-Oriented Software Development:Regardless of the software process

that is chosen, the builders of complex software invariably implement a set of localized
features, functions, and information content. These localized software characteristics
are modeled as components (e.g., object oriented classes) and then constructed within
the context of a system architecture.

As modern computer-based systems become more sophisticated (and complex), Other

concerns affect functions (e.g., the application of business rules), while others are
systemic (e.g., task synchronization or memory management).

When concerns cut across multiple system functions, features, and information, they
are often referred to as crosscutting concerns. Aspectual requirements define those
crosscutting concerns that have an impact across the software architecture. Aspect-
oriented software development (AOSD), often referred to as aspect-oriented
programming (AOP), is a relatively new software engineering paradigm that provides a
process and methodological approach for defining, specifying, designing, and
constructing aspects.

AOCE uses a concept of horizontal slices through vertically-decomposed software

components, called “aspects,” to characterize cross-cutting functional and non-
functional properties of components. Common, systemic aspects include user
interfaces, collaborative work, distribution, persistency, memory management,
transaction processing, security, integrity and so on.

1.11 The UNIFIED PROCESS

1.11.1 Introduction: The Unified Process is an attempt to draw on the best features
and characteristics of traditional software process models, but haracterize them in a
way that implements many of the best principles of agile software development.

The Unified Process recognizes the importance of customer communication and

streamlined methods for describing the customer’s view of a system. It emphasizes the
 Software Engineering Lecture notes

important role of software architecture and “helps the architect focus on the right goals,
such as understandability, reliance to future changes, and reuse”.

1.11.2 Phases of the Unified Process: The Unified Process is with five basic
framework activities depicted in figure 2.9. It depicts the “phases” of the UP and relates
them to the generic activities.

The inception phase of the UP encompasses both customer communication and

planning activities. The elaboration phase encompasses the communication and
modeling activities of the generic process model. The construction phase of the UP is
identical to the construction activity defined for the generic software process. The
transition phase of the UP encompasses the latter stages of the generic construction
activity and the first part of the generic deployment (delivery and feedback) activity.
Software is given to end users for beta testing and user feedback reports both defects
and necessary changes. In addition, the software team creates the necessary support
information (e.g., user manuals, troubleshooting guides, installation procedures) that is
required for the release. The production phase of the UP coincides with the deployment
activity of the generic process. During this phase, the ongoing use of the software is
monitored, support for the operating environment (infrastructure) is provided, and defect
reports and requests for changes are submitted and evaluated. A software engineering
workflow is distributed across all UP phases.

1.12 PERSONAL AND TEAM PROCESS MODELS

1.12.1 Introduction: If a software process model has been developed at a corporate or

organizational level, it can be effective only if it is agreeable to significant adaptation to
meet the needs of the project team that is actually doing software engineering work. In
 Software Engineering Lecture notes

an ideal setting, you would create a process that best fits your needs, and at the same
time, meets the broader needs of the team and the organization. Alternatively, the team
itself can create its own process, and at the same time meet the narrower needs of
individuals and the broader needs of the organization.

1.12.2 Personal Software Process (PSP): Every developer uses some process to
build computer software. The Personal Software Process (PSP) emphasizes personal
measurement of both the work product that is produced and the resultant quality of the
work product. In addition PSP makes the practitioner responsible for project planning
(e.g., estimating and scheduling) and empowers the practitioner to control the quality of
all software work products that are developed. The PSP model defines five framework
activities:
Planning. This activity isolates requirements and develops both size and resource
estimates. In addition, a defect estimate is made. All metrics are recorded on
worksheets or templates. Finally, development tasks are identified and a project
schedule is created.
High-level design. External specifications for each component to be constructed are
developed and a component design is created. Prototypes are built when uncertainty
exists. All issues are recorded and tracked.
High-level design review. Formal verification methods are applied to uncover errors in
the design. Metrics are maintained for all important tasks and work results.
Development. The component-level design is refined and reviewed. Code is generated,
reviewed, compiled, and tested. Metrics are maintained for all important tasks and work
results.
Postmortem. Using the measures and metrics collected, the effectiveness of the
process is determined. Measures and metrics should provide guidance for modifying the
process to improve its effectiveness.

PSP emphasizes the need to record and analyze the types of errors you make, so that
you can develop strategies to eliminate them.

