More efficient automatic repair of large-scale programs using weak recompilation

Qi, Yuhua; Mao, Xiaoguang; Wen, Yufeng; Dai, Ziying; Gu, Bohong

doi:10.1007/s11432-012-4741-1

Cited by 10 publications

(3 citation statements)

References 24 publications

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“…What is more, unlike Par whose source code is not publicly available, both source code and experimental benchmarks of GenProg are publicly available, facilitating the experiment reproduction and comparison between RSRepair and GenProg. In addition, literature [11] and our previous work [32,33] also used GenProg as the sole tool to conduct relevant experiments.…”

Section: Experimental Designmentioning

confidence: 99%

The strength of random search on automated program repair

Mao

Lei

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

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268

240

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Automated program repair recently received considerable attentions, and many techniques on this research area have been proposed. Among them, two genetic-programmingbased techniques, GenProg and Par, have shown the promising results. In particular, GenProg has been used as the baseline technique to check the repair effectiveness of new techniques in much literature. Although GenProg and Par have shown their strong ability of fixing real-life bugs in nontrivial programs, to what extent GenProg and Par can benefit from genetic programming, used by them to guide the patch search process, is still unknown.To address the question, we present a new automated repair technique using random search, which is commonly considered much simpler than genetic programming, and implement a prototype tool called RSRepair. Experiment on 7 programs with 24 versions shipping with real-life bugs suggests that RSRepair, in most cases (23/24), outperforms GenProg in terms of both repair effectiveness (requiring fewer patch trials) and efficiency (requiring fewer test case executions), justifying the stronger strength of random search over genetic programming. According to experimental results, we suggest that every proposed technique using optimization algorithm should check its effectiveness by comparing it with random search.

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Section: Experimental Designmentioning

confidence: 99%

The strength of random search on automated program repair

Mao

Lei

et al. 2014

Proceedings of the 36th International Conference on Software Engineering

Self Cite

268

240

View full text Add to dashboard Cite

show abstract

“…Motivation. Given the difficulty of fixing defects, recently a lot of research efforts have been devoted into automatic program repair techniques [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]. Most techniques generate a patch for a defect aiming at satisfying a specification.…”

Section: Introductionmentioning

confidence: 99%

Precise Condition Synthesis for Program Repair

Xiong

Wang

Yan

et al. 2017

2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)

263

305

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Due to the difficulty of repairing defect, many research efforts have been devoted into automatic defect repair. Given a buggy program that fails some test cases, a typical automatic repair technique tries to modify the program to make all tests pass. However, since the test suites in real world projects are usually insufficient, aiming at passing the test suites often leads to incorrect patches. This problem is known as weak test suites or overfitting.In this paper we aim to produce precise patches, that is, any patch we produce has a relatively high probability to be correct. More concretely, we focus on condition synthesis, which was shown to be able to repair more than half of the defects in existing approaches. Our key insight is threefold. First, it is important to know what variables in a local context should be used in an "if" condition, and we propose a sorting method based on the dependency relations between variables. Second, we observe that the API document can be used to guide the repair process, and propose document analysis technique to further filter the variables. Third, it is important to know what predicates should be performed on the set of variables, and we propose to mine a set of frequently used predicates in similar contexts from existing projects.Based on the insight, we develop a novel program repair system, ACS, that could generate precise conditions at faulty locations. Furthermore, given the generated conditions are very precise, we can perform a repair operation that is previously deemed to be too overfitting: directly returning the test oracle to repair the defect. Using our approach, we successfully repaired 17 defects on four projects of Defects4J, which is the largest number of fully automatically repaired defects reported on the dataset so far. More importantly, the precision of our approach in the evaluation is 73.9%, which is significantly higher than previous approaches, which are usually less than 40%.

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“…Recently, a lot of research effort has been put into automatic bug fixing [1,2,3,4,5,6]. Given a violated correctness condition, these approaches try to modify the code to satisfy the condition.…”

Section: Introductionmentioning

confidence: 99%

Safe Memory-Leak Fixing for C Programs

Gao

Xiong

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

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Abstract-Automatic bug fixing has become a promising direction for reducing manual effort in debugging. However, general approaches to automatic bug fixing may face some fundamental difficulties. In this paper, we argue that automatic fixing of specific types of bugs can be a useful complement.This paper reports our first attempt towards automatically fixing memory leaks in C programs. Our approach generates only safe fixes, which are guaranteed not to interrupt normal execution of the program. To design such an approach, we have to deal with several challenging problems such as inter-procedural leaks, global variables, loops, and leaks from multiple allocations. We propose solutions to all the problems and integrate the solutions into a coherent approach.We implemented our inter-procedural memory leak fixing into a tool named LeakF ix and evaluated LeakF ix on 15 programs with 522k lines of code. Our evaluation shows that LeakF ix is able to successfully fix a substantial number of memory leaks, and LeakF ix is scalable for large applications.

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More efficient automatic repair of large-scale programs using weak recompilation

Cited by 10 publications

References 24 publications

The strength of random search on automated program repair

The strength of random search on automated program repair

Precise Condition Synthesis for Program Repair

Safe Memory-Leak Fixing for C Programs

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