CRMF: A fault localization approach based on class reduction and method call frequency
Identifying the location of faults in real‐world programs is one of the costly processes during software debugging. To reduce the debugging effort, various fault localization techniques have been proposed in recent years. Spectrum‐based fault localization (SBFL) is one kind of widely investigated fa...
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| Published in: | Software, practice & experience Vol. 53; no. 4; pp. 1061 - 1090 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Bognor Regis
Wiley Subscription Services, Inc
01.04.2023
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| ISSN: | 0038-0644, 1097-024X |
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| Abstract | Identifying the location of faults in real‐world programs is one of the costly processes during software debugging. To reduce the debugging effort, various fault localization techniques have been proposed in recent years. Spectrum‐based fault localization (SBFL) is one kind of widely investigated fault localization technique. Most SBFL techniques first calculate the suspiciousness of program elements (such as statements, methods) to be faulty using the coverage information and execution results of tests. Then a rank list of program elements is generated according to their suspiciousness. However, some SBFL techniques only consider the binary coverage information (i.e., whether the program element is covered) but ignore some of the tests' running behaviors, such as the execution frequency when faults occur in the iteration entities or loop bodies, which are more likely to be faulty followed the propagation‐infection‐execution model. The execution frequency based techniques only replace the feature items of the existing formula limiting their effectiveness in fault localization. In this article, we propose a fault localization technique, class reduction and method call frequency (CRMF), which utilizes mutation analysis and information retrieval techniques. In particular, CRMF first uses mutation analysis to identify and reduce the classes, in which the program elements with a low probability of being faulty. Then we propose a new suspiciousness formula that applies information retrieval and considers method call frequency. To evaluate the effectiveness of CRMF, we conduct empirical studies on 264 real‐world programs from the Defects4J benchmark. Final results show that CRMF outperforms the statement frequency based technique FLSF and SBFL techniques (i.e., Ochiai, OP2, Tarantula, and Dstar) in both single‐fault programs and multiple‐fault programs. Specifically, CRMF can rank 29, 74, and 112 faults at the top 1, 3, 5 ranks and achieve a higher mean reciprocal rank for single‐fault programs and multiple‐fault programs. Finally, we discuss the essence of CRMF and analyze its effectiveness on multi‐fault programs in detail. |
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| AbstractList | Identifying the location of faults in real‐world programs is one of the costly processes during software debugging. To reduce the debugging effort, various fault localization techniques have been proposed in recent years. Spectrum‐based fault localization (SBFL) is one kind of widely investigated fault localization technique. Most SBFL techniques first calculate the suspiciousness of program elements (such as statements, methods) to be faulty using the coverage information and execution results of tests. Then a rank list of program elements is generated according to their