SFLVis: visual analysis of software fault localization
Since the birth of software, fault localization has been a time-consuming and laborious task. Programmers need to constantly find faults in software through program logging, assertions, breakpoints, and profiling. In order to improve the debugging efficiency, many fault localization methods based on...
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| Published in | Journal of visualization Vol. 27; no. 4; pp. 585 - 602 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.08.2024
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1343-8875 1875-8975 |
| DOI | 10.1007/s12650-024-00979-x |
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| Abstract | Since the birth of software, fault localization has been a time-consuming and laborious task. Programmers need to constantly find faults in software through program logging, assertions, breakpoints, and profiling. In order to improve the debugging efficiency, many fault localization methods based on test cases have been proposed, such as program spectrum-based methods, and slice-based methods. However, these methods are far from the logic of actual debugging and still require programmers to use traditional methods. However, programmers cannot access the execution process of the program, they need to constantly modify breakpoints and repeatedly check variable values, which makes fault localization very time-consuming. After interviewing five experts in the field of visualization and software testing, we designed SFLVis to provide users with a new method to improve the efficiency of fault localization. We designed an algorithm to obtain the process of program execution and combined it with existing fault localization methods. The goal is to show users the execution results of test cases, source code logic, and the level of suspicion of statements, and reproduce the execution process of test cases. We designed rich interactive features to help users explore SFLVis and correlate information from various views to improve the efficiency of fault localization. To verify the effectiveness of SFLVis, we conducted a case study using the program in the Siemens Suite dataset and conducted group experiments and related interviews with 20 volunteers. The results show that SFLVis can effectively improve programmers’ efficiency compared with existing fault localization methods.
Graphical abstract |
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| AbstractList | Since the birth of software, fault localization has been a time-consuming and laborious task. Programmers need to constantly find faults in software through program logging, assertions, breakpoints, and profiling. In order to improve the debugging efficiency, many fault localization methods based on test cases have been proposed, such as program spectrum-based methods, and slice-based methods. However, these methods are far from the logic of actual debugging and still require programmers to use traditional methods. However, programmers cannot access the execution process of the program, they need to constantly modify breakpoints and repeatedly check variable values, which makes fault localization very time-consuming. After interviewing five experts in the field of visualization and software testing, we designed SFLVis to provide users with a new method to improve the efficiency of fault localization. We designed an algorithm to obtain the process of program execution and combined it with existing fault localization methods. The goal is to show users the execution results of test cases, source code logic, and the level of suspicion of statements, and reproduce the execution process of test cases. We designed rich interactive features to help users explore SFLVis and correlate information from various views to improve the efficiency of fault localization. To verify the effectiveness of SFLVis, we conducted a case study using the program in the Siemens Suite dataset and conducted group experiments and related interviews with 20 volunteers. The results show that SFLVis can effectively improve programmers’ efficiency compared with existing fault localization methods.