1.12.3 Team Software Process (TSP): Because many industry-grade software projects
are addressed by a team of practitioners, The goal of TSP is to build a “self-directed”
project team that organizes itself to produce high-quality software.
Humphrey defines the following objectives for TSP:
• Build self-directed teams that plan and track their work, establish goals, and own their
processes and plans. These can be pure software teams or integrated product teams
(IPTs) of 3 to about 20 engineers.
• Show managers how to coach and motivate their teams and how to help them sustain
peak performance.
• Accelerate software process improvement by making CMM Level 5 behavior normal
and expected.
 Software Engineering Lecture notes

• Provide improvement guidance to high-maturity organizations.

• Facilitate university teaching of industrial-grade team skills.

A self-directed team has a consistent understanding of its overall goals and objectives;
defines roles and responsibilities for each team member; tracks quantitative project data
identifies a team process that is appropriate for the project and a strategy for
implementing the process; defines local standards that are applicable to the team’s
software engineering work; continually assesses risk and reacts to it; and tracks,
manages, and reports project status.

TSP defines the following framework activities: project launch, high-level design,
implementation, integration and test, and postmortem.

TSP makes use of a wide variety of scripts, forms, and standards that serve to guide
team members in their work. TSP recognizes that the best software teams are self-
directed. Team members set project objectives, adapt the process to meet their needs,
control the project schedule, and through measurement and analysis of the metrics
collected, work continually to improve the team’s approach to software engineering.

1.13 PROCESS TECHNOLOGY

Process technology tools allow a software organization to build an automated model of

the process framework, task sets, and umbrella activities. The model, normally
represented as a network, can then be analyzed to determine typical workflow and
examine alternative process structures that might lead to reduced development time or
cost.

Once an acceptable process has been created, other process technology tools can be
used to allocate, monitor, and even control all software engineering activities, actions,
and tasks defined as part of the process model. Each member of a software team can
use such tools to develop a checklist of work tasks to be performed, work products to be
produced, and quality assurance activities to be conducted. The process technology
tool can also be used to coordinate the use of other software engineering tools that are
appropriate for a particular work task.

1.14 PRODUCT AND PROCESS

If the process is weak, the end product will undoubtedly suffer. All of human activity
may be a Process. And the outcome of the process is Product.
 Software Engineering Lecture notes

Software is more than just a program code. Software engineering is

an engineering branch associated with development of software product using well-
defined scientific principles, methods and procedures which is process. The outcome
of software engineering is an efficient and reliable software product.

About every ten years give or take five, the software community redefines “the problem”
by shifting its focus from product issues to process issues. Thus, we have embraced
structured programming languages (product) followed by structured analysis methods
(process) followed by data encapsulation (product) followed by the current emphasis on
the Software Engineering Institute’s Software Development Capability Maturity Model
(process)

People: The primary element of any project is the people. People gather requirements,
people interview users (people), people design software, and people write software for
people. No people -- no software.

Process: Process is how we go from the beginning to the end of a project. All projects
use a process. Many project managers, however, do not choose a process based on
the people and product at hand. They simply use the same process they've always used
or misused. Let's focus on two points regarding process: (1) process improvement and
(2) using the right process for the people and product at hand.
 Software Engineering Lecture notes

Product: The product is the result of a project. The desired product satisfies the
customers and keeps them coming back for more. Sometimes, however, the actual
product is something less.

The product pays the bills and ultimately allows people to work together in a process
and build software. Always keep the product in focus. Our current emphasis on process
sometimes causes us to forget the product. This results in a poor product, no money, no
more business, and no more need for people and process.

AGILITY
1.15 WHAT IS AGILITY?

An agile team is a nimble team able to appropriately respond to changes. Change is

what software development is very much about. Changes in the software being built,
changes to the team members, changes because of new technology, changes of all
kinds that may have an impact on the product they build or the project that creates the
product. Support for changes should be built-in everything we do in software, something
we embrace because it is the heart and soul of software. An agile team recognizes that
software is developed by individuals working in teams and that the skills of these
people, their ability to collaborate is at the core for the success of the project.

It encourages team structures and attitudes that make communication (among team
members, between technologists and business people, between software engineers
and their managers) more facile. It emphasizes rapid delivery of operational software
and de-emphasizes the importance of intermediate work products.