suspiciousness. However, some SBFL techniques only consider the binary coverage information (i.e., whether the program element is covered) but ignore some of the tests' running behaviors, such as the execution frequency when faults occur in the iteration entities or loop bodies, which are more likely to be faulty followed the propagation‐infection‐execution model. The execution frequency based techniques only replace the feature items of the existing formula limiting their effectiveness in fault localization. In this article, we propose a fault localization technique, class reduction and method call frequency (CRMF), which utilizes mutation analysis and information retrieval techniques. In particular, CRMF first uses mutation analysis to identify and reduce the classes, in which the program elements with a low probability of being faulty. Then we propose a new suspiciousness formula that applies information retrieval and considers method call frequency. To evaluate the effectiveness of CRMF, we conduct empirical studies on 264 real‐world programs from the Defects4J benchmark. Final results show that CRMF outperforms the statement frequency based technique FLSF and SBFL techniques (i.e., Ochiai, OP2, Tarantula, and Dstar) in both single‐fault programs and multiple‐fault programs. Specifically, CRMF can rank 29, 74, and 112 faults at the top 1, 3, 5 ranks and achieve a higher mean reciprocal rank for single‐fault programs and multiple‐fault programs. Finally, we discuss the essence of CRMF and analyze its effectiveness on multi‐fault programs in detail. |
| Author | Li, Zheng Liu, Hengyuan Liu, Yong Wang, Haifeng Chen, Xiang |
| Author_xml | – sequence: 1 givenname: Hengyuan surname: Liu fullname: Liu, Hengyuan organization: Beijing University of Chemical Technology – sequence: 2 givenname: Zheng surname: Li fullname: Li, Zheng organization: Beijing University of Chemical Technology – sequence: 3 givenname: Haifeng orcidid: 0000-0003-2482-375X surname: Wang fullname: Wang, Haifeng email: h.f.wang@hotmail.com organization: Beijing University of Chemical Technology – sequence: 4 givenname: Yong orcidid: 0000-0003-1754-3039 surname: Liu fullname: Liu, Yong email: lyong@mail.buct.edu.cn organization: Beijing University of Chemical Technology – sequence: 5 givenname: Xiang orcidid: 0000-0002-1180-3891 surname: Chen fullname: Chen, Xiang organization: Nantong University |
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| Cites_doi | 10.1145/2610384.2628055 10.1109/TSE.2016.2521368 10.1016/S0306-4573(02)00021-3 10.1016/j.infsof.2010.04.002 10.1016/j.infsof.2020.106312 10.1016/j.jss.2020.110661 10.1109/ICSTW.2015.7107448 10.1145/2000791.2000795 10.1016/j.ins.2017.09.006 10.1002/smr.2312 10.1145/1868328.1868347 10.1145/2771783.2771797 10.1145/2950290.2983967 10.1145/1095430.1081753 10.1109/PRDC.2006.18 10.1109/TR.2013.2285319 10.1017/S1351324901002789 10.1109/ISSRE.2018.00026 10.1109/C-M.1978.218136 10.1145/1985441.1985451 10.1109/TR.2020.2982975 10.1109/QRS.2017.22 10.1109/TSE.2007.1016 10.1145/581396.581397 10.1109/ICSE.2017.62 10.5840/jphil2019116724 10.1145/2544173.2509551 10.1109/ASE.2011.6100062 10.1145/2786805.2786880 10.1109/TSE.1978.231514 10.1007/3-540-63531-9_29 10.1145/1287624.1287632 10.1002/9781118071953 10.1145/2559932 10.1109/ACCESS.2020.3004145 10.1109/ICST.2016.22 10.1145/2610384.2628053 10.1145/3078840 10.1109/ICST.2017.9 10.1109/AVSS.2011.6027363 10.1145/277633.277647 10.1109/ICST.2012.159 10.1109/TSE.2019.2911283 10.1109/COMPSAC.2013.139 10.1002/stvr.1509 10.1109/32.153381 10.1109/SCAM52516.2021.00021 10.1002/stvr.409 10.1145/3092703.3092717 