Graphical abstract Since the birth of software, fault localization has been a time-consuming and laborious task. Programmers need to constantly find faults in software through program logging, assertions, breakpoints, and profiling. In order to improve the debugging efficiency, many fault localization methods based on test cases have been proposed, such as program spectrum-based methods, and slice-based methods. However, these methods are far from the logic of actual debugging and still require programmers to use traditional methods. However, programmers cannot access the execution process of the program, they need to constantly modify breakpoints and repeatedly check variable values, which makes fault localization very time-consuming. After interviewing five experts in the field of visualization and software testing, we designed SFLVis to provide users with a new method to improve the efficiency of fault localization. We designed an algorithm to obtain the process of program execution and combined it with existing fault localization methods. The goal is to show users the execution results of test cases, source code logic, and the level of suspicion of statements, and reproduce the execution process of test cases. We designed rich interactive features to help users explore SFLVis and correlate information from various views to improve the efficiency of fault localization. To verify the effectiveness of SFLVis, we conducted a case study using the program in the Siemens Suite dataset and conducted group experiments and related interviews with 20 volunteers. The results show that SFLVis can effectively improve programmers’ efficiency compared with existing fault localization methods. |
| Author | Qin, Hongxing Yue, Xiaoqi Liu, Chao Sun, Desheng Hu, Haibo |
| Author_xml | – sequence: 1 givenname: Desheng surname: Sun fullname: Sun, Desheng organization: School of Big Data and Software Engineering, Chongqing University – sequence: 2 givenname: Xiaoqi surname: Yue fullname: Yue, Xiaoqi organization: School of Big Data and Software Engineering, Chongqing University – sequence: 3 givenname: Chao surname: Liu fullname: Liu, Chao organization: School of Big Data and Software Engineering, Chongqing University – sequence: 4 givenname: Hongxing surname: Qin fullname: Qin, Hongxing organization: College of Computer Science, Chongqing University – sequence: 5 givenname: Haibo surname: Hu fullname: Hu, Haibo email: haibo.hu@cqu.edu.cn organization: School of Big Data and Software Engineering, Chongqing University |
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| Cites_doi | 10.1109/ICSTW.2013.47 10.1109/SERE.2012.12 10.1109/ICSME52107.2021.00039 10.1109/ACCESS.2022.3151395 10.1109/32.341844 10.1007/s10515-022-00326-0 10.1145/357172.357173 10.1007/978-3-540-88582-5_51 10.1109/ASE.2003.1240292 10.1145/2635868.2635906 10.1016/j.jss.2004.06.026 10.1145/1529282.1529374 10.1016/S0950-5849(98)00089-5 10.1145/581396.581397 10.1145/774833.774843 10.1109/TSE.2007.70722 10.1109/TSMC.1981.4308636 10.1145/1596495.1596502 10.1109/SCCC.2018.8705160 10.1142/S021819400900426X 10.1016/S0065-2458(03)62003-6 10.1145/2351676.2351752 10.1145/1101908.1101949 10.1109/PRDC47002.2019.00045 10.1007/s10664-005-3861-2 10.1145/1037187.1024412 10.1145/3524610.3527877 10.1145/143062.143098 10.1109/PRDC.2006.18 10.1007/978-3-540-78137-0_20 10.1145/1363686.1363855 10.1109/TVCG.2018.2865026 10.1145/2591062.2591099 10.1145/2000791.2000795 10.1109/ICSE.2009.5070561 10.1109/TSE.2016.2521368 10.1145/1050849.1050865 |
| ContentType | Journal Article |
| Copyright | The Visualization Society of Japan 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| References | Zhang X-Y, Zheng Z (2019) A visualization analytical framework for software fault localization metrics. In: 2019 IEEE 24th pacific rim international symposium on dependable computing (PRDC), IEEE, pp 148–14809 DoHElbaumSRothermelGSupporting controlled experimentation with testing techniques: an infrastructure and its potential impactEmpir Softw Eng20051040543510.1007/s10664-005-3861-2 PaiGJDuganJBEmpirical analysis of software fault content and fault proneness using Bayesian methodsIEEE Trans Softw Eng2007331067568610.1109/TSE.2007.70722 Hao