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Alberto Bacchelli
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2020 – today
- 2024
- [j28]Pooja Rani
, Fernando Petrulio, Alberto Bacchelli:
On Refining the SZZ Algorithm with Bug Discussion Data. Empir. Softw. Eng. 29(5): 115 (2024) - [j27]Lanxin Yang
A prelinary investigation on using multi-task learning to predict change performance in code reviews. Empir. Softw. Eng. 29(6): 157 (2024) - [c90]Pooja Rani
Energy Patterns for Web: An Exploratory Study. ICSE (SEIS) 2024: 12-22 - [c89]Francesco Sovrano
An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms. ICSE (SEIS) 2024: 46-56 - [c88]Carolin E. Brandt
Mind the Gap: What Working With Developers on Fuzz Tests Taught Us About Coverage Gaps. ICSE-SEIP 2024: 157-167 - [c87]Pavlína Wurzel Gonçalves
Constructive Code Review: Managing the Impact of Interpersonal Conflicts in Practice. ICSE-SEIP 2024: 334-345 - [e1]Diomidis Spinellis, Alberto Bacchelli, Eleni Constantinou:
21st IEEE/ACM International Conference on Mining Software Repositories, MSR 2024, Lisbon, Portugal, April 15-16, 2024. ACM 2024, ISBN 979-8-4007-0587-8 [contents] - [i19]Pooja Rani, Jonas Zellweger, Veronika Kousadianos, Luis Cruz, Timo Kehrer, Alberto Bacchelli:
Energy Patterns for Web: An Exploratory Study. CoRR abs/2401.06482 (2024) - 2023
- [j26]Dhivyabharathi Ramasamy
Workflow analysis of data science code in public GitHub repositories. Empir. Softw. Eng. 28(1): 7 (2023) - [j25]Dhivyabharathi Ramasamy
Visualising data science workflows to support third-party notebook comprehension: an empirical study. Empir. Softw. Eng. 28(3): 58 (2023) - [j24]Enrico Fregnan
Graph-based visualization of merge requests for code review. J. Syst. Softw. 195: 111506 (2023) - [j23]Pavlína Wurzel Gonçalves
Competencies for Code Review. Proc. ACM Hum. Comput. Interact. 7(CSCW1): 1-33 (2023) - [j22]Nico Ritschel
Training industrial end-user programmers with interactive tutorials. Softw. Pract. Exp. 53(3): 729-747 (2023) - [c86]Francesco Sovrano, Kevin D. Ashley, Alberto Bacchelli:
Eliminating Hallucinations: GPT-based Explanatory AI for Intelligent Textbooks and Documentation. iTextbooks@AIED 2023: 54-65 - [c85]Lanxin Yang
EvaCRC: Evaluating Code Review Comments. ESEC/SIGSOFT FSE 2023: 275-287 - [c84]Lanxin Yang
Evaluating Learning-to-Rank Models for Prioritizing Code Review Requests using Process Simulation. SANER 2023: 461-472 - [i18]Francesco Sovrano, Michaël Lognoul, Alberto Bacchelli:
An Empirical Study on Compliance with Ranking Transparency in the Software Documentation of EU Online Platforms. CoRR abs/2312.14794 (2023) - 2022
- [j21]Enrico Fregnan
What happens in my code reviews? An investigation on automatically classifying review changes. Empir. Softw. Eng. 27(4): 89 (2022) - [j20]Pavlína Wurzel Gonçalves, Enrico Fregnan
Do explicit review strategies improve code review performance? Towards understanding the role of cognitive load. Empir. Softw. Eng. 27(4): 99 (2022) - [j19]Enrico Fregnan
The evolution of the code during review: an investigation on review changes. Empir. Softw. Eng. 27(7): 177 (2022) - [j18]Pavlína Wurzel Gonçalves, Gül Çalikli, Alberto Bacchelli:
