PSP-Finder: A Defect Detection Method Based on Mining Correlations from Function Call Paths

CUI Zhanqi; CHEN Xiang; MU Yongmin; PAN Minxue; WANG Rongcun

doi:10.1049/cje.2018.04.001

Volume 27 Issue 4

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Article Navigation > Chinese Journal of Electronics > 2018 > 27(4): 776-782

CUI Zhanqi, CHEN Xiang, MU Yongmin, et al., “PSP-Finder: A Defect Detection Method Based on Mining Correlations from Function Call Paths,” Chinese Journal of Electronics, vol. 27, no. 4, pp. 776-782, 2018, doi: 10.1049/cje.2018.04.001

Citation:

CUI Zhanqi, CHEN Xiang, MU Yongmin, et al., “PSP-Finder: A Defect Detection Method Based on Mining Correlations from Function Call Paths,” Chinese Journal of Electronics, vol. 27, no. 4, pp. 776-782, 2018, doi: 10.1049/cje.2018.04.001

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PSP-Finder: A Defect Detection Method Based on Mining Correlations from Function Call Paths

doi: 10.1049/cje.2018.04.001

1.
Computer School, Beijing Information Science and Technology University, Beijing 100101, China;
2.
Sate Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China;
3.
School of Computer Science and Technology, Nantong University, Nantong 226019, China;
4.
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China

Funds: This work is supported by the State Key Research Development Program of China (No.2016YFC0801407), the National Natural Science Foundation of China (No.61702041, No.61202006, No.61601039), and the Open Foundation of State Key Laboratory for Novel Software Technology (No.KFKT2016B12, No.KFKT2016B18).

Received Date: 2017-01-22
Rev Recd Date: 2017-03-27
Publish Date: 2018-07-10

Abstract

Abstract

Large scale programs usually imply many programming rules, which are missing from the specification documents. However, if programmers violate these rules in the process of programming, it is possible to introduce software defects. Previous works on mining function call correlation patterns only use structural information of the program, while control flow, data flow or other semantic information of the program are not exploited in those approaches. As a result, the defect detecting ability is restricted and high false rate is caused. This paper proposes a defect detection method based on mining function call association rules from program paths, which can be provided by simple static analysis. Then, the programs are automatically checked against the function call association rules for detecting suspicious defects. Based on this approach, experiments are carried out on a group of open source projects. The experiment results show that this approach can improve the capability of detecting defects and find more bugs related to program execution path. In addition, the false positive function call patterns and the overhead for manually validating suspicious defects are reduced.
- Function call graphs,
- Function call paths,
- Mining association rules,
- Defect detection

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References(19)

References

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