Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Flexeme: Untangling Commits Using Lexical Flows
  • Publication Type:
  • Authors:
    Partachi P-P, Dash SK, Allamanis M, Barr ET
  • Publisher:
  • Publication date:
  • Published proceedings:
    Proceedings of the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '20
  • Status:
  • Name of conference:
    28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, (ESEC/FSE 2020)
  • Conference start date:
  • Conference finish date:
  • Language:
  • Keywords:
    graph kernels, clustering, commit untangling
Today, most developers bundle changes into commits that they submit to a shared code repository. Tangled commits intermix distinct concerns, such as a bug fix and a new feature. They cause issues for developers, reviewers, and researchers alike: they restrict the usability of tools such as git bisect, make patch comprehension more difficult, and force researchers who mine software repositories to contend with noise. We present a novel data structure, the 𝛿-NFG, a multiversion Program Dependency Graph augmented with name flows. A 𝛿-NFG directly and simultaneously encodes different program versions, thereby capturing commits, and annotates data flow edges with the names/lexemes that flow across them. Our technique, Flexeme, builds a 𝛿-NFG from commits, then applies Agglomerative Clustering using Graph Similarity to that 𝛿-NFG to untangle its commits. At the untangling task on a C# corpus, our implementation, Heddle, improves the state-of-the-art on accuracy by 0.14, achieving 0.81, in a fraction of the time: Heddle is 32 times faster than the previous state-of-the-art.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Dept of Computer Science
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by