Interpersonal Conflicts During Code Review: Developers' Experience and Practices. Proc. ACM Hum. Comput. Interact. 6(CSCW1): 98:1-98:33 (2022) - [c83]Larissa Braz, Enrico Fregnan, Vivek Arora, Alberto Bacchelli:
An Exploratory Study on Regression Vulnerabilities. ESEM 2022: 12-22 - [c82]Larissa Braz, Christian Aeberhard, Gül Çalikli, Alberto Bacchelli:
Less is More: Supporting Developers in Vulnerability Detection during Code Review. ICSE 2022: 1317-1329 - [c81]Enrico Fregnan, Larissa Braz, Marco D'Ambros, Gül Çalikli, Alberto Bacchelli
First come first served: the impact of file position on code review. ESEC/SIGSOFT FSE 2022: 483-494 - [c80]Larissa Braz, Alberto Bacchelli:
Software security during modern code review: the developer's perspective. ESEC/SIGSOFT FSE 2022: 810-821 - [i17]Pavlína Wurzel Gonçalves, Gül Çalikli, Alberto Bacchelli:
Interpersonal Conflicts During Code Review. CoRR abs/2201.05425 (2022) - [i16]Larissa Braz, Christian Aeberhard, Gül Çalikli, Alberto Bacchelli:
Less is More: Supporting Developers in Vulnerability Detection during Code Review. CoRR abs/2202.04586 (2022) - [i15]Larissa Braz, Enrico Fregnan, Vivek Arora, Alberto Bacchelli:
An Exploratory Study on Regression Vulnerabilities. CoRR abs/2207.01942 (2022) - [i14]Enrico Fregnan, Larissa Braz, Marco D'Ambros, Gül Çalikli, Alberto Bacchelli:
First Come First Served: The Impact of File Position on Code Review. CoRR abs/2208.04259 (2022) - [i13]Larissa Braz, Alberto Bacchelli:
Software Security during Modern Code Review: The Developer's Perspective. CoRR abs/2208.04261 (2022) - [i12]Fernando Petrulio, David Ackermann, Enrico Fregnan, Gül Çalikli, Marco Castelluccio, Sylvestre Ledru, Calixte Denizet, Emma Humphries, Alberto Bacchelli:
SZZ in the time of Pull Requests. CoRR abs/2209.03311 (2022) - 2021
- [j17]Fernando Petrulio, Anand Ashok Sawant
The indolent lambdification of Java. Empir. Softw. Eng. 26(6): 134 (2021) - [c79]Larissa Braz, Enrico Fregnan, Gül Çalikli, Alberto Bacchelli:
Data and Materials for: Why Don't Developers Detect Improper Input Validation?'; DROP TABLE Papers; -. ICSE (Companion Volume) 2021: 203-204 - [c78]Larissa Braz, Enrico Fregnan, Gül Çalikli
Why Don't Developers Detect Improper Input Validation? '; DROP TABLE Papers; -. ICSE 2021: 499-511 - [c77]Egor Bogomolov
Authorship attribution of source code: a language-agnostic approach and applicability in software engineering. ESEC/SIGSOFT FSE 2021: 932-944 - [c76]Lorenzo Gasparini, Enrico Fregnan, Larissa Braz, Tobias Baum, Alberto Bacchelli:
ChangeViz: Enhancing the GitHub Pull Request Interface with Method Call Information. VISSOFT 2021: 115-119 - [i11]Larissa Braz, Enrico Fregnan, Gül Çalikli, Alberto Bacchelli:
Why Don't Developers Detect Improper Input Validation?'; DROP TABLE Papers; -. CoRR abs/2102.06251 (2021) - 2020
- [j16]Luca Pascarella
On the performance of method-level bug prediction: A negative result. J. Syst. Softw. 161 (2020) - [j15]Vladimir Kovalenko
Does Reviewer Recommendation Help Developers? IEEE Trans. Software Eng. 46(7): 710-731 (2020) - [c75]Linda Di Geronimo, Larissa Braz, Enrico Fregnan, Fabio Palomba, Alberto Bacchelli:
UI Dark Patterns and Where to Find Them: A Study on Mobile Applications and User Perception. CHI 2020: 1-14 - [c74]Vladimir Kovalenko, Egor Bogomolov
Building Implicit Vector Representations of Individual Coding Style. ICSE (Workshops) 2020: 117-124 - [c73]Davide Spadini, Gül Çalikli
Primers or reminders?: the effects of existing review comments on code review. ICSE 2020: 1171-1182 - [c72]Davide Spadini, Martin Schvarcbacher, Ana-Maria Oprescu, Magiel Bruntink, Alberto Bacchelli:
Investigating Severity Thresholds for Test Smells. MSR 2020: 311-321 - [c71]Pavlína Wurzel Gonçalves, Enrico Fregnan, Tobias Baum, Kurt Schneider
Do Explicit Review Strategies Improve Code Review Performance? MSR 2020: 606-610 - [d9]Luca Pascarella
Dataset of the paper "Information Needs in Contemporary Code Review". Zenodo, 2020 - [i10]Egor Bogomolov, Vladimir Kovalenko, Alberto Bacchelli, Timofey Bryksin:
Authorship Attribution of Source Code: A Language-Agnostic Approach and Applicability in Software Engineering. CoRR abs/2001.11593 (2020) - [i9]Vladimir Kovalenko, Egor Bogomolov, Timofey Bryksin, Alberto Bacchelli:
Building Implicit Vector Representations of Individual Coding Style. CoRR abs/2002.03997 (2020)
2010 – 2019
- 2019
- [j14]Davide Spadini
Mock objects for testing java systems - Why and how developers use them, and how they evolve. Empir. Softw. Eng. 24(3): 1461-1498 (2019) - [j13]Luca Pascarella
Classifying code comments in Java software systems. Empir. Softw. Eng. 24(3): 1499-1537 (2019) - [j12]Tobias Baum
Associating working memory capacity and code change ordering with code review performance. Empir. Softw. Eng. 24(4): 1762-1798 (2019) - [j11]Anand Ashok Sawant
To react, or not to react: Patterns of reaction to API deprecation. Empir. Softw. Eng. 24(6): 3824-3870 (2019) - [j10]Enrico Fregnan, Tobias Baum, Fabio Palomba
A survey on software coupling relations and tools. Inf. Softw. Technol. 107: 159-178 (2019) - [j9]Luca Pascarella
Fine-grained just-in-time defect prediction. J. Syst. Softw. 150: 22-36 (2019) - [j8]Marco di Biase
The effects of change decomposition on code review - a controlled experiment. PeerJ Comput. Sci. 5: e193 (2019) - [j7]Carmine Vassallo, Giovanni Grano
A large-scale empirical exploration on refactoring activities in open source software projects. Sci. Comput. Program. 180: 1-15 (2019) - [c70]Pavlina Wurzelová, Fabio Palomba, Alberto Bacchelli:
Characterizing women (not) contributing to open-source. GE@ICSE 2019: 5-8 - [c69]Vincent J. Hellendoorn, Sebastian Proksch, Harald C. Gall
When code completion fails: a case study on real-world completions. ICSE 2019: 960-970 - [c68]Davide Spadini, Fabio Palomba, Tobias Baum, Stefan Hanenberg, Magiel Bruntink, Alberto Bacchelli:
Test-driven code review: an empirical study. ICSE 2019: 1061-1072 - [c67]Vladimir Kovalenko, Egor Bogomolov
PathMiner: a library for mining of path-based representations of code. MSR 2019: 13-17 - [c66]Domenico Serra, Giovanni Grano
On the effectiveness of manual and automatic unit test generation: ten years later. MSR 2019: 121-125 - [c65]Mariaclaudia Nicolai, Luca Pascarella
