Conference Paper


Evolutionary fault localization based on the diversity of suspiciousness values

Abstract

Context. Fault localization (FL) is a software lifecycle activity and its automation is a challenge for researchers and practitioners. Method. The study focuses on evolutionary fault localization and introduces a novel Genetic Programming (GP) approach that evolves FL heuristics based on the diversity of the suspiciousness score of program statements – a score to grade how faulty a statement is. Experimental analysis. The approach was evaluated against baselines, which include the canonical GP, in benchmarks with real programs and real faults. Conclusion. The results showed the competitiveness of the approach through evaluation metrics commonly used in the research field.



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Authors

Ferreira, Willian de Jesus
Leitao-Junior, Plinio S.
Silva-Junior, Deuslirio
Harrison, Rachel

Oxford Brookes departments

School of Engineering, Computing and Mathematics

Dates

Year of publication: [in press]
Date of RADAR deposit: 2025-03-11



Details

  • Owner: Joseph Ripp
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