ABSTRACT
A software project’s success is dependent on the accuracy of its software effort estimate, which is critical in the development of software. The collapse of a software system is caused by imprecise, contradictory, and uncertain estimate. Efficient Software Effort Estimation (SEE) for software development is a challenging process due to the many particular specifications and modifications in the needs that must be considered. This software development effort estimate must be computed correctly in order to prevent unexpected outcomes. Soft computing is a term that refers to a group of approaches that include fuzzy set theory, neural nets, and evolutionary programming among others. The primary goal of the paper is to present an in-depth examination of software effort estimating, starting with the earliest phases, which included skilled judgment-based SEE, and progressing to the most recent soft computing methodologies.