Healthcare Android apps: a tale of the customers' perspective. WAMA@ESEC/SIGSOFT FSE 2019: 33-39 - [c64]Moritz Eck, Fabio Palomba, Marco Castelluccio
Understanding flaky tests: the developer's perspective. ESEC/SIGSOFT FSE 2019: 830-840 - [i8]Moritz Eck, Fabio Palomba, Marco Castelluccio, Alberto Bacchelli:
Understanding Flaky Tests: The Developer's Perspective. CoRR abs/1907.01466 (2019) - [i7]Luca Pascarella, Davide Spadini, Fabio Palomba, Alberto Bacchelli:
On The Effect Of Code Review On Code Smells. CoRR abs/1912.10098 (2019) - 2018
- [j6]Anand Ashok Sawant
On the reaction to deprecation of clients of 4 + 1 popular Java APIs and the JDK. Empir. Softw. Eng. 23(4): 2158-2197 (2018) - [j5]Luca Pascarella
Information Needs in Contemporary Code Review. Proc. ACM Hum. Comput. Interact. 2(CSCW): 135:1-135:27 (2018) - [c63]Vladimir Kovalenko, Alberto Bacchelli:
Code review for newcomers: is it different? CHASE@ICSE 2018: 29-32 - [c62]Luca Pascarella
Self-reported activities of Android developers. MOBILESoft@ICSE 2018: 144-155 - [c61]Caitlin Sadowski, Emma Söderberg, Luke Church, Michal Sipko, Alberto Bacchelli
Modern code review: a case study at google. ICSE (SEIP) 2018: 181-190 - [c60]Anand Ashok Sawant, Maurício Finavaro Aniche, Arie van Deursen, Alberto Bacchelli:
Understanding developers' needs on deprecation as a language feature. ICSE 2018: 561-571 - [c59]Davide Spadini, Maurício Finavaro Aniche, Margaret-Anne D. Storey, Magiel Bruntink, Alberto Bacchelli:
When testing meets code review: why and how developers review tests. ICSE 2018: 677-687 - [c58]Davide Spadini, Fabio Palomba
On the Relation of Test Smells to Software Code Quality. ICSME 2018: 1-12 - [c57]Anand Ashok Sawant, Guangzhe Huang, Gabriel Vilen, Stefan Stojkovski, Alberto Bacchelli:
Why are Features Deprecated? An Investigation Into the Motivation Behind Deprecation. ICSME 2018: 13-24 - [c56]Vladimir Kovalenko, Fabio Palomba
Mining file histories: should we consider branches? ASE 2018: 202-213 - [c55]Carmine Vassallo, Fabio Palomba
Continuous code quality: are we (really) doing that? ASE 2018: 790-795 - [c54]Franz-Xaver Geiger, Ivano Malavolta
A graph-based dataset of commit history of real-world Android apps. MSR 2018: 30-33 - [c53]Luca Pascarella, Fabio Palomba
How is video game development different from software development in open source? MSR 2018: 392-402 - [c52]Achyudh Ram, Anand Ashok Sawant, Marco Castelluccio
What makes a code change easier to review: an empirical investigation on code change reviewability. ESEC/SIGSOFT FSE 2018: 201-212 - [c51]Davide Spadini, Maurício Finavaro Aniche, Alberto Bacchelli:
PyDriller: Python framework for mining software repositories. ESEC/SIGSOFT FSE 2018: 908-911 - [c50]Luca Pascarella, Achyudh Ram, Azqa Nadeem, Dinesh Bisesser, Norman Knyazev, Alberto Bacchelli:
Investigating type declaration mismatches in Python. MaLTeSQuE 2018: 43-48 - [c49]Luca Pascarella, Fabio Palomba
Re-evaluating method-level bug prediction. SANER 2018: 592-601 - [d8]Vladimir Kovalenko