Agility can be applied to any software process. However, to accomplish this, it is

essential that the process be designed in a way that allows the project team to adapt
tasks and to streamline them, conduct planning in a way that understands the fluidity of
an agile development approach, eliminate all but the most essential work products and
keep them lean, and emphasize an incremental delivery strategy that gets working
software to the customer as rapidly as feasible for the product type and operational
environment.

1.16 AGILITY AND THE COST OF CHANGE

The conventional wisdom in software development is that the cost of change increases
nonlinearly as a project progresses (Figure: solid black curve). It is relatively easy to
accommodate a change when a software team is gathering requirements (early in a
 Software Engineering Lecture notes

project). A usage scenario might have to be modified, a list of functions may be

extended, or a written specification can be edited. The costs of doing this work are
minimal, and the time required will not adversely affect the outcome of the project.

The change requires a modification to the architectural design of the software, the
design and construction of three new components, modifications to another five
components, the design of new tests, and so on. Costs escalate quickly, and the time
and cost required to ensure that the change is made without unintended side effects is
nontrivial. Although debate about the degree to which the cost curve flattens is
ongoing, there is evidence to suggest that a significant reduction in the cost of change
can be achieved.

1.17 WHAT IS AN AGILE PROCESS?

Any agile software process is characterized in a manner that addresses a number of

key assumptions about the majority of software projects:
1. It is difficult to predict in advance which software requirements will persist and which
will change. It is equally difficult to predict how customer priorities will change as the
project proceeds.
2. For many types of software, design and construction are interleaved. That is, both
activities should be performed in tandem so that design models are proven as they are
created. It is difficult to predict how much design is necessary before construction is
used to prove the design.
3. Analysis, design, construction, and testing are not as predictable as we might like.
Given these three assumptions, an important question arises: How do we create a
process that can manage unpredictability? The answer, as I have already noted, lies in
process adaptability. An agile process, therefore, must be adaptable. But continual
adaptation without forward progress accomplishes little. Therefore, an agile software
 Software Engineering Lecture notes

process must adapt incrementally. To accomplish incremental adaptation, an agile team

requires customer feedback. An effective catalyst for customer feedback is an
operational prototype or a portion of an operational system. Hence, an incremental
development strategy should be instituted. Software increments must be delivered in
short time periods so that adaptation keeps pace with change. This iterative approach
enables the customer to evaluate the software increment regularly, provide necessary
feedback to the software team, and influence the process adaptations that are made to
accommodate the feedback.

1.17.1 Agility Principles: The Agile Alliance defines 12 agility principles for those who
want to achieve agility:
1. Our highest priority is to satisfy the customer through early and continuous delivery of
valuable software.
2. Welcome changing requirements, even late in development. Agile processes harness
change for the customer’s competitive advantage.
3. Deliver working software frequently, from a couple of weeks to a couple of months,
with a preference to the shorter timescale.
4. Business people and developers must work together daily throughout the project.
5. Build projects around motivated individuals. Give them the environment and support
they need, and trust them to get the job done.
6. The most efficient and effective method of conveying information to and within a
development team is face-to-face conversation.
7. Working software is the primary measure of progress.
8. Agile processes promote sustainable development. The sponsors, developers, and
users should be able to maintain a constant pace indefinitely.
9. Continuous attention to technical excellence and good design enhances agility.
10. Simplicity—the art of maximizing the amount of work not done—is essential.
11. The best architectures, requirements, and designs emerge from self–organizing
teams.
12. At regular intervals, the team reflects on how to become more effective, then tunes
and adjusts its behavior accordingly.

1.17.2 The Politics of Agile Development: There is considerable debate about the
benefits and applicability of agile software development as opposed to more
conventional software engineering processes. No one is against agility. The real
question is: What is the best way to achieve it? As important, how do you build software
that meets customers’ needs today and exhibits the quality characteristics that will
enable it to be extended and scaled to meet customers’ needs over the long term?

There are no absolute answers to either of these questions. Even within the agile school
itself, there are many proposed process models, each with a subtly different approach
to the agility problem. Within each model there is a set of “ideas” that represent a
 Software Engineering Lecture notes

significant departure from traditional software engineering. And yet, many agile
concepts are simply adaptations of good software engineering concepts. Bottom line:
there is much that can be gained by considering the best of both schools and virtually
nothing to be gained by denigrating either approach.