10.1145/1416950.1416952 10.1109/ASE.2013.6693093 10.1016/j.ins.2016.04.023 10.1007/978-3-642-39742-4_17 10.1109/ICPC.2017.29 10.1145/2931037.2931051 10.1007/s11432-012-4746-9 10.1109/TSE.2019.2892102 10.1007/978-3-642-33119-0_18 10.1109/DSA52907.2021.00016 10.1109/ICSM.2009.5306315 10.1007/978-1-4757-5939-6_7 10.1145/2554850.2554978 10.1109/ASE.2009.25 10.1016/j.infsof.2018.03.008 10.1109/ICSE.2012.6227210 10.1002/1099-1689(200009)10:3<171::AID-STVR209>3.0.CO;2-J 10.1145/3345628 10.1145/2365952.2365981 10.1145/1361684.1361686 10.1109/ICST.2014.28 10.1016/j.cola.2021.101064 |
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| References | 2021; 66 2013; 63 1978; 4 2020; 168 2020; 124 2007; 33 2012; 55 2014; 23 2020; 8 1992; 8 2010; 20 2021; 33 2001 2000; 10 2008; 27 2011; 20 2019; 28 2005; 30 2016; 42 2008; 26 2019; 116 2003; 242 2018; 100 2013; 48 2012 2017; 26 1978; 11 2011 2010 2018; 422 2009 1997 2007 2006 2003; 39 2005 1992 2002 2016; 360 1998; 174 2015; 25 2001; 7 2021 2019; 47 2017 2020; 69 1999; 350 2016 2015 2014 2013 2010; 52 1998; 33 Conover WJ (e_1_2_15_62_1) 1999 e_1_2_15_21_1 e_1_2_15_42_1 e_1_2_15_67_1 e_1_2_15_40_1 e_1_2_15_69_1 e_1_2_15_3_1 e_1_2_15_29_1 e_1_2_15_80_1 e_1_2_15_27_1 e_1_2_15_48_1 e_1_2_15_61_1 e_1_2_15_25_1 e_1_2_15_46_1 e_1_2_15_23_1 e_1_2_15_44_1 e_1_2_15_65_1 e_1_2_15_9_1 e_1_2_15_7_1 e_1_2_15_5_1 e_1_2_15_10_1 e_1_2_15_31_1 e_1_2_15_56_1 e_1_2_15_77_1 e_1_2_15_58_1 e_1_2_15_79_1 Wilcoxon F (e_1_2_15_63_1) 1992 e_1_2_15_18_1 e_1_2_15_39_1 e_1_2_15_16_1 e_1_2_15_37_1 e_1_2_15_50_1 e_1_2_15_71_1 e_1_2_15_14_1 e_1_2_15_35_1 e_1_2_15_52_1 e_1_2_15_73_1 e_1_2_15_12_1 e_1_2_15_33_1 e_1_2_15_54_1 e_1_2_15_75_1 e_1_2_15_19_1 e_1_2_15_20_1 e_1_2_15_43_1 e_1_2_15_66_1 e_1_2_15_41_1 e_1_2_15_68_1 e_1_2_15_28_1 e_1_2_15_2_1 e_1_2_15_26_1 e_1_2_15_49_1 e_1_2_15_60_1 e_1_2_15_24_1 e_1_2_15_47_1 e_1_2_15_22_1 e_1_2_15_45_1 e_1_2_15_64_1 e_1_2_15_8_1 e_1_2_15_6_1 e_1_2_15_4_1 e_1_2_15_32_1 e_1_2_15_55_1 e_1_2_15_78_1 e_1_2_15_30_1 e_1_2_15_59_1 e_1_2_15_17_1 Burges CJ (e_1_2_15_57_1) 2007 e_1_2_15_70_1 e_1_2_15_15_1 e_1_2_15_38_1 e_1_2_15_72_1 e_1_2_15_13_1 e_1_2_15_36_1 e_1_2_15_51_1 e_1_2_15_74_1 e_1_2_15_11_1 e_1_2_15_34_1 e_1_2_15_53_1 e_1_2_15_76_1 |
| References_xml | – year: 2011 – volume: 23 start-page: 1 issue: 1 year: 2014 end-page: 28 article-title: Prevalence of coincidental correctness and mitigation of its impact on fault localization publication-title: ACM Trans Softw Eng Methodol (TOSEM) – volume: 26 start-page: 13 issue: 3 year: 2008 article-title: Interpreting TF‐IDF term weights as making relevance decisions publication-title: ACM Trans Inf Syst (TOIS) – year: 2005 – start-page: 153 year: 2014 end-page: 162 – start-page: 351 year: 2009 end-page: 360 – volume: 33 issue: 3 year: 2021 article-title: Improving deep‐learning‐based fault localization with resampling publication-title: J Softw Evol Process – volume: 28 start-page: 1 issue: 4 year: 2019 end-page: 34 article-title: Precise learn‐to‐rank fault localization using dynamic and static features of target programs publication-title: ACM Trans Softw Eng Methodol (TOSEM) – volume: 66 year: 2021 article-title: Combi‐FL: neural network and SBFL based fault localization using mutation analysis publication-title: J Comput Lang – start-page: 14 year: 2012 end-page: 24 – volume: 30 start-page: 286 issue: 5 year: 2005 end-page: 295 article-title: SOBER: statistical model‐based bug localization publication-title: SIGSOFT Softw Eng Notes – start-page: 224 year: 2013 end-page: 238 – start-page: 1 year: 2010 end-page: 10 – start-page: 579 year: 2015 end-page: 