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Cited by 299

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Precise Condition Synthesis for Program Repair

Open access
Xiong, Yingfei, Wang, Jie, Yan, Runfa, Zhang, Jiachen, Han, Shi, Huang, Gang, Zhang, Lu·2017·2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)
DOI 10.1109/icse.2017.45
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Abstract

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 18 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 78.3%, which is significantly higher than previous approaches, which are usually less than 40%.

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Metadata

Authors
Xiong, Y., Wang, J., Yan, R., Zhang, J., Han, S., Huang, G., & Zhang, L.
Venue
2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE)
Publisher
IEEE
Published
2017-05
Pages
416-426
DOI
10.1109/icse.2017.45
OpenAlex
W2518136680
Cited by
299
References
47
FWCI
28.64
Type
conference paper
Language
en
Open access
green

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CoChat. (2026). Citation check: Precise Condition Synthesis for Program Repair. https://app.cochat.ai/papers/10.1109/icse.2017.45
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Xiong, Y., Wang, J., Yan, R., Zhang, J., Han, S., Huang, G., & Zhang, L. (2017). Precise Condition Synthesis for Program Repair. 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). https://doi.org/10.1109/icse.2017.45

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