Data and material for: "Mining file histories: should we consider branches?". Zenodo, 2018 - [d7]Luca Pascarella
On the Performance of Method-Level Bug Prediction: A Negative Result. Appendix. Zenodo, 2018 - [d6]Luca Pascarella
Fine-Grained Just-In-Time Defect Prediction - Appendix. Zenodo, 2018 - [d5]Luca Pascarella
Information Needs in Contemporary Code Review - Appendix. Zenodo, 2018 - [d4]Luca Pascarella
Information Needs in Contemporary Code Review - Appendix. Zenodo, 2018 - [d3]Davide Spadini
When Testing Meets Code Review: Why and How Developers Review Tests. Zenodo, 2018 - [d2]Davide Spadini
When Testing Meets Code Review: Why and How Developers Review Tests (Appendix). Zenodo, 2018 - [d1]Davide Spadini
When Testing Meets Code Review: Why and How Developers Review Tests (Appendix). Zenodo, 2018 - [i6]Marco di Biase, Magiel Bruntink, Arie van Deursen, Alberto Bacchelli:
The effects of change-decomposition on code review - A Controlled Experiment. CoRR abs/1805.10978 (2018) - [i5]Marco di Biase
The effects of change decomposition on code review - a controlled experiment. PeerJ Prepr. 6: e27438 (2018) - 2017
- [j4]Anand Ashok Sawant
fine-GRAPE: fine-grained APi usage extractor - an approach and dataset to investigate API usage. Empir. Softw. Eng. 22(3): 1348-1371 (2017) - [j3]Marco Seeber
Does single blind peer review hinder newcomers? Scientometrics 113(1): 567-585 (2017) - [j2]Alberto Bacchelli
Mining structured data in natural language artifacts with island parsing. Sci. Comput. Program. 150: 31-55 (2017) - [c48]Mark Juchli, Lars Krombeen, Shashank Rao, Chak Shun Yu, Anand Ashok Sawant, Alberto Bacchelli:
Mining Motivated Trends of Usage of Haskell Libraries. WAPI@ICSE 2017: 11-14 - [c47]Alberto Bacchelli, Moritz Beller
Double-blind review in software engineering venues: the community's perspective. ICSE (Companion Volume) 2017: 385-396 - [c46]Tobias Baum, Kurt Schneider
On the Optimal Order of Reading Source Code Changes for Review. ICSME 2017: 329-340 - [c45]Luca Pascarella
Classifying code comments in Java open-source software systems. MSR 2017: 227-237 - [c44]Davide Spadini, Mauricio Finavaro Aniche, Magiel Bruntink, Alberto Bacchelli:
To mock or not to mock?: an empirical study on mocking practices. MSR 2017: 402-412 - 2016
- [c43]Joop Aué, Michiel Haisma, Kristín Fjóla Tómasdóttir, Alberto Bacchelli:
Social Diversity and Growth Levels of Open Source Software Projects on GitHub. ESEM 2016: 41:1-41:6 - [c42]Annibale Panichella, Carol V. Alexandru, Sebastiano Panichella
A Search-based Training Algorithm for Cost-aware Defect Prediction. GECCO 2016: 1077-1084 - [c41]Georgios Gousios
Work practices and challenges in pull-based development: the contributor's perspective. ICSE 2016: 285-296 - [c40]Baishakhi Ray, Vincent J. Hellendoorn, Saheel Godhane, Zhaopeng Tu, Alberto Bacchelli, Premkumar T. Devanbu
On the "naturalness" of buggy code. ICSE 2016: 428-439 - [c39]Anand Ashok Sawant, Romain Robbes, Alberto Bacchelli:
On the Reaction to Deprecation of 25, 357 Clients of 4+1 Popular Java APIs. ICSME 2016: 400-410 - [c38]Marco di Biase
A Security Perspective on Code Review: The Case of Chromium. SCAM 2016: 21-30 - [c37]Sebastiaan Oosterwaal, Arie van Deursen