590 – volume: 350 year: 1999 – start-page: 43 year: 2011 end-page: 52 – volume: 8 start-page: 124297 year: 2020 end-page: 124310 article-title: IETCR: an information entropy based test case reduction strategy for mutation‐based fault localization publication-title: IEEE Access – start-page: 66 year: 2021 end-page: 77 – volume: 124 year: 2020 article-title: Multiple fault localization of software programs: a systematic literature review publication-title: Inf Softw Technol – start-page: 437 year: 2014 end-page: 440 – start-page: 432 year: 1997 end-page: 449 – start-page: 433 year: 2014 end-page: 436 – start-page: 408 year: 2011 end-page: 413 – volume: 42 start-page: 707 issue: 8 year: 2016 end-page: 740 article-title: A survey on software fault localization publication-title: IEEE Trans Softw Eng – volume: 26 start-page: 1 issue: 1 year: 2017 end-page: 30 article-title: Human competitiveness of genetic programming in spectrum‐based fault localisation: theoretical and empirical analysis publication-title: ACM Trans Softw Eng Methodol (TOSEM) – start-page: 345 year: 2013 end-page: 355 – start-page: 165 year: 2016 end-page: 176 – start-page: 241 year: 2017 end-page: 250 – start-page: 114 year: 2017 end-page: 125 – volume: 25 start-page: 605 issue: 5‐7 year: 2015 end-page: 628 article-title: Metallaxis‐FL: mutation‐based fault localization publication-title: Softw Test Verification Reliab – volume: 33 start-page: 420 issue: 6 year: 2007 end-page: 432 article-title: Feature location using probabilistic ranking of methods based on execution scenarios and information retrieval publication-title: IEEE Trans Softw Eng – volume: 116 start-page: 390 issue: 7 year: 2019 end-page: 411 article-title: Principles of indifference publication-title: J Philos – volume: 48 start-page: 765 issue: 10 year: 2013 end-page: 784 article-title: Injecting mechanical faults to localize developer faults for evolving software publication-title: ACM SIGPLAN Not – start-page: 609 year: 2017 end-page: 620 – start-page: 35 year: 2007 end-page: 44 – volume: 47 start-page: 1089 issue: 6 year: 2019 end-page: 1113 article-title: An empirical study of boosting spectrum‐based fault localization via pagerank publication-title: IEEE Trans Softw Eng – volume: 52 start-page: 972 issue: 9 year: 2010 end-page: 990 article-title: Bug localization using latent dirichlet allocation publication-title: Inf Softw Technol – start-page: 1 year: 2015 end-page: 10 – volume: 422 start-page: 572 year: 2018 end-page: 596 article-title: An optimal mutation execution strategy for cost reduction of mutation‐based fault localization publication-title: Inf Sci – volume: 100 start-page: 18 year: 2018 end-page: 31 article-title: Spectrum‐based fault localization in software product lines publication-title: Inf Softw Technol – start-page: 467 year: 2002 end-page: 477 – volume: 33 start-page: 83 issue: 7 year: 1998 end-page: 90 article-title: An Empirical Investigation of Program Spectra publication-title: SIGPLAN Not – volume: 11 start-page: 34 issue: 4 year: 1978 end-page: 41 article-title: Hints on test data selection: help for the practicing programmer publication-title: Computer – volume: 4 start-page: 293 year: 1978 end-page: 298 article-title: Theoretical and empirical studies of program testing publication-title: IEEE Trans Softw Eng – start-page: 39 year: 2006 end-page: 46 – volume: 7 start-page: 361 issue: 4 year: 2001 end-page: 378 article-title: The TREC question answering track publication-title: Nat Lang Eng – volume: 10 start-page: 171 issue: 3 year: 2000 end-page: 194 article-title: An empirical