A Fault Localization and Debugging Support Framework driven by Bug Tracking Data

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


Fault localization has been determined as a major resource factor in the software development life cycle. Academic fault localization techniques are mostly unknown and unused in professional environments. Although manual debugging approaches can vary significantly depending on bug type (e.g. memory bugs or semantic bugs), these differences are not reflected in most existing fault localization tools. Little research has gone into automated identification of bug types to optimize the fault localization process. Further, existing fault localization techniques leverage on historical data only for augmentation of suspiciousness rankings. This thesis aims to provide a fault localization framework by combining data from various sources to help developers in the fault localization process. To achieve this, a bug classification schema is introduced, benchmarks are created, and a novel fault localization method based on historical data is proposed.
Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 31st International Symposium on Software Reliability Engineering Workshops, ISSREW 2020
EditorsMarco Vieira, Henrique Madeira, Nuno Antunes, Zheng Zheng
PublisherIEEE Computer Society Conference Publishing Services
Number of pages4
ISBN (Electronic)9781728198705
Publication statusPublished - Jan 2021
Event31st International Symposium on Software Reliability Engineering: 2020 ISSRE - Virtual, Coimbra, Portugal
Duration: 12 Oct 202012 Oct 2020


Conference31st International Symposium on Software Reliability Engineering
Abbreviated titleISSRE 2020
CityVirtual, Coimbra
Internet address


  • debugging
  • fault taxonomy
  • bug data mining
  • fault localization

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

Fields of Expertise

  • Information, Communication & Computing


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