Software fault localisation: a systematic mapping study

被引:17
|
作者
Zakari, Abubakar [1 ,2 ]
Lee, Sai Peck [1 ]
Alam, Khubaib Amjad [1 ]
Ahmad, Rodina [1 ]
机构
[1] Univ Malaya, Dept Software Engn, Fac Comp Sci & Informat Technol, Kuala Lumpur 50603, Malaysia
[2] Kano Univ Sci & Technol, Dept Comp Sci, PMB 3244, Kano, Nigeria
关键词
program debugging; software fault tolerance; software engineering; software maintenance; software fault localisation; software complexity; SFL research domain; SFL techniques; fault localisation techniques; software engineers; BUG LOCALIZATION; NETWORK; SLICE;
D O I
10.1049/iet-sen.2018.5137
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Software fault localisation (SFL) is recognised to be one of the most tedious, costly, and critical activities in program debugging. Due to the increase in software complexity, there is a huge interest in advanced SFL techniques that aid software engineers in locating program bugs. This interest paves a way to the existence of a large amount of literature in the SFL research domain. This study aims to investigate the overall research productivity, demographics, and trends shaping the landscape of SFL research domain. The research also aims to classify existing fault localisation techniques and identify trends in the field of study. Accordingly, a systematic mapping study of 273 primary selected studies is conducted with the adoption of an evidence-based systematic methodology to ensure coverage of all relevant studies. The results of this systematic mapping study show that SFL research domain is gaining more attention since 2010, with an increasing number of publications per year. Three main research facets were identified, i.e. validation research, evaluation research, and solution research, with solution research type getting more attention. Hence, various contribution facets were identified as well. In totality, general demographics of SFL research domain were highlighted and discussed.
引用
收藏
页码:60 / 74
页数:15
相关论文
共 50 条
  • [41] A Systematic Mapping Study of the Advancement in Software Vulnerability Forecasting
    Gautier, Andrew
    Whitehead, Christofer
    Dzielski, Dale
    Devine, Thomas
    Hernandez, Joshua
    SOUTHEASTCON 2023, 2023, : 545 - 552
  • [42] Costing Secure Software Development - A Systematic Mapping Study
    Venson, Elaine
    Guo, Xiaomeng
    Yan, Zidi
    Boehm, Barry
    14TH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY AND SECURITY (ARES 2019), 2019,
  • [43] Green and Sustainable Software Engineering - a Systematic Mapping Study
    Mourao, Brunna C.
    Karita, Leila
    Machado, Ivan do Carmo
    PROCEEDINGS OF THE 17TH BRAZILIAN SYMPOSIUM ON SOFTWARE QUALITY (SBQS), 2015, : 121 - 130
  • [44] Understanding software architecture erosion: A systematic mapping study
    Li, Ruiyin
    Liang, Peng
    Soliman, Mohamed
    Avgeriou, Paris
    JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS, 2022, 34 (03)
  • [45] Software quality assessment model: a systematic mapping study
    Yan, Meng
    Xia, Xin
    Zhang, Xiaohong
    Xu, Ling
    Yang, Dan
    Li, Shanping
    SCIENCE CHINA-INFORMATION SCIENCES, 2019, 62 (09)
  • [46] Smart Tools in Software Engineering: A Systematic Mapping Study
    Savchenko, Dmitrii
    Kasurinen, Jussi
    Taipale, Ossi
    2019 42ND INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2019, : 1509 - 1513
  • [47] Coordination in Crowdsourced Software Development: A Systematic Mapping Study
    de Campos, Vitor Queiroz
    David, Jose Maria N.
    Braga, Regina
    PROCEEDINGS OF THE 2021 IEEE 24TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2021, : 305 - 310
  • [48] On preserving the behavior in software refactoring: A systematic mapping study
    AlOmar, Eman Abdullah
    Mkaouer, Mohamed Wiem
    Newman, Christian
    Ouni, Ali
    Information and Software Technology, 2021, 140
  • [49] Software quality assessment model: a systematic mapping study
    Meng Yan
    Xin Xia
    Xiaohong Zhang
    Ling Xu
    Dan Yang
    Shanping Li
    Science China Information Sciences, 2019, 62
  • [50] Predicting Software Product Quality: A Systematic Mapping Study
    Ouhbi, Sofia
    Idri, Ali
    Luis Fernandez-Aleman, Jose
    Toval, Ambrosio
    COMPUTACION Y SISTEMAS, 2015, 19 (03): : 547 - 562