- author = "Zhen Yu Ding and Yiwei Lyu and Christopher Timperley and Claire {Le Goues}",
- title = "Leveraging Program Invariants to Promote Population Diversity in Search-Based Automatic Program Repair",
- booktitle = "GI-2019, ICSE workshops proceedings",
- year = "2019",
- editor = "Justyna Petke and Shin Hwei Tan and William B. Langdon and Westley Weimer",
- pages = "2--9",
- address = "Montreal",
- month = "28 " # may,
- publisher = "IEEE",
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE",
- isbn13 = "978-1-7281-2268-7",
-
URL = "
http://geneticimprovementofsoftware.com/paper_pdfs/ding2019leveraging.pdf",
-
DOI = "
doi:10.1109/GI.2019.00011",
- size = "8 pages",
- abstract = "Search-based automatic program repair has shown promise in reducing the cost of defects in real-world software.However, to date, such techniques have typically been most successful when constructing short or single-edit repairs. This is true even when techniques make use of heuristic search strategies, like genetic programming, that in principle support the construction of patches of arbitrary length. One key reason is that the fitness function traditionally depends entirely on test cases, which are poor at identifying partially correct solutions and lead to a fitness landscape with many plateaus. We propose a novel fitness function that optimizes for both functionality and semantic diversity, characterized using learned invariant solver intermediate behaviour. Our early results show that this new approach improves semantic diversity and fitness granularity, but does not statistically significantly improve repair performance.",
-
notes = "Cost of buggy software in 2017. $170000000 Plateau
fitness landscape. Daikon. IntroClassJava
University of Pittsburgh
Slides: http://geneticimprovementofsoftware.com/slides/ding2019leveraging_slides.pdf
GI-2019 http://geneticimprovementofsoftware.com
part of \cite{Petke:2019:ICSEworkshop}",
