Assessing Practitioner Beliefs about Software Defect Prediction

被引:17
作者
Shrikanth, N. C. [1 ]
Menzies, Tim [1 ]
机构
[1] North Carolina State Univ, Raleigh, NC 27695 USA
来源
2020 IEEE/ACM 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE (ICSE-SEIP) | 2020年
基金
美国国家科学基金会;
关键词
defects; beliefs; practitioner; empirical software engineering;
D O I
10.1145/3377813.3381367
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Just because software developers say they believe in "X", that does not necessarily mean that "X" is true. As shown here, there exist numerous beliefs listed in the recent Software Engineering literature which are only supported by small portions of the available data. Hence we ask what is the source of this disconnect between beliefs and evidence?. To answer this question we look for evidence for ten beliefs within 300,000+ changes seen in dozens of open-source projects. Some of those beliefs had strong support across all the projects; specifically, "A commit that involves more added and removed lines is more bug-prone" and "Files with fewer lines contributed by their owners (who contribute most changes) are bug-prone". Most of the widely-held beliefs studied are only sporadically supported in the data; i.e. large effects can appear in project data and then disappear in subsequent releases. Such sporadic support explains why developers believe things that were relevant to their prior work, but not necessarily their current work. Our conclusion will be that we need to change the nature of the debate with Software Engineering. Specifically, while it is important to report the effects that hold right now, it is also important to report on what effects change over time.
引用
收藏
页码:182 / 190
页数:9
相关论文
共 37 条
[1]   We Don't Need Another Hero? The Impact of "Heroes" on Software Development [J].
Agrawal, Amritanshu ;
Rahman, Akond ;
Krishna, Rahul ;
Sobran, Alexander ;
Menzies, Tim .
2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING - SOFTWARE ENGINEERING IN PRACTICE TRACK (ICSE-SEIP 2018), 2018, :245-253
[2]  
[Anonymous], 2010, P 6 INT C PRED MOD S
[3]  
[Anonymous], 2008, P 2008 INT WORKING C
[4]  
Bird C., 2011, ACM SIGSOFT ESEC/FSE, P4, DOI [DOI 10.1145/2025113.2025119, 10.1145/2025113.2025119]
[5]  
D'Ambros Marco, 2010, Proceedings of the 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010), P31, DOI 10.1109/MSR.2010.5463279
[6]   Belief & Evidence in Empirical Software Engineering [J].
Devanbu, Prem ;
Zimmermann, Thomas ;
Bird, Christian .
2016 IEEE/ACM 38TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE), 2016, :108-119
[7]   The Impact of Mislabeled Changes by SZZ on Just-in-Time Defect Prediction [J].
Fan, Yuanrui ;
Xia, Xin ;
da Costa, Daniel Alencar ;
Lo, David ;
Hassan, Ahmed E. ;
Li, Shanping .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2021, 47 (08) :1559-1586
[8]   Predicting fault incidence using software change history [J].
Graves, TL ;
Karr, AF ;
Marron, JS ;
Siy, H .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2000, 26 (07) :653-661
[9]  
Hassan AE, 2005, PROC IEEE INT CONF S, P263
[10]   Predicting Faults Using the Complexity of Code Changes [J].
Hassan, Ahmed E. .
2009 31ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, PROCEEDINGS, 2009, :78-88