1.17.3 Human Factors: Proponents of agile software development take great pains to
emphasize the importance of “people factors.” If members of the software team are to
drive the characteristics of the process that is applied to build software, a number of key
traits must exist among the people on an agile team and the team itself:
Competence: In an agile development (as well as software engineering) context,
“competence” encompasses innate talent, specific software-related skills, and overall
knowledge of the process that the team has chosen to apply. Skill and knowledge of
process can and should be taught to all people who serve as agile team members.
Common focus:. Although members of the agile team may perform different tasks and
bring different skills to the project, all should be focused on one goal—to deliver a
working software increment to the customer within the time promised. To achieve this
goal, the team will also focus on continual adaptations (small and large) that will make
the process fit the needs of the team.
Collaboration: Software engineerinG is about assessing, analyzing, and using
information that is communicated to the software team; creating information that will
help all stakeholders understand the work of the team; and building information that
provides business value for the customer. To accomplish these tasks, team members
must collaborate—with one another and all other stakeholders.
Decision-making ability. Any good software team must be allowed the freedom to
control its own destiny. This implies that the team is given autonomy—decision-making
authority for both technical and project issues.
Fuzzy problem-solving ability. Software managers must recognize that the agile team
will continually have to deal with ambiguity and will continually be buffeted by change. In
some cases, the team must accept the fact that the problem they are solving today may
not be the problem that needs to be solved tomorrow. However, lessons learned from
any problem-solving. activity (including those that solve the wrong problem) may be of
benefit to the team later in the project.
Mutual trust and respect. The agile team must become what DeMarco and Lister call
a “jelled” team. A jelled team exhibits the trust and respect that are necessary to make
them “so strongly knit that the whole is greater than the sum of the parts.”
Self-organization. In the context of agile development, self-organization implies three
things: (1) the agile team organizes itself for the work to be done, (2) the team
organizes the process to best accommodate its local environment, (3) the team
organizes the work schedule to best achieve delivery of the software increment. Self-
organization has a number of technical benefits, but more importantly, it serves to
improve collaboration and boost team morale. In essence, the team serves as its own
management.
 Software Engineering Lecture notes

1.18 EXTREME PROGRAMMING (XP)

Extreme Programming (XP), the most widely used approach to agile software
development.
1.18.1 XP Values: Beck defines a set of five values that establish a foundation for all
work performed as part of XP—communication, simplicity, feedback, courage, and
respect. Each of these values is used as a driver for specific XP activities, actions, and
tasks.
Communication: In order to achieve effective communication between software
engineers and other stakeholders (e.g., to establish required features and functions for
the software), XP emphasizes close, yet informal (verbal) collaboration between
customers and developers, the establishment of effective metaphors for communicating
important concepts, continuous feedback, and the avoidance of voluminous
documentation as a communication medium.
Simplicity: To achieve simplicity, XP restricts developers to design only for immediate
needs, rather than consider future needs. The intent is to create a simple design that
can be easily implemented in code. If the design must be improved, it can be refactored
at a later time.
Feedback: It is derived from three sources: the implemented software itself, the
customer, and other software team members. By designing and implementing an
effective testing strategy, the software provides the agile team with feedback The
degree to which the software implements the output, function, and behavior of the use
case is a form of feedback. Finally, as new requirements are derived as part of iterative
planning, the team provides the customer with rapid feedback regarding cost and
schedule impact.
Courage: Beck argues that strict adherence to certain XP practices demands courage.
A better word might be discipline. An agile XP team must have the discipline (courage)
to design for today, recognizing that future requirements may change dramatically,
thereby demanding substantial rework of the design and implemented code.
Respect: By following each of these values, the agile team inculcates respect among
its members, between other stakeholders and team members, and indirectly, for the
software itself. As they achieve successful delivery of software increments, the team
develops growing respect for the XP process.

1.18.2 The XP Process: Extreme Programming uses an object-oriented approach as its

preferred development paradigm and encompasses a set of rules and practices that
occur within the context of four framework activities: planning, design, coding, and
testing. Figure 3.2 illustrates the XP process .

Planning: The planning activity begins with listening—a requirements gathering

activity that enables the technical members of the XP team to understand the business
 Software Engineering Lecture notes

context for the software and to get a broad feel for required output and major features
and functionality.

