Estimation of software defects fix effort using neural networks

Software defects fix effort is an important software development process metric that plays a critical role in software quality assurance. People usually like to apply parametric effort estimation techniques using historical lines of code and function points data to estimate effort of defects fixes. However, these techniques are neither efficient nor effective for a new different kind of project's fixing defects when code will be written within the context of a different project or organization. In this paper, we present a solution for estimating software defect fix effort using self-organizing neural networks.

[1]  Sunita Chulani,et al.  Bayesian analysis of software cost and quality models , 2001, Proceedings IEEE International Conference on Software Maintenance. ICSM 2001.

[2]  Michael R. Lyu,et al.  Handbook of software reliability engineering , 1996 .

[3]  Audris Mockus,et al.  Understanding and predicting effort in software projects , 2003, 25th International Conference on Software Engineering, 2003. Proceedings..

[4]  Barry Boehm,et al.  Bayesian analysis of software cost and quality models , 1999 .

[5]  Tim Menzies,et al.  Better Analysis of Defect Data at NASA , 2003, SEKE.

[6]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .