SOFTWARE REENGINEERING
SOFTWARE EVOLUTION AND
REENGINEERING
Choiru Za’in
2010
Terminology
• Legacy System :
old method, technology, computer system,
or application program that continues to be
used, typically because it still functions for the
users' needs, even though newer technology
or more efficient methods of performing a
task are now available
.
2
Overview
• Software Evolution
• Software Maintenance
• Evolution Process
• Legacy System
• Reengineering
3
Objectives
• To explain why change is inevitable if software
systems are remain useful
• To discuss software maintenance and
maintenance cost factors
• To describe the processes involved in software
evolution
• To discuss an approach to assessing evolution
strategies for legacy systems
4
Software Change
• Software change is inevitable
– New requirements emerge when the software is used
– The business environment changes
– Errors must be repaired
– New computers and equipment is added to the system
– The performance or reliability of the system may have to
be improved
• A key problem for organizations are implementing
and managing change to their existing software
systems.
5
Software Evolution
• Organizations have huge investments in their
software systems – they are critical business
assets.
• To maintain the value of these assets to the
business, they must be changed and updated.
• The majority of the software budget in large
companies is devoted to evolving existing
software rather than developing new hardware.
6
Lehman’s Law of Software Evolution
• The behaviour evolution of software
– Continuing Change
– Increasing Complexity
– Large Program Evolution
– Invariant Work-Rate
– Conservation of Familiarity
– Continuing Growth
– Declining Quality
– Feedback System
7
Spiral Model Evolution
Specification Implemention
Star t
Release 1
Operation Validation
Release 2
Release 3
8
Program evolution dynamics
• Program evolution dynamics is the study of the
processes of system change.
• After major empirical studies, Lehman and
Belady proposed that there were a number of
‘laws’ which applied to all systems as they
evolved.
• There are sensible observations rather than
laws. They are applicable to large systems
developed by large organisations. Perhaps less
applicable in other cases.
9
Lehman’s Laws
Law Description
Continuing change A program that is used in a real-world environment necessarily
must change or become progressively less useful in that
environment.
Increasing complexity As an evolving program changes, its structure tends to become
more complex. Extra resources must be devoted to preserving
and simplifying the structure.
Large program evolution Program evolution is a self-regulating process. System
attributes such as size, time between releases and the number of
reported errors is approximately invariant for each system
release.
Organisational stability Over a program’s lifetime, its rate of development is
approximately constant and independent of the resources
devoted to system development.
Conservation of Over the lifetime of a system, the incremental change in each
familiarity release is approximately constant.
Continuing growth The functionality offered by systems has to continually increase
to maintain user satisfaction.
Declining quality The quality of systems will appear to be declining unless they
are adapted to changes in their operational environment.
Feedback system Evolution processes incorporate multi-agent, multi-loop
feedback systems and you have to treat them as feedback
systems to achieve significant product improvement.
10
Softaware maintenance
• Modifying a program after it has been put into
use.
• Maintenance does not normally involve major
changes to the system’s architecture.
• Changes are implemented by modifying
existing components and adding new
components to the system.
11
Maintenance is inevitable
• The system requirements are likely to change
while the system is being developed because
the environment is changing. Therefore a
delivered system won't meet its requirements!
• Systems are tightly coupled with their environment. When a
system is installed in an
environment it changes that environment and
therefore changes the system requirements.
• Systems MUST be maintained therefore if they
are to remain useful in an environment.
Type of maintenance
• Maintenance to repair software faults
– Changing a system to correct deficiencies in the way meets
its requirements.
• Maintenance to adapt software to a different operating
environment
– Changing a system so that it operates in a different
environment (computer, OS, etc.) from its initial
implementation.
• Maintenance to add to or modify the system’s functionality
– Modifying the system to satisfy new requirements.
13
Maintenance effort distribution
Fault repair
(17%)
Functionality
Software
addition or
adaptation
modification
(18%)
(65%)
14
System evolution vs decline
• Is the cost of maintenance too high?
• Is the system reliability unacceptable?