Design: XP design rigorously follows the KIS (keep it simple) principle. A simple design
is always preferred over a more complex representation. In addition, the design
provides implementation guidance for a story as it is written—nothing less, nothing
more. If a difficult design problem is encountered as part of the design of a story, XP

recommends the immediate creation of an operational prototype of that portion of the

design. Called a spike solution, the design prototype is implemented and evaluated. A
central notion in XP is that design occurs both before and after coding commences.
Refactoring means that design occurs continuously as the system is constructed. In
fact, the construction activity itself will provide the XP team with guidance on how to
improve the design.
Coding. After stories are developed and preliminary design work is done, the team
does not move to code, but rather develops a series of unit tests that will exercise
each of the stories that is to be included in the current release. Once the unit test has
been created, the developer is better able to focus on what must be implemented to
pass the test. Nothing extraneous is added (KIS). Once the code is complete, it can be
unit-tested immediately, thereby providing instantaneous feedback to the developers.
A key concept during the coding activity is pair programming. XP recommends that two
people work together at one computer workstation to create code for a story. Problem
solving (two heads are often better than one) and real-time quality assurance.
Testing: I have already noted that the creation of unit tests before coding commences
 Software Engineering Lecture notes

is a key element of the XP approach. The unit tests that are created should be
implemented using a framework that enables them to be automated. This encourages a
regression testing strategy whenever code is modified. As the individual unit tests are
organized into a “universal testing suite”.
integration and validation testing of the system can occur on a daily basis. XP
acceptance tests, also called customer tests, are specified by the customer and focus
on overall system features and functionality that are visible and reviewable by the
customer.

1.18.3 Industrial XP: IXP is an organic evolution of XP. It is imbued with XP’s
minimalist, customer-centric, test-driven spirit. IXP incorporates six new practices that
are designed to help ensure that an XP project works successfully for significant
projects within a large organization.
Readiness assessment: Prior to the initiation of an IXP project, the organization should
conduct a readiness assessment. The assessment ascertains whether (1) an
appropriate development environment exists to support IXP, (2) the team will be
populated by the proper set of stakeholders, (3) the organization has a distinct quality
program and supports continuous improvement, (4) the organizational culture will
support the new values of an agile team, and (5) the broader project community will be
populated appropriately.
Project community. Classic XP suggests that the right people be used to populate the
agile team to ensure success. The implication is that people on the team must be well-
trained, adaptable and skilled, and have the proper temperament to contribute to a self-
organizing team. When XP is to be applied for a significant project in a large
organization, the concept of the “team” should morph into that of a community. A
community may have a technologist and customers who are central to the success of a
project as well as many other stakeholders (e.g., legal staff, quality auditors,
manufacturing or sales types) who “are often at the periphery of an IXP project yet they
may play important roles on the project”. In IXP, the community members and their roles
should be explicitly defined and mechanisms for communication and coordination
between community members should be established.
Project chartering. The IXP team assesses the project itself to determine whether an
appropriate business justification for the project exists and whether the project will
further the overall goals and objectives of the organization. Chartering also examines
the context of the project to determine how it complements, extends, or replaces
existing systems or processes.
Test-driven management. An IXP project requires measurable criteria for assessing
the state of the project and the progress that has been made to date. Test-driven
management establishes a series of measurable “destinations” and then defines
mechanisms for determining whether or not these destinations have been reached.
Retrospectives. An IXP team conducts a specialized technical review after a software
increment is delivered. Called a retrospective, the review examines “issues, events, and
 Software Engineering Lecture notes

lessons-learned” across a software increment and/or the entire software release. The
intent is to improve the IXP process. Continuous learning. Because learning is a vital
part of continuous process improvement, members of the XP team are encouraged to
learn new methods and techniques that can lead to a higher quality product.

1.18.4 The XP Debate: Issues that continue to trouble some critics of XP are:
• Requirements volatility. Because the customer is an active member of the XP team,
changes to requirements are requested informally. As a consequence, the scope of the
project can change and earlier work may have to be modified to accommodate current
needs.
• Conflicting customer needs. Many projects have multiple customers, each with his
own set of needs. In XP, the team itself is tasked with assimilating the needs of different
customers, a job that may be beyond their scope of authority.
• Requirements are expressed informally. User stories and acceptance tests are the
only explicit manifestation of requirements in XP. Critics argue that a more formal model
or specification is often needed to ensure that omissions, inconsistencies, and errors
are uncovered before the system is built. Proponents counter that the changing nature
of requirements makes such models and specification obsolete almost as soon as they
are developed.
• Lack of formal design. XP deemphasizes the need for architectural design and in
many instances, suggests that design of all kinds should be relatively informal.

