TY  - JOUR
T1  - A Comparative Analysis of Algorithmic and Soft Computing Techniques in Estimating Software Effort
AU - Shivakumar, N. AU - Balaji, N. AU - Ansnthskumsr, K. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 7
SP  - 1207
EP  - 1212
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.1207.1212
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.1207.1212
KW  - Effort estimation
KW  -algorithmic models
KW  -COCOMO
KW  -neuro fuzzy
KW  -PSOK-means clustering
KW  -triangular fuzzy
AB  - Effort estimation of project development was a very challenging problem. It is simple and valid in using algorithmic approaches in effort estimation but they are not so reliable in many cases. Based on information collected from history of projects, the process are continuously improved in the project management to eliminate difficulties in estimating effort of software. However, several methods are used to estimate the software development effort accurately. These non-algorithmic models ware build up on limited number of resources and their performance have not been well investigated. This study compares algorithmic models like Doty, Bailey, Halstead, COCOMO Iand COCOMO II with non-algorithmic approaches like particleswarm optimization k-means clustering algorithms, triangular fuzzy approach and adaptive neuro fuzzy. The results suggests that the non-algorithmic approaches works well with more accurate and reliable.
ER  -