• Can the system adapt to further change, and within a
reasonable amount of time?
• Is the system performance still beyond prescribed
constraints?
• Are system function of limited usefulness?
• Can other system do the same job better, faster, cheaper?
• Is the cost of maintaining the hardware great enough to
justify replacing it with cheaper, newer hardware?
15
Maintenance team responsibilities
• Understanding the system • Locating and correcting faults
• Locating information system • Answering questions about the
documentation way the system works
• Keeping system documentation • Restructuring design and code
up to date components
• Extending existing function to • Rewriting design and code
accommodate new or changing components
requirements • Deleting design and code
• Adding new function to the components that are no longer
system useful
• Finding the source of system • Managing changes to the system
failures or problem s as they are made
16
Maintenance Problem
• Staff problem
– Limited understanding
– Management priorities
– Morale
• Technical problem
– Artifacts and paradigms
– Testing difficulties
17
Factors affecting maintenance effort
• Application type
• System novelty
• Turnover and maintenance staff ability
• System life span
• Dependence on changing environment
• Hardware characteristics
• Design quality
• Code quality
• Documentation quality
• Testing quality
18
Measuring maintainability
• Necessary data : • Desirable data :
– Time at which problem is reported – Ratio of total change
– Time lost due to administrative implementation time to total
delay number of change implemented
– Time required to analyze problem – Number unresolved problem
– Time required to specify which – Time spent on unresolved
changes are to be made problems
– Time needed to make the change
– Percentage of changes that
– Time needed to test the change introduce new faults
– Time needed to documented the
– Number of components
change
modified to implement a change
19
Maintenance costs
• Usually greater than development costs (2* to
100* depending on the application).
• Affected by both technical and non-technical
factors.
• Increases as software is maintained.
Maintenance corrupts the software structure so
makes further maintenance more difficult.
• Ageing software can have high support costs
(e.g. old languages, compilers etc.).
20
Development/maintenance costs
System 1
System 2
450 $
0 50 1 00 15 0 200 2 50 3 00 35 0 400 500
Development costs Maintenance costs
21
Maintenance cost factors
• Team stability
– Maintenance costs are reduced if the same staff are involved with
them for some time
• Contractual responsibility
– The developers of a system may have no contractual responsibility for
maintenance so there is no incentive to design for future change.
• Staff skills
– Maintenance staff are often inexperienced and have limited domain
knowledge.
• Program age and structure
– As programs age, their structure is degraded and they become harder
to understand and change
22
Modeling Maintenance Effort (1)
• Belady and Lehman equation:
1. " M = p + K^(c-d)
• M ... total maintenance effort,
• p ... productive efforts,
• c ... complexity caused by lack of structured design and
documentation,
• d ... c reduced by d, the degreee to which the
maintenance team is familiar with the software
• K ... empirical constant determined by comparing this
model with the effort relationships on actual p
23
COCOMO II – Software Understanding
Rating Scale for software understanding increment SU
Very Low Low Nominal High Very High
Very Low Cohesion, Moderately low Reasonably well High Cohesion, Strong modularity
Structure High Coupling, cohesion, high structured, some weak Low coupling Information hiding in
Spaghetti Code coupling areas data and control
structures
No match between Some correlation Moderate correlation Good correlation bet Clear match between
program and between program and between program ween program and program and
Application clarity application world application and application application application world
views views
Obscure code; docu Some code commenta Moderate level of Good code commenta Self descriptive code;
Self descriptiveness mentation missing ry and headers; some code commentary, ry and headers; useful documentation upto
Obscure or obsolete useful documentation headers, documentation; some date, well organized
Documentation weak areas with design rationale
SU increment 50 40 30 20 10
24
Maintenance prediction
• Maintenance prediction is concerned with
assessing which parts of the system may cause
problems and have high maintenance costs
– Change acceptance depends on the maintainability of
the components affected by the change;
– Implementing changes degrades the system and
reduces its maintainability;
– Maintenance costs depend on the number of
changes and costs of change depend on
maintainability.
