- author = "Hammad Ahmad and Padraic Cashin and Stephanie Forrest and Westley Weimer",
- title = "Digging into Semantics: Where Do Search-Based Software Repair Methods Search?",
- booktitle = "Parallel Problem Solving from Nature - PPSN XVII - 17th International Conference, PPSN 2022, Proceedings, Part II",
- year = "2022",
- editor = "Guenter Rudolph and Anna V. Kononova and Hernan E. Aguirre and Pascal Kerschke and Gabriela Ochoa and Tea Tusar",
- volume = "13399",
- series = "Lecture Notes in Computer Science",
- pages = "3--18",
- address = "Dortmund, Germany",
- month = sep # " 10-14",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, genetic improvement, APR, SBSE, Semantic search spaces, Program repair, Patch diversity, Daikon, Defects4J",
- timestamp = "Tue, 16 Aug 2022 16:15:42 +0200",
-
biburl = "
https://dblp.org/rec/conf/ppsn/AhmadCFW22.bib",
- bibsource = "dblp computer science bibliography, https://dblp.org",
- isbn13 = "978-3-031-14720-3",
-
URL = "
https://web.eecs.umich.edu/~weimerw/p/weimer-asplos2022.pdf",
-
DOI = "
doi:10.1007/978-3-031-14721-0_1",
- abstract = "Search-based methods are a popular approach for automatically repairing software bugs, a field known as automated program repair (APR). There is increasing interest in empirical evaluation and comparison of different APR methods, typically measured as the rate of successful repairs on benchmark sets of buggy programs. Such evaluations, however, fail to explain why some approaches succeed and others fail. Because these methods typically use syntactic representations, i.e., source code, we know little about how the different methods explore their semantic spaces, which is relevant for assessing repair quality and understanding search dynamics. We propose an automated method based on program semantics, which provides quantitative and qualitative information about different APR search-based techniques. Our approach requires no manual annotation and produces both mathematical and human-understandable insights. In an empirical evaluation of 4 APR tools and 34 defects, we investigate the relationship between search-space exploration, semantic diversity and repair success, examining both the overall picture and how the tools search unfolds. Our results suggest that population diversity alone is not sufficient for finding repairs, and that searching in the right place is more important than searching broadly, highlighting future directions for the research community.",
-
notes = "Semantic distance between code mutants estimated by
comparing their invariant sets using Canberra distance.
2D visualisation. CapGem, GenProg, SimFix, TBar.
Java.
p12 four to twenty times more syntactic variability than (useful?) semantic variation. (ie Java syntax-to-semantics is many-to-one mapping.)
PPSN2022",
