OpenSZZ - A Free, Open-Source, Web-Accessible Implementation of the SZZ Algorithm

Valentina Lenarduzzi, Fabio Palomba, Taibi 0001 Davide, Damian Andrew Tamburri

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)

Abstract

The accurate identification of defect-inducing commits representsa key problem for researchers interested in studying the naturalness of defects and defining defect prediction models. To tacklethis problem, software engineering researchers have relied on andproposed several implementations of the well-known SliwerskiZimmermann-Zeller (SZZ) algorithm. Despite its popularity andwide usage, no open-source, publicly available, and web-accessibleimplementation of the algorithm has been proposed so far. In thispaper, we prototype and make available one such implementationfor further use by practitioners and researchers alike. The evaluation of the proposed prototype showed competitive results and laysthe foundation for future work. This paper outlines our prototype,illustrating its usage and reporting on its evaluation in action.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE/ACM 28th International Conference on Program Comprehension, ICPC 2020
Pages446-450
Number of pages5
ISBN (Electronic)9781450379588
DOIs
Publication statusPublished - 13 Jul 2020

Bibliographical note

DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

Keywords

  • Open-Source Tools
  • Software Defect Prediction
  • Software Defect Proneness
  • Web APIs

Fingerprint

Dive into the research topics of 'OpenSZZ - A Free, Open-Source, Web-Accessible Implementation of the SZZ Algorithm'. Together they form a unique fingerprint.

Cite this