DBugHelper: A Debug assistant tool for distributed systems

doi:10.3969/j.issn.1000-5641.2016.05.017

Abstract

Abstract:

Development of large-scale distributed systems has experienced a long developing period. During the whole development cycle, debug is one of the most important steps. We meet the challenges of finding all the bugs and the corresponding solutions fixing bugs in a short time. Bug reports record bug histories and solutions, which provide a way to understand bug features and help to find solutions for new bugs. After we analyze the bug reports and fixed solutions, we find that there are strong correlation and similarity among many large-scale distributed systems. Thus the developing and fixing scheme of bugs may have similar characteristics. Then existed fixing solutions of bugs can be used to assist fixing new bugs. In this paper, we propose DBugHelper, a debug helping tool which
can be applied to boost the development of large-scale distributed systems and provide a more effective way to fix bugs. In DBugHelper, the existed bug reports are processed offline, and the latest bug report is represented as a query vector. We query the bug report history database and find the similar bugs with their solutions. In such way, we suppose to shorten the whole system development period.

Key words: large-scale distributed system, Debug, bug report, assistance

ZHANG Yan-fei, ZHANG Chun-xi, LI Yu-ming, ZHANG Rong. DBugHelper: A Debug assistant tool for distributed systems[J]. Journal of East China Normal University(Natural Sc, doi: 10.3969/j.issn.1000-5641.2016.05.017.

References

[ 1 ] KIM S, ZIMMERMANN T, WHITEHEADE E J, et al. Predicting faults from cached history [C]//Proceedings of the 29th International Conference on Software Engineering. 2007.
[ 2 ] ZHOU J, ZHANG H, LO D. Where should the bugs be fixed? — more accurate information retrieval-based bug localization based on bug reports [C]//Proceedings of the 2012 International Conference on Software Engineering. 2012: 14-24.
[ 3 ] NGUYEN A T, NGUYEN T T, AL-KOFAHI J, et al. A topic-based approach for narrowing the search space of buggy files from a bug report [C]//Proceedings of the IEEE/ACM International Conference on Automated Software Engineering. 2011: 263-272.
[ 4 ] ZHANG J, WANG X Y, HAO D, et al. A survey on bug-report analysis[J]. Science China, 2015, 58(2): 1-24.
[ 5 ] Hadoop Map/Reduce[EB/OL]. [2016-06-20]. https://issues.apache.org/jira/browse/MAPREDUCE.
[ 6 ] SUN X, LI B, LEUNG H, et al. MSR4SM: Using topic models to effectively mining software repositories for software maintenance tasks[J]. Information & Software Technology, 2015, 66: 1-12.
[ 7 ] HUANG L, NG V, PERSING I, et al. AutoODC: Automated generation of orthogonal defect classifications [J]. Automated Software Engineering, 2015, 22(1): 3-46.
[ 8 ] THUNG F, LO D, JIANG L. Automatic defect categorization [C]//Proceedings of the 2012 19th Working Conference on Reverse Engineering (WCRE). IEEE, 2012: 205-214.
[ 9 ] BLEI D M, NG A Y, JORDAN M I. Latent Dirichlet allocation [J]. Journal of Machine Learning Research, 2003: 993-1022.
[10] THOMAS S W. Mining software repositories using topic models [C]//Proceedings of the 33rd International Conference on Software Engineering. 2011: 1138-1139.
[11] MANNING C D, RAGHAVAN P, SCH¨ UTZE H. Introduction to Information Retrieval [M]. Cambridge: Cambridge University Press, 2008.
[12] KANUNGO T, MOUNT D M, NETANYAHU N S, et al. An efficient k-means clustering algorithm: Analysis and implementation [J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2002, 24(7): 881-892.
[13] SI X S, HU C H, ZHOU Z J. Fault prediction model based on evidential reasoning approach [J]. Science China Information Sciences, 2010, 53(10): 2032-2046.
[14] LUKINS S K, KRAFT N A, ETZKORN L H. Bug localization using latent Dirichlet allocation [J]. Information & Software Technology, 2010, 52(9): 972-990.
[15] RAO S, KAK A. Retrieval from software libraries for bug localization: A comparative study of generic and composite text models [C]//Proceedings of the International Working Conference on Mining Software Repositories. 2011: 43-52.
[16] PINGCLASAI N, HATA H, MATSUMOTO K. Classifying bug reports to bugs and other requests using topic modeling [C]//Proceedings of the Asia-Pacific Software Engineering Conference. IEEE Computer Society, 2013: 13-18.
[17] RUNESON P, ALEXANDERSSON M, NYHOLM O. Detection of duplicate defect reports using natural language processing [C]//Proceedings of the 29th International Conference on Software Engineering. 2007: 499-510.