Abstract—Software development effort estimation is a
daunting task that is being carried out by software developers
as not much of the information about the software which is to
be developed is available during the early stages of
development. The information that is to be gathered for
various attributes of software needs to be subjective which
otherwise leads to imprecision and uncertainty. Inaccurate
estimation of the software effort and schedule leads to financial
loses and also delays in project deadline. In this paper, we
present the use of soft computing technique to build a suitable
model which improves the process of effort estimation. To do
so, various parameters of Constructive Cost Model (COCOMO)
II are fuzzified that leads to reliable and accurate estimates of
effort. The results show that the value of Magnitude of Relative
Error (MRE) obtained by applying fuzzy logic is quite lower
than MRE obtained from algorithmic model. By analyzing the
results further it is observed that Gaussian Membership
Function (gaussmf) performs better than Triangular
Membership Function (trimf) and Trapezoidal Membership
Function (trapmf) as the transition from one interval to
another is quite smoother. Here varying number of COCOMO
II inputs are fuzzified with these membership functions. The
validation of the experiment is carried on COCOMO public
Index Terms—Software cost estimation, COCOMO, soft computing, fuzzy logic.
Sandeep Kad is with the Department of Information Technology, Amritsar College of Engineering and Technology, Amritsar, Punjab, India (e-mail: firstname.lastname@example.org).
Vinay Chopra is with the Department of Computer Science and Engineering,DAV Institute of Engineering and Technology, Jalandhar, Punjab, India (e-mail: email@example.com).
Cite:Sandeep Kad and Vinay Chopra, "Software Development Effort Estimation Using Soft Computing," International Journal of Machine Learning and Computing vol.2, no. 5, pp. 548-551, 2012.