Automatic Software Repair: A Survey

Despite their growing complexity and increasing size, modern software applications must satisfy strict release requirements that impose short bug fixing and maintenance cycles, putting significant pressure on developers who are responsible for timely producing high-quality software. To reduce develo...

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Bibliographic Details
Published in:IEEE transactions on software engineering 2019-01, Vol.45 (1), p.34-67
Main Authors: Gazzola, Luca, Micucci, Daniela, Mariani, Leonardo
Format: Article
Language:English
Subjects:
Algorithms
Applications programs
Automatic program repair
Computer bugs
Conferences
correct by construction
Debugging
Fault diagnosis
generate and validate
Maintenance
Maintenance engineering
program synthesis
Repair
Repair & maintenance
search-based
self-repairing
semantics-driven repair
Software
Software algorithms
Surveying
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Summary:Despite their growing complexity and increasing size, modern software applications must satisfy strict release requirements that impose short bug fixing and maintenance cycles, putting significant pressure on developers who are responsible for timely producing high-quality software. To reduce developers workload, repairing and healing techniques have been extensively investigated as solutions for efficiently repairing and maintaining software in the last few years. In particular, repairing solutions have been able to automatically produce useful fixes for several classes of bugs that might be present in software programs. A range of algorithms, techniques, and heuristics have been integrated, experimented, and studied, producing a heterogeneous and articulated research framework where automatic repair techniques are proliferating. This paper organizes the knowledge in the area by surveying a body of 108 papers about automatic software repair techniques, illustrating the algorithms and the approaches, comparing them on representative examples, and discussing the open challenges and the empirical evidence reported so far.
ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.2017.2755013