25
Maintenance prediction
What par ts of the system
will be the most expensive
What parts of the system are to maintain?
most likely to be affected by
change requests?
Predicting
maintainability
What will be the lifetime
maintenance costs of this
Predicting system Predicting system?
changes maintenance
costs
What will be the costs of
How many change maintaining this system
requests can be over the next year?
expected?
26
Change prediction
• Predicting the number of changes requires and understanding
of the relationships between a system and its environment.
• Tightly coupled systems require changes whenever the
environment is changed.
• Factors influencing this relationship are
– Number and complexity of system interfaces;
– Number of inherently volatile system requirements;
– The business processes where the system is used.
Complexity metrics
• Predictions of maintainability can be made by assessing the
complexity of system components.
• Studies have shown that most maintenance effort is spent on
a relatively small number of system components.
• Complexity depends on
– Complexity of control structures;
– Complexity of data structures;
– Object, method (procedure) and module size.
Process metrics
• Process measurements may be used to assess
maintainability
– Number of requests for corrective maintenance;
– Average time required for impact analysis;
– Average time taken to implement a change
request;
– Number of outstanding change requests.
• If any or all of these is increasing, this may
indicate a decline in maintainability.
Evolution processes
• Evolution processes depend on
– The type of software being maintained;
– The development processes used;
– The skills and experience of the people involved.
• Proposals for change are the driver for system
evolution. Change identification and evolution
continue throughout the system lifetime.
Change identification and evolution
Change identification
process
New system Change proposals
Software evolution
process
The system evolution process
Change Impact Release Change System
requests analysis planning implementa tion release
Platform System
Fault repair
adaptation enhancement
Change implementation
Proposed Requirements Requirements Software
changes anal ysis upda ting de velopment
Urgent change requests
• Urgent changes may have to be implemented
without going through all stages of the
software engineering process
– If a serious system fault has to be repaired;
– If changes to the system’s environment (e.g. an OS
upgrade) have unexpected effects;
– If there are business changes that require a very
rapid response (e.g. the release of a competing
product).
Emergency repair
Change Analyse Modify Deliver modified
requests source code sour ce code system
System re-engineering
• Re-structuring or re-writing part or all of a
legacy system without changing its
functionality.
• Applicable where some but not all sub-systems
of a larger system require frequent
maintenance.
• Re-engineering involves adding effort to make
them easier to maintain. The system may be re-structured
and re-documented.
Advantages of reengineering
• Reduced risk
– There is a high risk in new software development.
There may be development problems, staffing
problems and specification problems.
• Reduced cost
– The cost of re-engineering is often significantly
less than the costs of developing new software.
Forward and re-engineering
System Design and New
specification implementation system
Forward eng ineering
Existing Understanding and Re-eng ineer ed
softw are system transf ormation system
Software re-eng ineering
The re-engineering process
Original Program Modularised Original data
program documentation program
Reverse
eng ineering
Data
Source code Program re-eng ineering
translation modularisation
Prog ram
structure
improvement
Structured Re-engineered
prog ram data
Reengineering process activities
• Source code translation
– Convert code to a new language.
• Reverse engineering
– Analyse the program to understand it;
• Program structure improvement
– Restructure automatically for understandability;
• Program modularisation
– Reorganise the program structure;
• Data reengineering
– Clean-up and restructure system data.
Re-engineering approaches
Automa ted pr og ram Pro gram and da ta
restructuring restructuring
Automated sour ce Automa ted restructuring Restructuring plus
code con version with man ual changes architectur al changes
Increased cost
Reengineering cost factors
• The quality of the software to be
reengineered.
• The tool support available for reengineering.
• The extent of the data conversion which is
required.
• The availability of expert staff for
reengineering.
– This can be a problem with old systems based on
technology that is no longer widely used.
Legacy system evolution
• Organisations that rely on legacy systems must choose a
strategy for evolving these systems
– Scrap the system completely and modify business processes so that it
is no longer required;
– Continue maintaining the system;
– Transform the system by re-engineering to improve its maintainability;
– Replace the system with a new system.