D, Zhang L, Zhang L, Sun J, Mei H (2009) Vida: visual interactive debugging. In: 2009 IEEE 31st international conference on software engineering, IEEE, pp 583–586 RosenblumDSA practical approach to programming with assertionsIEEE Trans Softw Eng1995211193110.1109/32.341844 Edwards JC (2003) Method, system, and program for logging statements to monitor execution of a program. Google Patents. US Patent 6,539,501 Ribeiro HL (2016) On the use of control-and data-ow in fault localization. PhD thesis, Universidade de São Paulo Bhushan RC, Yadav D (2017) Number of test cases required in achieving statement, branch and path coverage using ‘gcov’: an analysis. In: 7th international workshop on computer science and engineering (WCSE 2017) Beijing, China, pp 176–180 Collofello JS, Cousins L (1987) Towards automatic software fault location through decision-to-decision path analysis. In: Managing requirements knowledge, international workshop On, IEEE Computer Society, pp 539–539 Janssen T, Abreu R, Van Gemund AJ (2009) Zoltar: a spectrum-based fault localization tool. In: Proceedings of the 2009 ESEC/FSE workshop on software integration and evolution@ Runtime, pp 23–30 Rosenblum DS (1992) Towards a method of programming with assertions. In: Proceedings of the 14th international conference on software engineering, pp 92–104 WeiserMDProgram slices: formal, psychological, and practical investigations of an automatic program abstraction method1979USAUniversity of Michigan KorelBRillingJDynamic program slicing methodsInf Softw Technol19984011–1264765910.1016/S0950-5849(98)00089-5 WongWEGaoRLiYAbreuRWotawaFA survey on software fault localizationIEEE Trans Softw Eng201642870774010.1109/TSE.2016.2521368 Mutti D (2014) Coverage based debugging visualization. PhD thesis, Universidade de São Paulo Zhang S, Zhang C (2014) Software bug localization with markov logic. In: Companion proceedings of the 36th international conference on software engineering, pp 424–427 BinkleyDWHarmanMA survey of empirical results on program slicingAdv Comput20046210517810517810.1016/S0065-2458(03)62003-6 Campos J, Riboira A, Perez A, Abreu R (2012) Gzoltar: an eclipse plug-in for testing and debugging. In: Proceedings of the 27th IEEE/ACM international conference on automated software engineering, pp 378–381 Stallman RM, et al. (1999) Using and porting the GNU compiler collection vol. 86. Free Software Foundation, ??? XuBQianJZhangXWuZChenLA brief survey of program slicingACM SIGSOFT Softw Eng Notes200530213610.1145/1050849.1050865 Jones JA, Harrold MJ (2005) Empirical evaluation of the tarantula automatic fault-localization technique. In: Proceedings of the 20th IEEE/ACM international conference on automated software engineering, pp 273–282 Tip F (1994) A survey of program slicing techniques. Centrum voor Wiskunde en Informatica Amsterdam, ??? Ghandehari LSG, Bourazjany MN, Lei Y, Kacker RN, Kuhn DR (2013) Applying combinatorial testing to the siemens suite. In: 2013 IEEE Sixth international conference on software testing, verification and validation workshops, IEEE, pp 362–371 Nessa S, Abedin M, Wong WE, Khan L, Qi Y (2009) Fault localization using n-gram analysis. In: Proceedings of the 3rd international conference on wireless algorithms, systems, and applications, pp 548–559 Planning S (2002) The economic impacts of inadequate infrastructure for software testing. National Institute of Standards and Technology, 1 Jones JA, Harrold MJ, Stasko J (2002) Visualization of test information to assist fault localization. In: Proceedings of the 24th international conference on software engineering. ICSE, IEEE, pp 467–477 XieCXuWMuellerKA visual analytics framework for the detection of anomalous call stack trees in high performance computing applicationsIEEE Trans Visual Comput Graph201825121522410.1109/TVCG.2018.2865026 Wong WE, Debroy V, Li Y, Gao R (2012) Software fault localization using dstar (d*). In: 2012 IEEE sixth international conference on software security and reliability, IEEE, pp 21–30 SugiyamaKTagawaSTodaMMethods for visual understanding of hierarchical system structuresIEEE Trans Syst Man Cybern198111210912561143610.1109/TSMC.1981.4308636 WongWESugetaTQiYMaldonadoJCSmart