research-article

Influential Global and Local Contexts Guided Trace Representation for Fault Localization

Authors:

Yue YuAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology, Volume 32, Issue 3

Article No.: 78, Pages 1 - 27

https://doi.org/10.1145/3576043

Published: 26 April 2023 Publication History

Abstract

Trace data is critical for fault localization (FL) to analyze suspicious statements potentially responsible for a failure. However, existing trace representation meets its bottleneck mainly in two aspects: (1) the trace information of a statement is restricted to a local context (i.e., a test case) without the consideration of a global context (i.e., all test cases of a test suite); (2) it just uses the ‘occurrence’ for representation without strong FL semantics.

Thus, we propose UNITE: an inflUential coNtext-GuIded Trace rEpresentation, representing the trace from both global and local contexts with influential semantics for FL. UNITE embodies and implements two key ideas: (1) UNITE leverages the widely used weighting capability from local and global contexts of information retrieval to reflect how important a statement (a word) is to a test case (a document) in all test cases of a test suite (a collection), where a test case (a document) and all test cases of a test suite (a collection) represent local and global contexts respectively; (2) UNITE further elaborates the trace representation from ‘occurrence’ (weak semantics) to ‘influence’ (strong semantics) by combing program dependencies. The large-scale experiments on 12 FL techniques and 20 programs show that UNITE significantly improves FL effectiveness.

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Index Terms

Influential Global and Local Contexts Guided Trace Representation for Fault Localization
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 32, Issue 3

May 2023

937 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/3594533

Editor:
Mauro Pezzè
USI Università della Svizzera italiana and SIT Schaffhausen Institute of Technology, Switzerland

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Publication History

Published: 26 April 2023

Online AM: 15 December 2022

Accepted: 26 November 2022

Revised: 10 October 2022

Received: 18 February 2022

Published in TOSEM Volume 32, Issue 3

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Wu JZhang ZYang DXu JHe JMao X(2024)Knowledge-Augmented Mutation-Based Bug Localization for Hardware Design CodeACM Transactions on Architecture and Code Optimization10.1145/3660526Online publication date: 22-Apr-2024
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Arcuri AZhang MGaleotti J(2024)Advanced White-Box Heuristics for Search-Based Fuzzing of REST APIsACM Transactions on Software Engineering and Methodology10.1145/365215733:6(1-36)Online publication date: 27-Jun-2024
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Li GTang YYi BHe YLi JRen FLin ZLib L(2024)Statement Types and Error Rates: How are they Related for Boosting Fault Localization?2024 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C)10.1109/SANER-C62648.2024.00031(1-8)Online publication date: 12-Mar-2024
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Yu XRao JLiu LLin GHu WKeung JZhou JXiang J(2024)Improving effort-aware defect prediction by directly learning to rank software modulesInformation and Software Technology10.1016/j.infsof.2023.107250165:COnline publication date: 1-Jan-2024
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