Page 171 - 《软件学报》2025年第12期
P. 171
5552 软件学报 2025 年第 36 卷第 12 期
随着科技的不断进步, 集成电路的复杂度不断增加, 使得测试电路成本不断提高, 当集成电路在测试集的激励
下得到与预期不同的输出响应时, 使用基于模型的诊断方法进行分析, 从而得到集成电路的候选故障信息, 可以大
幅度地减少测试的成本. 除此之外, 配电网的故障诊断也尤为重要, 国家电网面积大且错综复杂, 由于硬件老化、
气候、人为等因素, 出现故障频率较高, 若能够在短时间内找到故障点, 防止大面积停电等事故, 可减少大量的经
济损失.
References:
[1] Reiter R. A theory of diagnosis from first principles. Artificial Intelligence, 1987, 32(1): 57–95. [doi: 10.1016/0004-3702(87)90062-2]
[2] Mordoch A, Juba B, Stern R. Learning safe numeric action models. In: Proc. of the 37th AAAI Conf. on Artificial Intelligence.
Washington: AAAI, 2023. 12079–12086. [doi: 10.1609/aaai.v37i10.26424]
[3] Wang QJ, Jin T, Wang MQ. A hierarchical minimum hitting set calculation method for multiple multiphase faults in power distribution
networks. IEEE Trans. on Industrial Electronics, 2021, 68(1): 4–14. [doi: 10.1109/tie.2020.2967691]
[4] Torlak E, Chang FSH, Jackson D. Finding minimal unsatisfiable cores of declarative specifications. In: Proc. of the 15th Int’l Symp. on
Formal Methods. Turku: Springer, 2008. 326–341. [doi: 10.1007/978-3-540-68237-0_23]
[5] Wang QJ, Jin T, Mohamed MA. A fast and robust fault section location method for power distribution systems considering multisource
information. IEEE Systems Journal, 2022, 16(2): 1954–1964. [doi: 10.1109/JSYST.2021.3057663]
[6] Jose M, Majumdar R. Cause clue clauses: Error localization using maximum satisfiability. In: Proc. of the 32nd ACM SIGPLAN Conf. on
Programming Language Design and Implementation. San Jose: ACM, 2011. 437–446. [doi: 10.1145/1993498.1993550]
[7] Jannach D, Schmitz T. Model-based diagnosis of spreadsheet programs: A constraint-based debugging approach. Automated Software
Engineering, 2016, 23(1): 105–144. [doi: 10.1007/s10515-014-0141-7]
[8] Luo C, Xing WQ, Cai SW, Hu CM. NuSC: An effective local search algorithm for solving the set covering problem. IEEE Trans. on
Cybernetics, 2024, 54(3): 1403–1416. [doi: 10.1109/TCYB.2022.3199147]
[9] Cai SW, Li BH, Zhang XD. Local search for satisfiability modulo integer arithmetic theories. ACM Trans. on Computational Logic,
2023, 24(4): 32. [doi: 10.1145/3597495]
[10] Jiang LY, Ouyang DT, Dong BW, Zhang LM. Enhanced pruning scheme for enumerating MUS. Ruan Jian Xue Bao/Journal of Software,
2024, 35(4): 1964–1979 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/6845.htm [doi: 10.13328/j.cnki.jos.006845]
[11] Jiang LY, Ouyang DT, Zhang Q, Zhang LM. DeciLS-PBO: An effective local search method for pseudo-boolean optimization. Frontiers
of Computer Science, 2024, 18(2): 182326. [doi: 10.1007/s11704-023-3018-8]
[12] Ouyang DT, Gao H, Tian NY, Liu M, Zhang LM. MUS enumeration based on double-model. Journal of Computer Research and
Development, 2019, 56(12): 2623–2631 (in Chinese with English abstract). [doi: 10.7544/issn1000-1239.2019.20180852]
[13] Zhao XF, Ouyang DT. Deriving all minimal conflict sets using satisfiability algorithms. Acta Electronica Sinica, 2009, 37(4): 804–810 (in
Chinese with English abstract). [doi: 10.3321/j.issn:0372-2112.2009.04.024]
[14] Ignatiev A, Morgado A, Marques-Silva J. RC2: An efficient MaxSAT solver. Journal on Satisfiability, Boolean Modeling and
Computation, 2019, 11(1): 53–64. [doi: 10.3233/SAT190116]
[15] Liffiton MH, Malik A. Enumerating infeasibility: Finding multiple MUSes quickly. In: Proc. of the 10th Int’l Conf. on Integration of AI
and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Yorktown Heights: Springer, 2013. 160–175.
[doi: 10.1007/978-3-642-38171-3_11]
[16] Liffiton MH, Previti A, Malik A, Marques-Silva J. Fast, flexible MUS enumeration. Constraints, 2016, 21(2): 223–250. [doi: 10.1007/
s10601-015-9183-0]
[17] Jiang YF, Lin L. The computation of hitting sets with Boolean formulas. Chinese Journal of Computers, 2003, 26(8): 919–924 (in
Chinese with English abstract). [doi: 10.3321/j.issn:0254-4164.2003.08.004]
[18] Pill I, Quaritsch T. Optimizations for the boolean approach to computing minimal hitting sets. In: Proc. of the 20th European Conf. on
Artificial Intelligence. Montpellier: IOS, 2012. 648–653. [doi: 10.3233/978-1-61499-098-7-648]
[19] Zhao XF, Ouyang DT. Deriving all minimal hitting sets based on join relation. IEEE Trans. on Systems, Man, and Cybernetics: Systems,
2015, 45(7): 1063–1076. [doi: 10.1109/TSMC.2015.2400423]
[20] Jannach D, Schmitz T, Shchekotykhin K. Parallelized hitting set computation for model-based diagnosis. In: Proc. of the 29th AAAI
Conf. on Artificial Intelligence. Austin: AAAI, 2015. 1503–1510. [doi: 10.1609/aaai.v29i1.9389]
[21] Liu SG, Ouyang DT, Zhang LM. Method of minimality-checking of candidate solution for minimal hitting set algorithm. Ruan Jian Xue
Bao/Journal of Software, 2018, 29(12): 3733–3746 (in Chinese with English abstract). http://www.jos.org.cn/1000-9825/5311.htm [doi:
10.13328/j.cnki.jos.005311]
[22] Zhao XF, Huang S, Tong XR, Ouyang DT, Zhang LM, Zhang XL. IBWIICC: Incrementally computing minimal hitting-sets combing

