TBFL和SAFL方法熵分析

计算机科学 ›› 2013, Vol. 40 ›› Issue (11): 152-157.

TBFL和SAFL方法熵分析

王蓁蓁,徐宝文,周毓明,陈林

金陵科技学院信息技术学院南京211169;南京大学软件新技术国家重点实验室南京210093;南京大学软件新技术国家重点实验室南京210093;南京大学软件新技术国家重点实验室南京210093

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金重大研究计划重点项目(90818027),国家自然科学基金面上项目(60773104,7),金陵科技学院科研基金(jit-b-201207)资助

Entropy Analysis of Testing-based Fault Localization and Similarity-aware Fault Localization

WANG Zhen-zhen,XU Bao-wen,ZHOU Yu-ming and CHEN Lin

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 为TBFL(testing-based fault localization)方法和SAFL(similarity-aware fault localization)方法构造了熵模型,并用该模型对Dicing方法、TARANTULA方法、SAFL方法在一个实例上进行分析比较。结果表明,熵模型可以为构造以及分析TBFL方法和SAFL方法提供一个原则性框架。

关键词: 熵,错误定位,相似性错误定位

Abstract: We presented an entropy model for the TBFL(testing-based fault localization) approaches and SAFL(similar-ity-aware fault localization) approach．We used the model to compare and analyze the Dicing approach,TARANTULA approach and SAFL approach on one instance．The analysis demonstrates that the entropy model can not only provide a new type of TBFL,but also provide a principle framework for constructing and analyzing various TBFL approaches and SAFL approach.

Key words: Entropy,Testing-based fault localization,Similarity-aware fault localization

王蓁蓁,徐宝文,周毓明,陈林. TBFL和SAFL方法熵分析[J]. 计算机科学, 2013, 40(11): 152-157. https://doi.org/

WANG Zhen-zhen,XU Bao-wen,ZHOU Yu-ming and CHEN Lin. Entropy Analysis of Testing-based Fault Localization and Similarity-aware Fault Localization[J]. Computer Science, 2013, 40(11): 152-157. https://doi.org/

参考文献

[1] Agrawal H,Horgan J,London S,et al.Fault location using execution slices and dataflow tests [C]∥IEEE Software Reliability Engineering．1995:143-151
[2] Cleve H,Zeller A．Locating causes of program failures [C]∥Proceedings of the 27^th International Conference on Software Engineering．2005:342-351
[3] Hao D,Zhang L,Pan Y,et al.On similarity-awareness in tes-ting-based fault localization [J]．Automated Software Enginee-ring,2008,15(2):207-249
[4] Haykin S．Neural networks-A comprehensive foundation [M]．Beijing:Tsinghua University Press,2001:484-508
[5] Kyriazis A,Mathioudakis K．Enhance of fault localization using probabilistic fusion with gas path analysis algorithms [J]．Journal of Engineering for Gas Turbines and Power,2009,131(5):51601-51609
[6] Jones J A,Harrold M J,Stasko J．Visualization of test information to assist fault localization [C]∥Proceeding of the 24^th International Conference on Software Engineering．2002:467-477
[7] Jones J A,Harrold M J．Empirical evaluation of the tarantula automatic fault-localization technique [C]∥Proceedings of the 20^th IEEE/ACM International Conference on Automated Software Engineering．2005:273-282
[8] Liblit B,Naik M,Zheng A X,et al.Scalable statistical bug isolation [C]∥Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation(PLDI)．2005:15-16
[9] Schach S R．Object-oriented classical software engineering [M]．Beijing:China Machine Press,2007:490-193
[10] Liu C,Yan X,Fei L,et al.SOBER:statistical model-based bug localization [C]∥Proceedings of the 13the ACM SIGSOFT Symposium on Foundations of Software Engineering．2005:286-295
[11] Renieris M,Reiss S P.Fault localization with nearest neighborqueries [C]∥Proceedings of the 18^th International Conference on Automated Software Engineering．2003:30-39
[12] Zeller A.Isolating cause-effect chains from computer programs [C]∥Proceedings of the 10^th ACM SIGFOFT Symposium on Foundations of Software Engineering．2002:1-10

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