Helping Developers Help Themselves: Automatic Decomposition of Code Review Changesets

Code Reviews, an important and popular mechanism for quality assurance, are often performed on a change set, a set of modified files that are meant to be committed to a source repository as an atomic action. Understanding a code review is more difficult when the change set consists of multiple, independent, code differences. We introduce CLUSTERCHANGES, an automatic technique for decomposing change sets and evaluate its effectiveness through both a quantitative analysis and a qualitative user study.

[1]  Andrew P. Black,et al.  How we refactor, and how we know it , 2009, 2009 IEEE 31st International Conference on Software Engineering.

[2]  Westley Weimer,et al.  Automatically documenting program changes , 2010, ASE.

[3]  Christian Bird,et al.  Convergent contemporary software peer review practices , 2013, ESEC/FSE 2013.

[4]  Alessandro Orso,et al.  A differencing algorithm for object-oriented programs , 2004, Proceedings. 19th International Conference on Automated Software Engineering, 2004..

[5]  J. Fleiss.  Measuring nominal scale agreement among many raters. , 1971 .

[6]  C. A. R. Hoare,et al.  Differential static analysis: opportunities, applications, and challenges , 2010, FoSER '10.

[7]  Dongmei Zhang,et al.  How do software engineers understand code changes?: an exploratory study in industry , 2012, SIGSOFT FSE.

[8]  Emerson R. Murphy-Hill,et al.  The design of bug fixes , 2013, 2013 35th International Conference on Software Engineering (ICSE).

[9]  Kenny Wong,et al.  Extracting and representing cross-language dependencies in diverse software systems , 2005, 12th Working Conference on Reverse Engineering (WCRE'05).

[10]  D HerbslebJames,et al.  Two case studies of open source software development , 2002 .

[11]  Daniel M. Germán,et al.  Peer Review on Open-Source Software Projects: Parameters, Statistical Models, and Theory , 2014, TSEM.

[12]  Andreas Zeller,et al.  The impact of tangled code changes , 2013, 2013 10th Working Conference on Mining Software Repositories (MSR).

[13]  Daniel M. Germán,et al.  Contemporary Peer Review in Action: Lessons from Open Source Development , 2012, IEEE Software.

[14]  Miryung Kim,et al.  Interactive Code Review for Systematic Changes , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.

[15]  Martin P. Robillard,et al.  Non-essential changes in version histories , 2011, 2011 33rd International Conference on Software Engineering (ICSE).

[16]  Miryung Kim,et al.  LSdiff: a program differencing tool to identify systematic structural differences , 2010, 2010 ACM/IEEE 32nd International Conference on Software Engineering.

[17]  Peter H. Golde,et al.  C# Language Specification , 2003 .

[18]  Shinji Kusumoto,et al.  Hey! are you committing tangled changes? , 2014, ICPC 2014.

[19]  Frank Tip,et al.  Chianti: a tool for change impact analysis of java programs , 2004, OOPSLA.

[20]  Alberto Bacchelli,et al.  Expectations, outcomes, and challenges of modern code review , 2013, 2013 35th International Conference on Software Engineering (ICSE).

[21]  J. Herbsleb,et al.  Two case studies of open source software development: Apache and Mozilla , 2002, TSEM.

[22]  Miryung Kim,et al.  An empirical study of code clone genealogies , 2005, ESEC/FSE-13.

[23]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[24]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[25]  Matthew B. Dwyer,et al.  Differential symbolic execution , 2008, SIGSOFT '08/FSE-16.