Syntactic Versus Semantic Similarity of Artificial and Real Faults in Mutation Testing Studies-Reference-Cited by-同舟云学术

Syntactic Versus Semantic Similarity of Artificial and Real Faults in Mutation Testing Studies

Published:2023-07 Issue:7 Volume:49 Page:3922-3938
ISSN:0098-5589
Container-title:IEEE Transactions on Software Engineering
language:
Short-container-title:IIEEE Trans. Software Eng.

Author:

Ojdanic Milos¹^ORCID,Garg Aayush¹^ORCID,Khanfir Ahmed¹^ORCID,Degiovanni Renzo¹^ORCID,Papadakis Mike¹^ORCID,Le Traon Yves¹^ORCID

Affiliation:

1. University of Luxembourg, Luxembourg

Funder

Luxembourg National Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Software

Link

http://xplorestaging.ieee.org/ielx7/32/10185148/10136793.pdf?arnumber=10136793

Reference57 articles.

1. Selecting fault revealing mutants

2. Where should the bugs be fixed? More accurate information retrieval-based bug localization based on bug reports

3. The care and feeding of wild-caught mutants

4. A critique and improvement of the “CL” common language effect size statistics of McGraw and Wong;vargha;Journal of Educational and Behavioral Statistics,2000

5. An Empirical Study on Mutation, Statement and Branch Coverage Fault Revelation That Avoids the Unreliable Clean Program Assumption

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1. On the Coupling between Vulnerabilities and LLM-Generated Mutants: A Study on Vul4J Dataset;2024 IEEE Conference on Software Testing, Verification and Validation (ICST);2024-05-27

2. Natural Language Processing-Based Software Testing: A Systematic Literature Review;IEEE Access;2024