SE code optimization using Data Mining Approach

SE code optimization using Data Mining Approach

  IJCOT-book-cover
 		 International Journal of Computer  & Organization Trends  (IJCOT)          
 
© 2012 by IJCOT Journal
Volume-2 Issue-3                          
Year of Publication : 2012
Authors : - S.Suyambu Kesavan,Dr.K.Alagarsamy, 

Citation

- S.Suyambu Kesavan,Dr.K.Alagarsamy,   SE code optimization using Data Mining Approach . International Journal of Computer & organization Trends  (IJCOT), V2(3):9-12 May - Jun 2012, ISSN 2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract

Data mining also holds promises for other software engineering processes, which have to deal with uncertainty and intangible data such as cost estimation, effort estimation and quality. It can also aid in interesting by helping the software engineer to arrive at the require test cases that ensure accurate testing. Data mining also has potential to address some highly challenging areas of software engineering such as adaptability and security. This paper aims to help the software developer in the aspect of code debugging. Code debugging is an eminent phase of the software development. This paper gives some solution to rectify the code debugging problem using data mining technique.

References

[1]. Tao Xie, Jain Pei, Ahmed E Hassen,"mining software engineering data", IEEE 29th International Conference on software engineering ICSE 07.
[2]. Ivano Malavelta, Henry Muccini, Patrizio Pellicciona, Damien Andrew Tamburri, “Providing Architectural Languages and Tools Interoperability through Model Transformation Technologies”, IEEE Transactions on Software Engineering, Vol. 36, No. 4, January/February 2010, pp. 119-140.
[3]. Tao Xie, Suresh Thummalapenta, David lo, Chao Liu,”Data Mining for Software Engineering”, IEEE Computer, August 2009, pp. 55-62.
[4]. Mohammed J Zaki, Christopher D Carothes, Boleslan K Szymaski, “VOGUE: A Variable Order hidden Markov Model with duration based on Frequent Sequence Mining”, ACM Transactions on Knowledge Discovery from Data, Vol. 4 No.1, Article 5, January 2010.
[5]. Francisco P.Romero, Jose A.Olivas, MArcele Genero, Mario Piattini, “Automatic Extraction of the main terminology used in Empirical Software Engineering through Text Mining Techniques” ACM ESEM 08 pp. 357 – 358.

Keywords

code debugging; Pattern matching, Software development.