CFP last date
20 May 2024
Reseach Article

Article:Software Specifications Mining using Transaction Mapping Algorithm

by R. Jeevarathinam, Dr. Antony Selvadoss Thanamani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 5
Year of Publication: 2010
Authors: R. Jeevarathinam, Dr. Antony Selvadoss Thanamani
10.5120/1674-2258

R. Jeevarathinam, Dr. Antony Selvadoss Thanamani . Article:Software Specifications Mining using Transaction Mapping Algorithm. International Journal of Computer Applications. 12, 5 ( December 2010), 26-31. DOI=10.5120/1674-2258

@article{ 10.5120/1674-2258,
author = { R. Jeevarathinam, Dr. Antony Selvadoss Thanamani },
title = { Article:Software Specifications Mining using Transaction Mapping Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 12 },
number = { 5 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 26-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume12/number5/1674-2258/ },
doi = { 10.5120/1674-2258 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:54.826072+05:30
%A R. Jeevarathinam
%A Dr. Antony Selvadoss Thanamani
%T Article:Software Specifications Mining using Transaction Mapping Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 12
%N 5
%P 26-31
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Specification mining is a dynamic analysis process aimed at automatically inferring suggested specifications of a program from its execution traces. In software development it would be preferable if all programs and software projects are developed with clear, precise and documented specifications. But due to hard deadlines and `short-time-to-market' requirement, software products often come with project oriented, incomplete and even without any documented specifications. This situation is further motivated by a phenomenon termed as software evolution. As software evolves the documented specification is often not updated. This might render the original documented specification of little use after several cycles of program evolution. The above factors have contributed to high software maintenance costs. In this paper a novel technique to efficiently mine software specifications, called TM_TraceMiner is proposed which mines software specifications from program execution traces. To address the limitations of Apriori-like methods and FP-growth methods, a mining paradigm has been proposed, which uses Transaction Mapping algorithm.

References
  1. G. Ammons, R. Bodik, and J. R. Larus. Mining specifications. In Proceedings of the 29th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pages 4–16, 2002
  2. J. Yang, D. Evans, D. Bhardwaj, T. Bhat, and M.Das. Perracotta: Mining temporal API rules from imperfect traces. In Proc. of Int. Conf. on Software Engineering, 2006.
  3. The Java hotspot performance engine architecture. http://java.sun.com/products/hotspot/whitepaper.html
  4. J. Han and M. Kamber. Data Mining Concepts and Techniques. Morgan Kaufmann, 2001.
  5. R.Agrawal, T. Imielinski, and A.N.Swami, “Mining Association Rules Between Sets of Items in Large Databases”,Proc.ACM SIGMOD Int’l Conf.Management of Data,pp.207-216, May 1993.
  6. R.Agrawal, T. Imielinski, and A.N.Swami, “Mining Association Rules Between Sets of Items in Large Databases”,Proc.ACM SIGMOD Int’l Conf.Management of Data,pp.207-216, May 1993.
  7. R.Jeevarathinam and Antony Selvadoss Thanamani, “An Efficient Algorithm for Mining Software Specifications from Program Execution Traces” presented at Int’l Conf. Sensors, Security, Software and Intelligent Systems (ISSSIS 2009 )
  8. Han J., Pei J., Yin Y.: Mining frequent patterns without candidate generation. Proc. of the 2000 ACM SIGMOD Conf. on Management of Data (2000)
  9. R.Jeevarathinam and Antony Selvadoss Thanamani, “An Implementation of FP-growth algorithm for Software Specification Mining”, CIIT Int’l Journal of Data mining and Knowledge Engineering, Vol-1, pp.18-23, April 2009.
  10. M.J.Zaki, S. Parthasarathy, M.Ogihara, and W.Li, “New Algorithms for Fast Discovery of Association Rules,” Proc. Third Int’l Conf. Knowledge Discovery and Data Mining, pp. 283-286,1997
  11. P. Shenoy, J. R. Haritsa, S. Sudarshan, G. Bhalotia, M.Bawa, and D. Shah, “Turbo-Charging Vertical Mining of Large Databases,” Proc. ACM SIGMOD Int’l Conf. Management of Data, pp.22-23, May 2000.
  12. R.Agrawal, C.Aggrawal, and V.Prasad, “A Tree Projection Algorithm for Generation of Frequent Item Sets,” Parallel and Distributed Computing, pp.350-371, 2000
  13. D. Lo and S-C. Khoo. SMArTIC: Toward building an accurate, robust and scalable specifications miner. In SIGSOFT FSE, 2006.
  14. J. Wang and J. Han. BIDE: Efficient mining of frequent closed sequences. In ICDE, 2004.
  15. M.Song and S. Rajesekaran, “ A Transaction Mapping Algorithm for Frequent Item sets Mining”, IEEE Trans. On Knowledge and Data Engineering, Vol. 18, No. 4, pp. 472-481. April 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Algorithms Apriori FP-growth mining specifications program execution traces transaction mapping