Automated Tool for Extraction of Software Fault Data

  • Pradeep SinghEmail author
  • Shrish Verma
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 38)


Open-source software repositories contain lots of useful information related to software development, software design, and software’s common error patterns. To access the software quality an automated software fault data extraction and preparation, which can be used for further prediction is still a major issue. Prediction of software fault has recently attracted the attention of software engineers. These prediction models require training fault data of projects. The fault training data contains information of software metrics and related bug information, and these data have to be prepared for each project. But it is not so easy to collect and prepare the fault data for the prediction model. We developed an automatic tool which extracts and prepares fault data for the prediction models. By using these automatic tools, we have extracted the data from the open-source projects developed in various languages. Extraction of fault data of various projects which includes source code and related defects from open-source software repository is performed. Various versions of open-source project software were taken from source forge and used for this purpose.


Software metrics Defects Open-source software 



This study is partially supported by Chhattisgarh Council of Science and Technology (CGCOST) C.G. under Grant 8068/CCOST. The findings and opinions in this study belong solely to the authors and are not necessarily those of the sponsor.


  1. 1.
    Chidamber SR, Kemerer CF (1994) A metrics suite for object oriented design. IEEE Trans Softw Eng 20(6):476–493CrossRefGoogle Scholar
  2. 2.
    Watanabe S, Kaiya H, Kaijiri K (2008) Adapting a fault prediction model to allow inter languagereuse. In: Proceedings of 4th international workshop on Predictor models in software engineering—PROMISE’08, p 19Google Scholar
  3. 3.
    Mahajan R, Gupta SK, Bedi RK (2015) Design of software fault prediction model using BR technique. Procedia Comput Sci 46:849–858CrossRefGoogle Scholar
  4. 4.
    Singh P, Pal NR, Verma S, Vyas OP (2016) Fuzzy rule-based approach for software fault prediction. IEEE Trans Syst Man Cybern Syst 47(5):1–12Google Scholar
  5. 5.
    Bishnu PS, Bhattacherjee V (2012) Software fault prediction using quad tree-based K-means clustering algorithm. IEEE Trans Knowl Data Eng 24(6):1146–1150CrossRefGoogle Scholar
  6. 6.
    Kaur D, Kaur A, Gulati S, Aggarwal M. A clustering algorithm for software fault prediction 1 2Google Scholar
  7. 7.
    Pei H, Ai J (2014) Collecting software defect data automatically from web site of open-source software. In: ICRMS 2014—Proceedings of 2014 10th international conference on reliability, maintainability and safety, pp 333–337Google Scholar
  8. 8.
    Akjnwale O, Dascalu S, Karam M (2006) DuoTracker: tool support for software defect data collection and analysis. CMMGoogle Scholar
  9. 9.
    Malhotra R, Agrawal A (2014) CMS tool. ACM SIGSOFT Softw Eng Notes 39(1):1–5CrossRefGoogle Scholar
  10. 10.
    Hall T, Bowes D, Liebchen G, Wernick P (2010) Evaluating three approaches to extracting fault data from software change repositories. Lecture Notes in Computer Science (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol 6156 LNCS, pp 107–115CrossRefGoogle Scholar
  11. 11.
    Home · TortoiseSVN (Online) Available: Accessed 10 Nov 2017
  12. 12. (Online) Available: Accessed 10 Nov 2017
  13. 13.
    The community platform for bioinformatics—OMICtools (Online) Available: Accessed 10 Nov 2017
  14. 14.
    Spinellis D (2005) Tool writing: a forgotten art? IEEE Softw 22(4):9–11CrossRefGoogle Scholar
  15. 15.
    Freeorion (Online) Available: Accessed 10 Nov 2017

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNational Institute of TechnologyRaipurIndia
  2. 2.Electronics & Telecommunication EngineeringNational Institute of TechnologyRaipurIndia

Personalised recommendations