Equivalent Mutants in the Wild: Identifying and Efficiently Suppressing Equivalent Mutants for Java Programs
This program is tentative and subject to change.
The presence of equivalent mutants has long been considered a major obstacle to the widespread adoption of mutation analysis and mutation testing in practice. This paper presents a study on the types and prevalence of equivalent mutants in real-world Java programs. To our knowledge, no such systematic study exists. We conducted a ground-truth analysis of 1,931 mutants, sampled from 7 open source Java projects. Our analysis identified 214 equivalent mutants, which we grouped based on two criteria that describe why the mutants are equivalent and how challenging their detection is. From this analysis, we observed that (1) the median equivalent mu- tant rate across the 7 projects is 2.97%; (2) many equivalent mutants are caused by common programming patterns and their detection is not much more complex than structural pattern matching over an abstract syntax tree. Based on the findings of our ground-truth analysis, we developed Equivalent Mutant Suppression (EMS), a technique that comprises 10 efficient and targeted analyses. We evaluated EMS on 19 open- source Java projects, comparing the effectiveness and efficiency of EMS to two variants of Trivial Compiler Equivalence (TCE), the current state of the art in equivalent mutant detection. Additionally, we analyzed all 9,047 equivalent mutants reported by any tool to better understand the types and frequencies of equivalent mutants found. Overall, EMS detects 8,776 equivalent mutants within 325 seconds; TCE detects 2,124 equivalent mutants in 2,938 hours.
This program is tentative and subject to change.
Wed 18 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:30 - 11:50 | |||
10:30 20mTalk | Large Language Models for Equivalent Mutant Detection: How Far are We? Technical Papers Zhao Tian Tianjin University, Honglin Shu Kyushu University, Dong Wang Tianjin University, China, Xuejie Cao College of Intelligence and Computing, Tianjin University, Yasutaka Kamei Kyushu University, Junjie Chen Tianjin University DOI Pre-print | ||
10:50 20mTalk | An Empirical Examination of Fuzzer Mutator Performance Technical Papers James Kukucka George Mason University, Luís Pina University of Illinois at Chicago, Paul Ammann George Mason University, USA, Jonathan Bell Northeastern University | ||
11:10 20mTalk | Equivalent Mutants in the Wild: Identifying and Efficiently Suppressing Equivalent Mutants for Java Programs Technical Papers Benjamin Kushigian University of Washington, Samuel Kaufman University of Washington, Ryan Featherman University of Washington, Hannah Potter University of Washington, Ardi Madadi University of Washington, René Just University of Washington | ||
11:30 20mTalk | LPR: Large Language Models-Aided Program Reduction Technical Papers Mengxiao Zhang University of Waterloo, Yongqiang Tian The Hong Kong University of Science and Technology, Zhenyang Xu University of Waterloo, Yiwen Dong University of Waterloo, Shin Hwei Tan Concordia University, Chengnian Sun University of Waterloo DOI | ||