Role of Soft Computing Techniques in Software Effort Estimation: An Analytical Study

Abstract

In developing software, software effort estimation plays an important role in the success of a software project. Inaccurate, inconsistent, and unreliable estimation of a software leads to failure. Because of various special specifications and changes in the requirements, accurate Software Effort Estimation (SEE) for developing software is a difficult task. This software effort estimation must be calculated effectively to avoid unforeseen results. At early development stages, these inabilities to maintain certainty, inaccurate, unreliability are the limitations of expert judgment and algorithmic effort estimation models. After that, attention was turned to machine learning and soft computing methods. Soft computing is an association with the methodologies centering on fuzzy logic, artificial neural networks, and evolutionary computation. These methods will provide flexible information processing capability for handling real-life situations. The main aim of the study is to provide an in-depth review of software effort estimation from the initial stages that included expert judgment-based SEE to the latest techniques of soft computing.