Page 302 - 《软件学报》2026年第7期
P. 302
王海宁 等: 融合因果效应的高效软件产品线缺陷定位方法 2987
[19] Johnson B, Brun Y, Meliou A. Causal testing: Understanding defects’ root causes. In: Proc. of the 42nd ACM/IEEE Int’l Conf. on
Software Engineering. Seoul: ACM, 2020. 87–99. [doi: 10.1145/3377811.3380377]
[20] Wong WE, Gao RZ, Li YH, Abreu R, Wotawa F, Li DC. Software fault localization: An overview of research, techniques, and tools. In:
Wong WE, Tse TH, eds. Handbook of Software Fault Localization: Foundations and Advances. Hoboken: Wiley-IEEE Press, 2023.
[21] Jones JA, Harrold MJ. Empirical evaluation of the tarantula automatic fault-localization technique. In: Proc. of the 20th IEEE/ACM Int’l
Conf. on Automated Software Engineering. Long Beach: ACM, 2005. 273–282. [doi: 10.1145/1101908.1101949]
[22] Abreu R, Zoeteweij P, Golsteijn R, van Gemund AJC. A practical evaluation of spectrum-based fault localization. Journal of Systems and
Software, 2009, 82(11): 1780–1792. [doi: 10.1016/j.jss.2009.06.035]
[23] Papadakis M, Le Traon Y. Metallaxis-FL: Mutation-based fault localization. Software Testing, Verification and Reliability, 2015, 25(5-
7): 605–628. [doi: 10.1002/stvr.1509]
[24] Li ZJ, Yan LF, Liu YZ, Zhang ZY, Jiang B. MURE: Making use of mutations to refine spectrum-based fault localization. In: Proc. of the
2018 IEEE Int’l Conf. on Software Quality, Reliability and Security Companion (QRS-C). Lisbon: IEEE, 2018. 56–63. [doi: 10.1109/
QRS-C.2018.00024]
[25] Boehm B, Basili VR. Software defect reduction top 10 list. Computer, 2001, 34(1): 135–137. [doi: 10.1109/2.962984]
[26] Baah GK, Podgurski A, Harrold MJ. Mitigating the confounding effects of program dependences for effective fault localization. In: Proc.
of the 19th ACM SIGSOFT Symp. and the 13th European Conf. on Foundations of Software Engineering. Szeged: ACM, 2011. 146–156.
[doi: 10.1145/2025113.2025136]
[27] Zakari A, Lee SP, Abreu R, Ahmed BH, Rasheed RA. Multiple fault localization of software programs: A systematic literature review.
Information and Software Technology, 2020, 124: 106312. [doi: 10.1016/j.infsof.2020.106312]
[28] Weiser M. Program slicing. IEEE Trans. on Software Engineering, 1984, SE-10(4): 352–357. [doi: 10.1109/TSE.1984.5010248]
[29] Agrawal H, Horgan JR. Dynamic program slicing. ACM SIGPLAN Notices, 1990, 25(6): 246–256. [doi: 10.1145/93548.93576]
[30] Chaleshtari NB, Parsa S. SMBFL: Slice-based cost reduction of mutation-based fault localization. Empirical Software Engineering, 2020,
25(5): 4282–4314. [doi: 10.1007/s10664-020-09845-4]
[31] Sinnema M, Deelstra S, Nijhuis J, Bosch J. COVAMOF: A framework for modeling variability in software product families. In: Proc. of
the 3rd Int’l Conf. on Software Product Lines. Boston: Springer, 2004. 197–213. [doi: 10.1007/978-3-540-28630-1_12]
[32] Xiang Y, Huang H, Li SZ, Li MQ, Luo C, Yang XW. Automated test suite generation for software product lines based on quality-
diversity optimization. ACM Trans. on Software Engineering and Methodology, 2023, 33(2): 46. [doi: 10.1145/3628158]
[33] Nguyen S, Nguyen H, Tran N, Tran H, Nguyen T. Feature-interaction aware configuration prioritization for configurable code. In: Proc.
of the 34th IEEE/ACM Int’l Conf. on Automated Software Engineering (ASE). San Diego: IEEE, 2019. 489–501. [doi: 10.1109/ASE.
2019.00053]
[34] Kolesnikov S. Feature interactions in configurable software systems [Ph.D. Thesis]. Passau: Universität Passau, 2019.
[35] Dubslaff C, Weis K, Baier C, Apel S. Causality in configurable software systems. In: Proc. of the 44th IEEE/ACM Int’l Conf. on
Software Engineering. Pittsburgh: IEEE, 2022. 325–337. [doi: 10.1145/3510003.3510200]
[36] Yao LY, Chu ZX, Li S, Li YL, Gao J, Zhang AD. A survey on causal inference. ACM Trans. on Knowledge Discovery from Data
(TKDD), 2021, 15(5): 74. [doi: 10.1145/3444944]
[37] Imbens GW, Angrist JD. Identification and estimation of local average treatment effects. Econometrica, 1994, 62(2): 467–475. [doi: 10.
2307/2951620]
[38] De Chaisemartin C, D’Haultfœuille X. Two-way fixed effects estimators with heterogeneous treatment effects. American Economic
Review, 2020, 110(9): 2964–2996. [doi: 10.1257/aer.20181169]
[39] Pearl J. Causality: Models, Reasoning, and Inference. Cambridge: Cambridge University Press, 2000.
[40] Musco V, Monperrus M, Preux P. Mutation-based graph inference for fault localization. In: Proc. of the 16th IEEE Int’l Working Conf.
on Source Code Analysis and Manipulation (SCAM). Raleigh: IEEE, 2016. 97–106. [doi: 10.1109/SCAM.2016.24]
[41] Furia CA, Torkar R, Feldt R. Towards causal analysis of empirical software engineering data: The impact of programming languages on
coding competitions. ACM Trans. on Software Engineering and Methodology, 2023, 33(1): 13. [doi: 10.1145/3611667]
[42] Aho AV, Garey MR, Ullman JD. The transitive reduction of a directed graph. SIAM Journal on Computing, 1972, 1(2): 131–137. [doi: 10.
1137/0201008]
[43] Ngo KT, Nguyen TT, Nguyen S, Vo HD. Variability fault localization: A benchmark. In: Proc. of the 25th ACM Int’l Systems and
Software Product Line Conf. Vol. A. Leicester: ACM, 2021. 120–125. [doi: 10.1145/3461001.3473058]
[44] Abreu R, Zoeteweij P, van Gemund AJC. An evaluation of similarity coefficients for software fault localization. In: Proc. of the 12th
Pacific Rim Int’l Symp. on Dependable Computing (PRDC 2006). Riverside: IEEE, 2006. 39–46. [doi: 10.1109/PRDC.2006.18]