debugging software architectural design in SDLJ Syst Softw2005761152810.1016/j.jss.2004.06.026 Hauswirth M, Chilimbi TM (2004) Low-overhead memory leak detection using adaptive statistical profiling. In: Proceedings of the 11th international conference on architectural support for programming languages and operating systems, pp 156–164 Abreu R, González A, Zoeteweij P, Gemund AJ (2008) Automatic software fault localization using generic program invariants. In: Proceedings of the 2008 ACM symposium on applied computing, pp 712–717 Kanda T, Shimari K, Inoue K (2022)didiffff: a viewer for comparing changes in both code and execution traces. In: Proceedings of the 30th IEEE/ACM international conference on program comprehension, pp 528–532 Renieres M, Reiss SP (2003) Fault localization with nearest neighbor queries. In: 18th IEEE International conference on automated software engineering, Proceedings, IEEE, pp 30–39 Stallman R, Pesch R, Shebs S, et al.: Debugging with GDB. Free Software Foundation 675 (1988) Orso A, Jones JA, Harrold MJ, Stasko J Gammatella (2004) Visualization of program-execution data for deployed software. In: Proceedings. 26th international conference on software engineering, IEEE, pp 699–700 NadimMMondalDRoyCKLeveraging structural properties of source code graphs for just-in-time bug predictionAutom Softw Eng202229113010.1007/s10515-022-00326-0 Xuan J, Monperrus M (2014) Test case purification for improving fault localization. In: Proceedings of the 22nd ACM SIGSOFT international symposium on foundations of software engineering, pp 52–63 Abreu R, Mayer W, Stumptner M, Gemund AJ (2009) Refining spectrum-based fault localization rankings. In: Proceedings of the 2009 ACM symposium on applied computing, pp 409–414 Abreu R, Zoeteweij P, Van Gemund AJ (2006) An evaluation of similarity coefficients for software fault localization. In: 2006 12th Pacific rim international symposium on dependable computing (PRDC’06), IEEE, pp 39–46 QayumAKhanSURAkhunzadaAFinecodeanalyzer: multi-perspective source code analysis support for software developer through fine-granular level interactive code visualizationIEEE Access202210204962051310.1109/ACCESS.2022.3151395 Silva FP, Souza HA, Chaim ML (2018) An empirical assessment of visual debugging tools effectiveness and efficiency. In: 2018 37th international conference of the Chilean computer science society (SCCC), IEEE, pp 1–8 NaishLLeeHJRamamohanaraoKA model for spectra-based software diagnosisACM Trans Softw Eng Methodol (TOSEM)201120313210.1145/2000791.2000795 Cellier P, Ducassé M, Ferré S, Ridoux O (2008) Formal concept analysis enhances fault localization in software. In: Formal concept analysis: 6th international conference, ICFCA 2008, Montreal, Canada, February 25-28, 2008. Proceedings, Springer, 6, pp 273–288 ChoiS-SChaS-HTappertCCA survey of binary similarity and distance measuresJ Syst Cybern Inf2010814348 Zhang X-Y, Jiang M (2021) Spica: a methodology for reviewing and analysing fault localisation techniques. In: 2021 IEEE international conference on software maintenance and evolution (ICSME), IEEE, pp 366–377 HennessyJSymbolic debugging of optimized codeACM Trans Program Languag Syst (TOPLAS)19824332334410.1145/357172.357173 WongWEQiYBP neural network-based effective fault localizationInt J Softw Eng Knowl Eng2009190457359710.1142/S021819400900426X 979_CR16 979_CR17 979_CR39 979_CR18 WE Wong (979_CR42) 2016; 42 979_CR19 DS Rosenblum (979_CR32) 1995; 21 M Nadim (979_CR22) 2022; 29 979_CR30 C Xie (979_CR43) 2018; 25 979_CR31 979_CR11 979_CR33 979_CR12 J Hennessy (979_CR15) 1982; 4 979_CR34 979_CR13 979_CR35 979_CR14 979_CR37 979_CR2 979_CR1 B Korel (979_CR20) 1998; 40 GJ Pai (979_CR26) 2007; 33 S-S Choi (979_CR8) 2010; 8 979_CR27 979_CR29 WE Wong (979_CR40) 2009; 19 979_CR7 DW Binkley (979_CR5) 2004; 62 979_CR21 WE Wong (979_CR41) 2005; 76 979_CR9 979_CR4 979_CR45 979_CR3 979_CR24 K Sugiyama (979_CR36) 1981; 11 979_CR46 979_CR6 979_CR25 979_CR47 979_CR48 L Naish (979_CR23) 2011; 20 A Qayum (979_CR28) 2022; 10 H Do (979_CR10) 2005; 10 B Xu (979_CR44) 2005; 30 MD Weiser (979_CR38) 1979 |
