Visualization of automated program repair focusing on suspiciousness values

Naoki Tane*, Yusaku Ito, Hironori Washizaki, Yoshiaki Fukazawa

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automated program repair (APR) can realize efficient debugging in software development. Automated program corrections using genetic algorithms (GA) can repair programs, including those with multiple bugs, but the repair process of GA-based APR is difficult to understand using logs because many modification program codes are generated. Consequently, Matsumoto et al. implemented a methodology for visualizing the process. Their proposed methodology provides an intuitive understanding of the conformance values (test case pass rates), generations, states, and operations performed to generate each variant; however, it lacks sufficient information to analyze whether defect localization is appropriate in APR. Herein we propose a new methodology to visualize the impact of fault localization on program evolution in GA-based APR and create a new tool. Additionally, a case study demonstrates the effectiveness of the proposed methodology and future works are considered.

Original languageEnglish
Title of host publicationSEKE 2022 - Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering
PublisherKnowledge Systems Institute Graduate School
Pages243-248
Number of pages6
ISBN (Electronic)1891706543, 9781891706547
DOIs
Publication statusPublished - 2022
Event34th International Conference on Software Engineering and Knowledge Engineering, SEKE 2022 - Pittsburgh, United States
Duration: 2022 Jul 12022 Jul 10

Publication series

NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
ISSN (Print)2325-9000
ISSN (Electronic)2325-9086

Conference

Conference34th International Conference on Software Engineering and Knowledge Engineering, SEKE 2022
Country/TerritoryUnited States
CityPittsburgh
Period22/7/122/7/10

Keywords

  • Automated Program Repair
  • Bug Localization
  • Fault Localization
  • Genetic Algorithm
  • Visualization

ASJC Scopus subject areas

  • Software

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