Recent methods for software effort estimation by analogy
Syona Gupta, Geeta Sikka, Harsh Kumar Verma · ACM SIGSOFT Software Engineering Notes · 2011
Fairly accurate cost and effort predictions of software projects have always been a challenging goal for both, industry as well as academia. Most approaches for effort estimation are either algorithmic or analogy based. The most well-known algorithmic models are COCOMO 81 [1] and Function Points [2]. Estimation by analogy, on the other hand, is essentially a form of case based reasoning. Fuzzy logic, Grey System Theory, Machine Learning techniques such as Genetic Algorithms, Support vector Machines, etc. have been used to optimize the prediction by analogy method. We study these analogy based approaches to software effort estimation and compare some of these techniques on the basis of widely used measures of accuracy.