1.19 OTHER AGILE PROCESS MODELS

The most widely used of all agile process models is Extreme Programming (XP). But
many other agile process models have been proposed and are in use across the
industry. Among the most common are:
• Adaptive Software Development (ASD)
• Scrum
• Dynamic Systems Development Method (DSDM)
• Crystal
• Feature Drive Development (FDD)
• Lean Software Development (LSD)
• Agile Modeling (AM)
• Agile Unified Process (AUP)

1.19.1 Adaptive Software Development (ASD): Adaptive Software Development

(ASD) has been proposed by Jim Highsmith as a technique for building complex
software and systems. The philosophical underpinnings of ASD focus on human
collaboration and team self-organization.
 Software Engineering Lecture notes

1.19.2 Scrum: Scrum is an agile software development method that was conceived by
Jeff Sutherland in the early 1990s. Scrum principles are consistent with the agile
manifesto and are used to guide development activities within a process that
incorporates the following framework activities: requirements, analysis, design,
evolution, and delivery. Within each framework activity, work tasks occur within a
process pattern called a sprint. The work conducted within a sprint is adapted to the
problem at hand and is defined and often modified in real time by the Scrum team. The
overall flow of the Scrum process is illustrated in Figure
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Scrum emphasizes the use of a set of software process patterns that have proven
effective for projects with tight timelines, changing requirements, and business criticality.
Each of these process patterns defines a set of development actions:
Backlog—a prioritized list of project requirements or features that provide business
value for the customer. Items can be added to the backlog at any time. The product
manager assesses the backlog and updates priorities as required.
Sprints—consist of work units that are required to achieve a requirement defined in the
backlog that must be fit into a predefined time-box.
Changes (e.g., backlog work items) are not introduced during the sprint. Hence, the
sprint allows team members to work in a short-term, but stable environment.
Scrum meetings—are short (typically 15 minutes) meetings held daily by the Scrum
team. Three key questions are asked and answered by all team members:
• What did you do since the last team meeting?
• What obstacles are you encountering?
• What do you plan to accomplish by the next team meeting?
A team leader, called a Scrum master, leads the meeting and assesses the responses
from each person. The Scrum meeting helps the team to uncover potential problems as
early as possible. Also, these daily meetings lead to “knowledge socialization” and
thereby promote a self-organizing team structure.
Demos—deliver the software increment to the customer so that functionality that has
been implemented can be demonstrated and evaluated by the customer. It is important
to note that the demo may not contain all planned functionality, but rather those
functions that can be delivered within the time-box that was established.

1.19.3 Dynamic Systems Development Method (DSDM): The Dynamic Systems

Development Method (DSDM) is an agile software development approach that
“provides a framework for building and maintaining systems which meet tight time
constraints through the use of incremental prototyping in a controlled project
environment”. The DSDM philosophy is borrowed from a modified version of the Pareto
principle—80 percent of an application can be delivered in 20 percent of the time it
would take to deliver the complete (100 percent) application.

DSDM is an iterative software process in which each iteration follows the 80 percent
rule. That is, only enough work is required for each increment to facilitate movement to
the next increment. The remaining detail can be completed later when more business
requirements are known or changes have been requested and accommodated.
DSDM consortium has defined an agile process model, called the DSDM life cycle that
defines three different iterative cycles, preceded by two additional life cycle activities:
Feasibility study—establishes the basic business requirements and constraints
associated with the application to be built and then assesses whether the application is
a viable candidate for the DSDM process.
 Software Engineering Lecture notes

Business study—establishes the functional and information requirements that will

allow the application to provide business value; also, defines the basic application
architecture and identifies the maintainability requirements for the application.
Functional model iteration—produces a set of incremental prototypes that
demonstrate functionality for the customer. The intent during this iterative cycle is to
gather additional requirements by eliciting feedback from users as they exercise the
prototype.
Design and build iteration—revisits prototypes built during functional model iteration to
ensure that each has been engineered in a manner that will enable it to provide
operational business value for end users. In some cases, functional model iteration and
design and build iteration occur concurrently.
Implementation—places the latest software increment into the operational
environment. It should be noted that (1) the increment may not be 100 percent complete
or (2) changes may be requested as the increment is put into place. In either case,
DSDM development work continues by returning to the functional model iteration
activity.