Visualizing code and coverage changes for code review. SIGSOFT FSE 2016: 1038-1041 - [p2]Alberto Bacchelli:
Structure your unstructured data first! Perspectives on Data Science for Software Engineering 2016: 161-168 - [i4]Moritz Beller
Double blind reviews in software engineering venues: Practicability, promises and perils. PeerJ Prepr. 4: e1757 (2016) - 2015
- [j1]Luigi Cerulo, Massimiliano Di Penta
Irish: A Hidden Markov Model to detect coded information islands in free text. Sci. Comput. Program. 105: 26-43 (2015) - [c36]Anja Guzzi, Alberto Bacchelli
Supporting Developers' Coordination in the IDE. CSCW 2015: 518-532 - [c35]Vincent J. Hellendoorn, Premkumar T. Devanbu
Will They Like This? Evaluating Code Contributions with Language Models. MSR 2015: 157-167 - [c34]Maarten Duijn, Adam Kucera, Alberto Bacchelli:
Quality Questions Need Quality Code: Classifying Code Fragments on Stack Overflow. MSR 2015: 410-413 - [c33]Jeffrey Goderie, Brynjolfur Mar Georgsson, Bastiaan van Graafeiland, Alberto Bacchelli:
ETA: Estimated Time of Answer Predicting Response Time in Stack Overflow. MSR 2015: 414-417 - [c32]Selman Ercan, Quinten Stokkink
Automatic Assessments of Code Explanations: Predicting Answering Times on Stack Overflow. MSR 2015: 442-445 - [c31]Rogier Slag, Mike de Waard, Alberto Bacchelli:
One-Day Flies on StackOverflow - Why the Vast Majority of StackOverflow Users Only Posts Once. MSR 2015: 458-461 - [c30]Anand Ashok Sawant
A Dataset for API Usage. MSR 2015: 506-509 - [c29]Martin Dias, Alberto Bacchelli
Untangling fine-grained code changes. SANER 2015: 341-350 - [p1]Peter C. Rigby, Alberto Bacchelli, Georgios Gousios
A Mixed Methods Approach to Mining Code Review Data. The Art and Science of Analyzing Software Data 2015: 231-255 - [i3]Martin Dias, Alberto Bacchelli, Georgios Gousios, Damien Cassou, Stéphane Ducasse:
Untangling Fine-Grained Code Changes. CoRR abs/1502.06757 (2015) - [i2]Baishakhi Ray, Vincent J. Hellendoorn, Zhaopeng Tu, Connie Nguyen, Saheel Godhane, Alberto Bacchelli, Premkumar T. Devanbu:
On the "Naturalness" of Buggy Code. CoRR abs/1506.01159 (2015) - [i1]Carol V. Alexandru, Annibale Panichella, Sebastiano Panichella, Alberto Bacchelli, Harald C. Gall
Smart learning: A search-based approach to rank change and defect prone classes. PeerJ Prepr. 3: e1160 (2015) - 2014
- [c28]Luca Ponzanelli
Improving Low Quality Stack Overflow Post Detection. ICSME 2014: 541-544 - [c27]Moritz Beller
Modern code reviews in open-source projects: which problems do they fix? MSR 2014: 202-211 - [c26]Luca Bigliardi, Michele Lanza, Alberto Bacchelli, Marco D'Ambros, Andrea Mocci
Quantitatively Exploring Non-code Software Artifacts. QSIC 2014: 286-295 - [c25]Luca Ponzanelli
Understanding and Classifying the Quality of Technical Forum Questions. QSIC 2014: 343-352 - 2013
- [c24]Luca Ponzanelli
Leveraging Crowd Knowledge for Software Comprehension and Development. CSMR 2013: 57-66 - [c23]Alberto Bacchelli
Expectations, outcomes, and challenges of modern code review. ICSE 2013: 712-721 - [c22]Luca Ponzanelli