investigation of the relationship between spectra differences and regression faults publication-title: Softw Test Verif Reliab – volume: 242 start-page: 133 year: 2003 end-page: 142 – volume: 174 start-page: 21 year: 1998 – start-page: 244 year: 2012 end-page: 258 – volume: 55 start-page: 2826 issue: 12 year: 2012 end-page: 2840 article-title: Comparing logic coverage criteria on test case prioritization publication-title: Sci China Inf Sci – volume: 27 start-page: 2 issue: 1 year: 2008 article-title: Rank‐biased precision for measurement of retrieval effectiveness publication-title: ACM Trans Inf Syst (TOIS) – volume: 63 start-page: 290 issue: 1 year: 2013 end-page: 308 article-title: The DStar method for effective software fault localization publication-title: IEEE Trans Reliab – volume: 47 start-page: 332 issue: 2 year: 2019 end-page: 347 article-title: An empirical study of fault localization families and their combinations publication-title: IEEE Trans Softw Eng – start-page: 196 year: 1992 end-page: 202 – start-page: 1 year: 2015 end-page: 11 – volume: 168 year: 2020 article-title: HMER: a hybrid mutation execution reduction approach for mutation‐based fault localization publication-title: J Syst Softw – start-page: 103 year: 2021 end-page: 113 – volume: 8 start-page: 717 year: 1992 end-page: 727 article-title: PIE: a dynamic failure‐based technique publication-title: IEEE Trans Softw Eng – start-page: 299 year: 2016 end-page: 30 – start-page: 828 year: 2013 end-page: 829 – volume: 360 start-page: 43 year: 2016 end-page: 56 article-title: Fault localization based on statement frequency publication-title: Inf Sci – start-page: 88 year: 2009 end-page: 99 – start-page: 193 year: 2007 end-page: 200 – start-page: 34 year: 2001 end-page: 44 – volume: 20 start-page: 121 issue: 2 year: 2010 end-page: 147 article-title: Fault localization based on information flow coverage publication-title: Softw Test Verif Reliab – start-page: 1115 year: 2016 end-page: 1117 – start-page: 1293 year: 2014 end-page: 1300 – volume: 39 start-page: 45 issue: 1 year: 2003 end-page: 65 article-title: An information‐theoretic perspective of TF–IDF measures publication-title: Inf Process Manag – volume: 20 start-page: 11 issue: 3 year: 2011 article-title: A model for spectra‐based software diagnosis publication-title: ACM Trans Softw Eng Methodol (TOSEM) – volume: 69 start-page: 1021 issue: 3 year: 2020 end-page: 1049 article-title: Improving fault‐localization accuracy by referencing debugging history to alleviate structure bias in code suspiciousness publication-title: IEEE Trans Reliab – ident: e_1_2_15_29_1 doi: 10.1145/2610384.2628055 – ident: e_1_2_15_7_1 doi: 10.1109/TSE.2016.2521368 – ident: e_1_2_15_26_1 doi: 10.1016/S0306-4573(02)00021-3 – ident: e_1_2_15_66_1 doi: 10.1016/j.infsof.2010.04.002 – ident: e_1_2_15_78_1 doi: 10.1016/j.infsof.2020.106312 – ident: e_1_2_15_72_1 doi: 10.1016/j.jss.2020.110661 – ident: e_1_2_15_73_1 doi: 10.1109/ICSTW.2015.7107448 – ident: e_1_2_15_41_1 – ident: e_1_2_15_31_1 doi: 10.1145/2000791.2000795 – ident: e_1_2_15_56_1 doi: 10.1016/j.ins.2017.09.006 – ident: e_1_2_15_58_1 doi: 10.1002/smr.2312 – ident: e_1_2_15_76_1 doi: 10.1145/1868328.1868347 – ident: e_1_2_15_69_1 doi: 10.1145/2771783.2771797 – ident: e_1_2_15_13_1 doi: 10.1145/2950290.2983967 – ident: e_1_2_15_2_1 doi: 10.1145/1095430.1081753 – ident: e_1_2_15_30_1 doi: 10.1109/PRDC.2006.18 – ident: e_1_2_15_33_1 doi: 10.1109/TR.2013.2285319 – ident: e_1_2_15_59_1 doi: 10.1017/S1351324901002789 – ident: e_1_2_15_28_1 – ident: e_1_2_15_48_1 doi: 10.1109/ISSRE.2018.00026 – ident: e_1_2_15_37_1 doi: 10.1109/C-M.1978.218136 – ident: e_1_2_15_67_1 doi: 10.1145/1985441.1985451 – ident: e_1_2_15_50_1 doi: 10.1109/TR.2020.2982975 – ident: e_1_2_15_10_1 doi: 10.1109/QRS.2017.22 – ident: e_1_2_15_18_1 doi: 10.1109/TSE.2007.1016 – ident: e_1_2_15_32_1 doi: 10.1145/581396.581397 – ident: e_1_2_15_14_1 doi: 10.1109/ICSE.2017.62 – ident: e_1_2_15_46_1 doi: 10.5840/jphil2019116724 – ident: e_1_2_15_74_1 doi: 10.1145/2544173.2509551 – ident: e_1_2_15_55_1 – ident: e_1_2_15_20_1 doi: 10.1109/ASE.2011.6100062 – ident: e_1_2_15_17_1 doi: 10.1145/2786805.2786880 – ident: e_1_2_15_5_1 doi: 10.1109/TSE.1978.231514 – ident: e_1_2_15_34_1 doi: 10.1007/3-540-63531-9_29 – ident: e_1_2_15_19_1 doi: 10.1145/1287624.1287632 – ident: e_1_2_15_42_1 doi: 10.1002/9781118071953 – ident: e_1_2_15_45_1 doi: 10.1145/2559932 – volume-title: Practical Nonparametric Statistics year: 1999 ident: e_1_2_15_62_1 – ident: e_1_2_15_68_1 doi: 10.1109/ACCESS.2020.3004145 – ident: e_1_2_15_4_1 doi: 10.1109/ICST.2016.22 – ident: e_1_2_15_43_1 doi: 10.1145/2610384.2628053 – ident: e_1_2_15_71_1 doi: 10.1145/3078840 – ident: e_1_2_15_51_1 doi: 10.1109/ICST.2017.9 – ident: e_1_2_15_60_1 doi: 10.1109/AVSS.2011.6027363 – ident: e_1_2_15_35_1 doi: 10.1145/277633.277647 – ident: e_1_2_15_52_1 doi: 10.1109/ICST.2012.159 – ident: e_1_2_15_54_1 doi: 10.1145/2610384.2628053 – ident: e_1_2_15_49_1 doi: 10.1109/TSE.2019.2911283 – ident: e_1_2_15_12_1 doi: 10.1109/COMPSAC.2013.139 – ident: e_1_2_15_53_1 doi: 10.1002/stvr.1509 – ident: e_1_2_15_44_1 doi: 10.1109/32.153381 – ident: e_1_2_15_79_1 doi: 10.1109/SCAM52516.2021.00021 – ident: e_1_2_15_6_1 doi: 10.1002/stvr.409 – ident: e_1_2_15_47_1 doi: 10.1145/3092703.3092717 – ident: e_1_2_15_64_1 doi: 10.1145/1416950.1416952 – ident: e_1_2_15_23_1 doi: 10.1109/ASE.2013.6693093 – ident: e_1_2_15_15_1 doi: 10.1016/j.ins.2016.04.023 – ident: e_1_2_15_25_1 doi: 10.1007/978-3-642-39742-4_17 – start-page: 196 volume-title: Individual Comparisons by Ranking Methods year: 1992 ident: e_1_2_15_63_1 – ident: e_1_2_15_70_1 doi: 10.1109/ICPC.2017.29 – ident: e_1_2_15_16_1 doi: 10.1145/2931037.2931051 – ident: e_1_2_15_3_1 doi: 10.1007/s11432-012-4746-9 – ident: e_1_2_15_8_1 doi: 10.1109/TSE.2019.2892102 – ident: e_1_2_15_24_1 doi: 10.1007/978-3-642-33119-0_18 – ident: e_1_2_15_40_1 doi: 10.1109/DSA52907.2021.00016 – ident: e_1_2_15_65_1 doi: 10.1109/ICSM.2009.5306315 – ident: e_1_2_15_38_1 doi: 10.1007/978-1-4757-5939-6_7 – ident: e_1_2_15_36_1 doi: 10.1145/2554850.2554978 – ident: e_1_2_15_9_1 doi: 10.1109/ASE.2009.25 – ident: e_1_2_15_11_1 doi: 10.1016/j.infsof.2018.03.008 – ident: e_1_2_15_22_1 doi: 10.1109/ICSE.2012.6227210 – start-page: 193 volume-title: Advances in Neural Information Processing Systems year: 2007 ident: e_1_2_15_57_1 – ident: e_1_2_15_77_1 doi: 10.1002/1099-1689(200009)10:3<171::AID-STVR209>3.0.CO;2-J – ident: e_1_2_15_75_1 doi: 10.1145/3345628 – ident: e_1_2_15_21_1 – ident: e_1_2_15_61_1 doi: 10.1145/2365952.2365981 – ident: e_1_2_15_27_1 doi: 10.1145/1361684.1361686 – ident: e_1_2_15_39_1 doi: 10.1109/ICST.2014.28 – ident: e_1_2_15_80_1 doi: 10.1016/j.cola.2021.101064 |
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| SubjectTerms | class reduction Debugging Effectiveness Empirical analysis Fault detection fault localization Fault location Faults Information retrieval Iterative methods Localization method call frequency Mutation program debugging Reduction |
| Title | CRMF: A fault localization approach based on class reduction and method call frequency |
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