Software Process Quality Assessment in Medium Sized Software Organizations
International Journal of Computer Science (IJCS Journal) Published by SK Research Group of Companies (SKRGC) Scholarly Peer Reviewed Research Journals
The spurt in the number of medium-sized software organizations has thrown open a number of challenges unique to this segment. These organizations are faced with the twin issues of reducing the costs and achieving quality products at the same time. Most Software processes are typically applicable only for large organizations that can afford the incurred cost. In this context, software process improvement in such organizations is of vital importance. This paper proposes the use of genetic algorithm together with the clustering data mining technique to estimate the quality of processes used by a medium sized organization. Such estimation of process quality would definitely aid the organization in identifying the faulty processes and thereby contribute to process improvement in future projects.
 Berkhin, Pavel, Survey of Clustering Data Mining Techniques, Retrieved from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.145.895  Krishna, K, Murty M,N, “genetic k-means algorithm”, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol 29, Issue 3, 199, pp 433-439  D. Doval, S. Mancoridis, B. S. Mitchell, Automatic Clustering of Software Systems using a Genetic Algorithm, Retrieved from: https://www.cs.drexel.edu/~spiros/papers/step99.pdf  Zhong, Shi, Khoshgoftaar. Taghi M, Seliya, Naeem, “Analyzing Software Measurement Data with Clustering Techniques”, IEEE Intelligent Systems, IEEE Computer Society, 2004