Seahawk: stack overflow in the IDE. ICSE 2013: 1295-1298 - [c21]Lori L. Pollock, David W. Binkley, Dawn J. Lawrie
1st international workshop on natural language analysis in software engineering (NaturaLiSE 2013). ICSE 2013: 1537-1538 - [c20]Emily Hill, Alberto Bacchelli, Dave W. Binkley, Bogdan Dit, Dawn J. Lawrie, Rocco Oliveto:
Which Feature Location Technique is Better? ICSM 2013: 408-411 - [c19]Michele Lanza, Marco D'Ambros, Alberto Bacchelli, Lile Hattori, Francesco Rigotti:
Manhattan: Supporting real-time visual team activity awareness. ICPC 2013: 207-210 - [c18]Anja Guzzi, Alberto Bacchelli, Michele Lanza, Martin Pinzger, Arie van Deursen
Communication in open source software development mailing lists. MSR 2013: 277-286 - [c17]Alberto Bacchelli, Nicolas Bettenburg, Latifa Guerrouj, Sonia Haiduc:
3rd workshop on Mining Unstructured Data. WCRE 2013: 491-492 - 2012
- [c16]Alberto Bacchelli, Luca Ponzanelli
Harnessing stack overflow for the IDE. RSSE@ICSE 2012: 26-30 - [c15]Alberto Bacchelli, Tommaso Dal Sasso, Marco D'Ambros, Michele Lanza:
Content classification of development emails. ICSE 2012: 375-385 - [c14]Alberto Bacchelli, Nicolas Bettenburg, Latifa Guerrouj:
Workshop on Mining Unstructured Data (MUD) ... Because "Mining Unstructured Data is Like Fishing in Muddy Waters"! WCRE 2012: 5-6 - 2011
- [c13]Lile Hattori, Alberto Bacchelli, Michele Lanza, Mircea Lungu:
Erase and rewind - Learning by replaying examples. CSEE&T 2011: 558 - [c12]Alberto Bacchelli, Michele Lanza, Vitezslav Humpa:
RTFM (Read the Factual Mails) - Augmenting Program Comprehension with Remail. CSMR 2011: 15-24 - [c11]Alberto Bacchelli, Michele Lanza, Marco D'Ambros:
Miler: a toolset for exploring email data. ICSE 2011: 1025-1027 - [c10]Alberto Bacchelli:
Exploring, exposing, and exploiting emails to include human factors in software engineering. ICSE 2011: 1074-1077 - [c9]Alberto Bacchelli, Anthony Cleve, Michele Lanza, Andrea Mocci
Extracting structured data from natural language documents with island parsing. ASE 2011: 476-479 - 2010
- [c8]Alberto Bacchelli, Marco D'Ambros, Michele Lanza:
Are Popular Classes More Defect Prone? FASE 2010: 59-73 - [c7]Alberto Bacchelli, Michele Lanza, Romain Robbes
Linking e-mails and source code artifacts. ICSE (1) 2010: 375-384 - [c6]Alberto Bacchelli, Michele Lanza, Vitezslav Humpa:
Towards integrating e-mail communication in the IDE. SUITE@ICSE 2010: 1-4 - [c5]Alberto Bacchelli, Marco D'Ambros, Michele Lanza:
Extracting Source Code from E-Mails. ICPC 2010: 24-33 - [c4]Marco D'Ambros, Alberto Bacchelli, Michele Lanza:
On the Impact of Design Flaws on Software Defects. QSIC 2010: 23-31
2000 – 2009
- 2009
- [c3]Alberto Bacchelli, Michele Lanza, Marco D'Ambros:
Miler - A Tool Infrastructure to Analyze Mailing Lists. FAMOOSr@WCRE 2009: 12-15 - [c2]Alberto Bacchelli, Marco D'Ambros, Michele Lanza, Romain Robbes
Benchmarking Lightweight Techniques to Link E-Mails and Source Code. WCRE 2009: 205-214 - 2008
- [c1]Alberto Bacchelli, Paolo Ciancarini
On the Effectiveness of Manual and Automatic Unit Test Generation. ICSEA 2008: 252-257
Coauthor Index
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