- author = "Westley Weimer",
- title = "Advances in Automated Program Repair and a Call to Arms",
- booktitle = "Symposium on Search-Based Software Engineering",
- year = "2013",
- editor = "Guenther Ruhe and Yuanyuan Zhang",
- volume = "8084",
- series = "Lecture Notes in Computer Science",
- pages = "1--3",
- address = "Leningrad, Russia",
- month = aug # " 24-26",
- publisher = "Springer",
- note = "Invited keynote",
- keywords = "genetic algorithms, genetic programming, genetic improvement, APR, SBSE, GenProg",
- isbn13 = "978-3-642-39741-7",
-
URL = "
http://www.cs.ucl.ac.uk/staff/s.yoo/papers/Xie2013kx.pdf",
-
DOI = "
doi:10.1007/978-3-642-39742-4_1",
- size = "3 pages",
-
abstract = "In this keynote address I survey recent success and
momentum in the subfield of automated program repair. I
also encourage the search-based software engineering
community to rise to various challenges and
opportunities associated with test oracle generation,
large-scale human studies, and reproducible research
through benchmarks.
I discuss recent advances in automated program repair, focusing on the search-based GenProg technique but also presenting a broad overview of the subfield. I argue that while many automated repair techniques are correct by construction or otherwise produce only a single repair (e.g., AFix [13], Axis [17], Coker and Hafiz [4], Demsky and Rinard [7], Gopinath et al. [12], Jolt [2], Juzi [8], etc.), the majority can be categorised as generate and validate approaches that enumerate and test elements of a space of candidate repairs and are thus directly amenable to search-based software engineering and mutation testing insights (e.g., ARC [1], AutoFix-E [23], ARMOR [3], CASC [24], ClearView [21], Debroy and Wong [6], FINCH [20], PACHIKA [5], PAR [14], SemFix [18], Sidiroglou and Keromytis [22], etc.). I discuss challenges and advances such as scalability, test suite quality, and repair quality while attempting to convey the excitement surrounding a subfield that has grown so quickly in the last few years that it merited its own session at the 2013 International Conference on Software Engineering [3,4,14,18]. Time permitting, I provide a frank discussion of mistakes made and lessons learnt with GenProg [15].
In the second part of the talk, I pose three challenges to the SBSE community. I argue for the importance of human studies in automated software engineering. I present and describe multiple how to examples of using crowd sourcing (e.g., Amazon's Mechanical Turk) and massive on-line education (MOOCs) to enable SBSE-related human studies [10,11]. I argue that we should leverage our great strength in testing to tackle the increasingly-critical problem of test oracle generation (e.g., [9]) - not just test data generation - and draw supportive analogies with the subfields of specification mining and invariant detection [16,19]. Finally, I challenge the SBSE community to facilitate reproducible research and scientific advancement through benchmark creation, and support the need for such efforts with statistics from previous accepted papers.",