| References_xml | – reference: Ribeiro HL (2016) On the use of control-and data-ow in fault localization. PhD thesis, Universidade de São Paulo – reference: Stallman RM, et al. (1999) Using and porting the GNU compiler collection vol. 86. Free Software Foundation, ??? – reference: Abreu R, González A, Zoeteweij P, Gemund AJ (2008) Automatic software fault localization using generic program invariants. In: Proceedings of the 2008 ACM symposium on applied computing, pp 712–717 – reference: Abreu R, Mayer W, Stumptner M, Gemund AJ (2009) Refining spectrum-based fault localization rankings. In: Proceedings of the 2009 ACM symposium on applied computing, pp 409–414 – reference: Jones JA, Harrold MJ (2005) Empirical evaluation of the tarantula automatic fault-localization technique. In: Proceedings of the 20th IEEE/ACM international conference on automated software engineering, pp 273–282 – reference: RosenblumDSA practical approach to programming with assertionsIEEE Trans Softw Eng1995211193110.1109/32.341844 – reference: Zhang X-Y, Jiang M (2021) Spica: a methodology for reviewing and analysing fault localisation techniques. In: 2021 IEEE international conference on software maintenance and evolution (ICSME), IEEE, pp 366–377 – reference: DoHElbaumSRothermelGSupporting controlled experimentation with testing techniques: an infrastructure and its potential impactEmpir Softw Eng20051040543510.1007/s10664-005-3861-2 – reference: Zhang X-Y, Zheng Z (2019) A visualization analytical framework for software fault localization metrics. In: 2019 IEEE 24th pacific rim international symposium on dependable computing (PRDC), IEEE, pp 148–14809 – reference: Cellier P, Ducassé M, Ferré S, Ridoux O (2008) Formal concept analysis enhances fault localization in software. In: Formal concept analysis: 6th international conference, ICFCA 2008, Montreal, Canada, February 25-28, 2008. Proceedings, Springer, 6, pp 273–288 – reference: Mutti D (2014) Coverage based debugging visualization. PhD thesis, Universidade de São Paulo – reference: PaiGJDuganJBEmpirical analysis of software fault content and fault proneness using Bayesian methodsIEEE Trans Softw Eng2007331067568610.1109/TSE.2007.70722 – reference: Campos J, Riboira A, Perez A, Abreu R (2012) Gzoltar: an eclipse plug-in for testing and debugging. In: Proceedings of the 27th IEEE/ACM international conference on automated software engineering, pp 378–381 – reference: Wong WE, Debroy V, Li Y, Gao R (2012) Software fault localization using dstar (d*). In: 2012 IEEE sixth international conference on software security and reliability, IEEE, pp 21–30 – reference: Abreu R, Zoeteweij P, Van Gemund AJ (2006) An evaluation of similarity coefficients for software fault localization. In: 2006 12th Pacific rim international symposium on dependable computing (PRDC’06), IEEE, pp 39–46 – reference: XieCXuWMuellerKA visual analytics framework for the detection of anomalous call stack trees in high performance computing applicationsIEEE Trans Visual Comput Graph201825121522410.1109/TVCG.2018.2865026 – reference: WongWESugetaTQiYMaldonadoJCSmart debugging software architectural design in SDLJ Syst Softw2005761152810.1016/j.jss.2004.06.026 – reference: Edwards JC (2003) Method, system, and program for logging statements to monitor execution of a program. Google Patents. US Patent 6,539,501 – reference: Jones JA, Harrold MJ, Stasko J (2002) Visualization of test information to assist fault localization. In: Proceedings of the 24th international conference on software engineering. ICSE, IEEE, pp 467–477 – reference: Rosenblum DS (1992) Towards a method of programming with assertions. In: Proceedings of the 14th international conference on software engineering, pp 92–104 – reference: Hauswirth M, Chilimbi TM (2004) Low-overhead memory leak detection using adaptive statistical profiling. In: Proceedings of the 11th international conference on architectural support for programming languages and operating systems, pp 156–164 – reference: Orso A, Jones JA, Harrold MJ, Stasko J Gammatella (2004) Visualization of program-execution data for deployed software. In: Proceedings. 