1.19.4 Crystal: To achieve maneuverability, Cockburn and Highsmith have defined a

set of methodologies, each with core elements that are common to all, and roles,
process patterns, work products, and practice that are unique to each. The Crystal
family is actually a set of example agile processes that have been proven effective for
different types of projects. The intent is to allow agile teams to select the member of the
crystal family that is most appropriate for project and environment.

1.19.5 Feature Driven Development (FDD): Like other agile approaches, FDD adopts
a philosophy that (1) emphasizes collaboration among people on an FDD team; (2)
manages problem and project complexity using feature-based decomposition followed
by the integration of software increments, and (3) communication of technical detail
using verbal, graphical, and text-based means. FDD emphasizes software quality
assurance activities by encouraging an incremental development strategy, the use of
design and code inspections, the application of software quality assurance audits, the
collection of metrics, and the use of patterns

In the context of FDD, a feature “is a client-valued function that can be implemented in
two weeks or less”. The emphasis on the definition of features provides the following
benefits:
• Because features are small blocks of deliverable functionality, users can describe
them more easily; understand how they relate to one another more readily; and
better review them for ambiguity, error, or omissions.
• Features can be organized into a hierarchical business-related grouping.
• Since a feature is the FDD deliverable software increment, the team develops
operational features every two weeks.
 Software Engineering Lecture notes

• Because features are small, their design and code representations are easier to
inspect effectively.
• Project planning, scheduling, and tracking are driven by the feature hierarchy,
rather than an arbitrarily adopted software engineering task set.

1.19.6 Lean Software Development (LSD): The lean principles that inspire the LSD
process can be summarized as eliminate waste, build quality in, create knowledge,
defer commitment, deliver fast, respect people, and optimize the whole. Each of these
principles can be adapted to the software process. For example, eliminate waste within
the context of an agile software project can be interpreted to mean (1) adding no
extraneous features or functions, (2) assessing the cost and schedule impact of any
newly requested requirement, (3) removing any superfluous process steps, (4)
establishing mechanisms to improve the way team members find information, (5)
ensuring the testing finds as many errors as possible, (6) reducing the time required to
request and get a decision that affects the software or the process that is applied to
create it, and (7) streamlining the manner in which information is transmitted to all
stakeholders involved in the process.

1.19.7 Agile Modeling (AM): There are many situations in which software engineers
must build large, business critical systems. The scope and complexity of such systems
must be modeled so that (1) all constituencies can better understand what needs to be
accomplished, (2) the problem can be partitioned effectively among the people who
must solve it, and (3) quality can be assessed as the system is being engineered and
built.

Agile modeling adopts all of the values that are consistent with the agile manifesto. The
agile modeling philosophy recognizes that an agile team must have the courage to
make decisions that may cause it to reject a design and re factor. The team must also
 Software Engineering Lecture notes

have the humility to recognize that technologists do not have all the answers and that
business expert and other stakeholders should be respected and embraced. Although
AM suggests a wide array of “core” and “supplementary” modeling principles, those that
make AM unique are:
• Model with a purpose
• Use multiple models
• Travel light
• Content is more important than representation
• Know the models and the tools you use to create them
• Adapt locally

1.19.8 Agile Unified Process (AUP): The Agile Unified Process (AUP) adopts a “serial
in the large” and “iterative in the small” philosophy for building computer-based systems.
By adopting the classic UP phased activities—inception, elaboration, construction, and
transition—AUP provides a serial overlay that enables a team to visualize the overall
process flow for a software project. However, within each of the activities, the team
iterates to achieve agility and to deliver meaningful software increments to end users as
rapidly as possible. Each AUP iteration addresses the following activities
• Modeling. UML representations of the business and problem domains are created.
However, to stay agile, these models should be “just barely good enough” to allow the
team to proceed.
• Implementation. Models are translated into source code.
• Testing. Like XP, the team designs and executes a series of tests to uncover errors
and ensure that the source code meets its requirements.
• Deployment. Like the generic process activity. Deployment in this context focuses on
the delivery of a software increment and the acquisition of feedback from end users.
• Configuration and project management. In the context of AUP, configuration
management addresses change management, risk management, and the control of any
persistent work products that are produced by the team. Project management tracks
and controls the progress of the team and coordinates team activities.
• Environment management. Environment management coordinates a process
infrastructure that includes standards, tools, and other support technology available to
the team.