• The strategy chosen should depend on the system quality and
its business value.
System quality and business value
High business value
High business value
Low quality
High quality
9
10 8
6
7
Low business value Low business value
Low quality High quality
2 5
1 3 4
System quality
Legacy system categories
• Low quality, low business value
– These systems should be scrapped.
• Low-quality, high-business value
– These make an important business contribution but are expensive to
maintain. Should be re-engineered or replaced if a suitable system is
available.
• High-quality, low-business value
– Replace with COTS, scrap completely or maintain.
• High-quality, high business value
– Continue in operation using normal system maintenance.
Business value assessment
• Assessment should take different viewpoints
into account
– System end-users;
– Business customers;
– Line managers;
– IT managers;
– Senior managers.
• Interview different stakeholders and collate
results.
System quality assessment
• Business process assessment
– How well does the business process support the
current goals of the business?
• Environment assessment
– How effective is the system’s environment and
how expensive is it to maintain?
• Application assessment
– What is the quality of the application software
system?
Business process assessment
• Use a viewpoint-oriented approach and seek answers from
system stakeholders
– Is there a defined process model and is it followed?
– Do different parts of the organisation use different processes for the
same function?
– How has the process been adapted?
– What are the relationships with other business processes and are
these necessary?
– Is the process effectively supported by the legacy application
software?
• Example - a travel ordering system may have a low business
value because of the widespread use of web-based ordering.
Environment assessment 1
Factor Questions
Supplier Is the supplier is still in existence? Is the supplier financially
stability stable and likely to continue in existence? If the supplier is
no longer in business, does someone else maintain the
systems?
Failure rate Does the hardware have a high rate of reported failures?
Does the support software crash and force system restarts?
Age How old is the hardware and software? The older the
hardware and support software, the more obsolete it will be.
It may still function correctly but there could be significant
economic and business benefits to moving to more modern
systems.
Performance Is the performance of the system adequate? Do performance
problems have a significant effect on system users?
Environment assessment 2
Support What local support is required by the hardware and
requirements software? If there are high costs associated with this support,
it may be worth considering system replacement.
Maintenance What are the costs of hardware maintenance and support
costs software licences? Older hardware may have higher
maintenance costs than modern systems. Support software
may have high annual licensing costs.
Interoperability Are there problems interfacing the system to other systems?
Can compilers etc. be used with current versions of the
operating system? Is hardware emulation required?
Application assessment 1
Factor Questions
Understandability How difficult is it to understand the source code of the
current system? How complex are the control structures
that are used? Do variables have meaningful names that
reflect their function?
Documentation What system documentation is available? Is the
documentation complete, consistent and up-to-date?
Data Is there an explicit data model for the system? To what
extent is data duplicated in different files? Is the data used
by the system up-to-date and consistent?
Performance Is the performance of the application adequate? Do
performance problems have a significant effect on system
users?
Application assessment 2
Programming Are modern compilers available for the programming
language language used to develop the system? Is the programming
language still used for new system development?
Configuration Are all versions of all parts of the system managed by a
management configuration management system? Is there an explicit
description of the versions of components that are used in
the current system?
Test data Does test data for the system exist? Is there a record of
regression tests carried out when new features have been
added to the system?
Personnel skills Are there people available who have the skills to maintain
the application? Are there only a limit ed number of people
who understand the system?
System measurement
• You may collect quantitative data to make an
assessment of the quality of the application
system
– The number of system change requests;
– The number of different user interfaces used by
the system;
– The volume of data used by the system.
Key points
• Software development and evolution should
be a single iterative process.
• Lehman’s Laws describe a number of insights
into system evolution.
• Three types of maintenance are bug fixing,
modifying software for a new environment
and implementing new requirements.
• For custom systems, maintenance costs
usually exceed development costs.
Key points
• The process of evolution is driven by requests
for changes from system stakeholders.
• Software re-engineering is concerned with re-
structuring and re-documenting software to
make it easier to change.
• The business value of a legacy system and its
quality should determine the evolution
strategy that is used.
