By Topic

Proposing a New High Performance Model for Software Cost Estimation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Attarzadeh, I. ; Dept. of Software Eng., Univ. of Malaya, Kuala Lumpur, Malaysia ; Siew Hock Ow

Software development effort estimation is the process of predicting the most realistic use of effort required for developing software based on some parameters. It has always characterised one of the biggest challenges in Computer Science for the last decades. Because time and cost estimate at the early stages of the software development are the most difficult to obtain, and they are often the least accurate. Traditional algorithmic techniques such as regression models, Software Life Cycle Management (SLIM), COCOMO model, function points, etc, require an estimation process in a long term. But, nowadays that is not acceptable for software developers and companies. Newer soft computing techniques to effort estimation based on non-algorithmic techniques such as Fuzzy Logic (FL) may offer an alternative for solving the problem. This work aims to propose a fuzzy logic realistic model to achieve more accuracy in software effort estimation. In this innovative model, by applying fuzzy logic and using training procedure to the system, the accuracy of the results is desirable in comparison with the famous traditional algorithmic technique, COCOMO II model. This novelty model will lead researchers to focus on non-algorithmic models to overcome the estimation problems. Our validation experiment was carried out on artificial dataset as well as the COCOMO standard dataset.

Published in:

Computer and Electrical Engineering, 2009. ICCEE '09. Second International Conference on  (Volume:2 )

Date of Conference:

28-30 Dec. 2009