26th international conference on software engineering, IEEE, pp 699–700 – reference: HennessyJSymbolic debugging of optimized codeACM Trans Program Languag Syst (TOPLAS)19824332334410.1145/357172.357173 – reference: NadimMMondalDRoyCKLeveraging structural properties of source code graphs for just-in-time bug predictionAutom Softw Eng202229113010.1007/s10515-022-00326-0 – reference: NaishLLeeHJRamamohanaraoKA model for spectra-based software diagnosisACM Trans Softw Eng Methodol (TOSEM)201120313210.1145/2000791.2000795 – reference: Bhushan RC, Yadav D (2017) Number of test cases required in achieving statement, branch and path coverage using ‘gcov’: an analysis. In: 7th international workshop on computer science and engineering (WCSE 2017) Beijing, China, pp 176–180 – reference: WongWEQiYBP neural network-based effective fault localizationInt J Softw Eng Knowl Eng2009190457359710.1142/S021819400900426X – reference: Stallman R, Pesch R, Shebs S, et al.: Debugging with GDB. Free Software Foundation 675 (1988) – reference: Ghandehari LSG, Bourazjany MN, Lei Y, Kacker RN, Kuhn DR (2013) Applying combinatorial testing to the siemens suite. In: 2013 IEEE Sixth international conference on software testing, verification and validation workshops, IEEE, pp 362–371 – reference: BinkleyDWHarmanMA survey of empirical results on program slicingAdv Comput20046210517810517810.1016/S0065-2458(03)62003-6 – reference: KorelBRillingJDynamic program slicing methodsInf Softw Technol19984011–1264765910.1016/S0950-5849(98)00089-5 – reference: QayumAKhanSURAkhunzadaAFinecodeanalyzer: multi-perspective source code analysis support for software developer through fine-granular level interactive code visualizationIEEE Access202210204962051310.1109/ACCESS.2022.3151395 – reference: ChoiS-SChaS-HTappertCCA survey of binary similarity and distance measuresJ Syst Cybern Inf2010814348 – reference: Tip F (1994) A survey of program slicing techniques. Centrum voor Wiskunde en Informatica Amsterdam, ??? – reference: WeiserMDProgram slices: formal, psychological, and practical investigations of an automatic program abstraction method1979USAUniversity of Michigan – reference: Xuan J, Monperrus M (2014) Test case purification for improving fault localization. In: Proceedings of the 22nd ACM SIGSOFT international symposium on foundations of software engineering, pp 52–63 – reference: Kanda T, Shimari K, Inoue K (2022)didiffff: a viewer for comparing changes in both code and execution traces. In: Proceedings of the 30th IEEE/ACM international conference on program comprehension, pp 528–532 – reference: Nessa S, Abedin M, Wong WE, Khan L, Qi Y (2009) Fault localization using n-gram analysis. In: Proceedings of the 3rd international conference on wireless algorithms, systems, and applications, pp 548–559 – reference: SugiyamaKTagawaSTodaMMethods for visual understanding of hierarchical system structuresIEEE Trans Syst Man Cybern198111210912561143610.1109/TSMC.1981.4308636 – reference: Janssen T, Abreu R, Van Gemund AJ (2009) Zoltar: a spectrum-based fault localization tool. In: Proceedings of the 2009 ESEC/FSE workshop on software integration and evolution@ Runtime, pp 23–30 – reference: Zhang S, Zhang C (2014) Software bug localization with markov logic. In: Companion proceedings of the 36th international conference on software engineering, pp 424–427 – reference: Renieres M, Reiss SP (2003) Fault localization with nearest neighbor queries. In: 18th IEEE International conference on automated software engineering, Proceedings, IEEE, pp 30–39 – reference: Silva FP, Souza HA, Chaim ML (2018) An empirical assessment of visual debugging tools effectiveness and efficiency. In: 2018 37th international conference of the Chilean computer science society (SCCC), IEEE, pp 1–8 – reference: WongWEGaoRLiYAbreuRWotawaFA survey on software fault localizationIEEE Trans Softw Eng201642870774010.1109/TSE.2016.2521368 – reference: Planning S (2002) The economic impacts of inadequate infrastructure for software testing. National Institute of Standards and Technology, 1 – reference: Hao D, Zhang L, Zhang L, Sun J, Mei H (2009) Vida: visual interactive debugging. In: 2009 IEEE 31st international conference on software engineering, IEEE, pp 583–586 – reference: XuBQianJZhangXWuZChenLA brief survey of program slicingACM SIGSOFT Softw Eng Notes200530213610.1145/1050849.1050865 – reference: Collofello JS, Cousins L (1987) Towards automatic software fault location through decision-to-decision path analysis. In: Managing requirements knowledge, international workshop On, IEEE Computer Society, pp 539–539 – ident: 979_CR12 doi: 10.1109/ICSTW.2013.47 – ident: 979_CR39 doi: 10.1109/SERE.2012.12 – ident: 979_CR46 doi: 10.1109/ICSME52107.2021.00039 – ident: 979_CR27 – volume: 10 start-page: 20496 year: 2022 ident: 979_CR28 publication-title: IEEE Access doi: 10.1109/ACCESS.2022.3151395 – volume-title: Program slices: formal, psychological, and practical investigations of an automatic program abstraction method year: 1979 ident: 979_CR38 – volume: 21 start-page: 19 issue: 1 year: 1995 ident: 979_CR32 publication-title: IEEE Trans Softw Eng doi: 10.1109/32.341844 – ident: 979_CR21 – volume: 29 start-page: 1 issue: 1 year: 2022 ident: 979_CR22 publication-title: Autom Softw Eng doi: 10.1007/s10515-022-00326-0 – volume: 4 start-page: 323 issue: 3 year: 1982 ident: 979_CR15 publication-title: ACM Trans Program Languag Syst (TOPLAS) doi: 10.1145/357172.357173 – ident: 979_CR24 doi: 10.1007/978-3-540-88582-5_51 – ident: 979_CR29 doi: 10.1109/ASE.2003.1240292 – ident: 979_CR45 doi: 10.1145/2635868.2635906 – volume: 76 start-page: 15 issue: 1 year: 2005 ident: 979_CR41 publication-title: J Syst Softw doi: 10.1016/j.jss.2004.06.026 – ident: 979_CR2 doi: 10.1145/1529282.1529374 – volume: 40 start-page: 647 issue: 11–12 year: 1998 ident: 979_CR20 publication-title: Inf Softw Technol doi: 10.1016/S0950-5849(98)00089-5 – ident: 979_CR18 doi: 10.1145/581396.581397 – ident: 979_CR9 – ident: 979_CR25 doi: 10.1145/774833.774843 – volume: 8 start-page: 43 issue: 1 year: 2010 ident: 979_CR8 publication-title: J Syst Cybern Inf – ident: 979_CR11 – volume: 33 start-page: 675 issue: 10 year: 2007 ident: 979_CR26 publication-title: IEEE Trans Softw Eng doi: 10.1109/TSE.2007.70722 – volume: 11 start-page: 109 issue: 2 year: 1981 ident: 979_CR36 publication-title: IEEE Trans Syst Man Cybern doi: 10.1109/TSMC.1981.4308636 – ident: 979_CR16 doi: 10.1145/1596495.1596502 – ident: 979_CR33 doi: 10.1109/SCCC.2018.8705160 – volume: 19 start-page: 573 issue: 04 year: 2009 ident: 979_CR40 publication-title: Int J Softw Eng Knowl Eng doi: 10.1142/S021819400900426X – volume: 62 start-page: 105 issue: 105178 year: 2004 ident: 979_CR5 publication-title: Adv Comput doi: 10.1016/S0065-2458(03)62003-6 – ident: 979_CR6 doi: 10.1145/2351676.2351752 – ident: 979_CR17 doi: 10.1145/1101908.1101949 – ident: 979_CR30 – ident: 979_CR47 doi: 10.1109/PRDC47002.2019.00045 – ident: 979_CR4 – volume: 10 start-page: 405 year: 2005 ident: 979_CR10 publication-title: Empir Softw Eng doi: 10.1007/s10664-005-3861-2 – ident: 979_CR14 doi: 10.1145/1037187.1024412 – ident: 979_CR19 doi: 10.1145/3524610.3527877 – ident: 979_CR31 doi: 10.1145/143062.143098 – ident: 979_CR34 – ident: 979_CR3 doi: 10.1109/PRDC.2006.18 – ident: 979_CR7 doi: 10.1007/978-3-540-78137-0_20 – ident: 979_CR37 – ident: 979_CR35 – ident: 979_CR1 doi: 10.1145/1363686.1363855 – volume: 25 start-page: 215 issue: 1 year: 2018 ident: 979_CR43 publication-title: IEEE Trans Visual Comput Graph doi: 10.1109/TVCG.2018.2865026 – ident: 979_CR48 doi: 10.1145/2591062.2591099 – volume: 20 start-page: 1 issue: 3 year: 2011 ident: 979_CR23 publication-title: ACM Trans Softw Eng Methodol (TOSEM) doi: 10.1145/2000791.2000795 – ident: 979_CR13 doi: 10.1109/ICSE.2009.5070561 – volume: 42 start-page: 707 issue: 8 year: 2016 ident: 979_CR42 publication-title: IEEE Trans Softw Eng doi: 10.1109/TSE.2016.2521368 – volume: 30 start-page: 1 issue: 2 year: 2005 ident: 979_CR44 publication-title: ACM SIGSOFT Softw Eng Notes doi: 10.1145/1050849.1050865 |
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| SubjectTerms | Algorithms Classical and Continuum Physics Computer Imaging Debugging Efficiency Engineering Engineering Fluid Dynamics Engineering Thermodynamics Fault location Heat and Mass Transfer Localization Pattern Recognition and Graphics Programmers Regular Paper Software testing Source code Vision |
| Title | SFLVis: visual analysis of software fault localization |
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