Influence of Project Duration constraint on efforts in Constructive Cost Model and optimizing the efforts to obtain accuracy

Software cost estimation accuracy is one of the biggest challenges in the field of software development for developer and customers. In general, many algorithmic models like Constructive Cost Model (COCOMO) are used to estimate cost but they have inability to deal with uncertainties related to software development environment and other factors influencing the software development process. The Evolutionary computation approaches provide the solution for estimating the effort along with handling these uncertainties. In this paper, COCOMO is used as algorithmic model and an attempt is being made to validate the soundness of genetic algorithm using NASA project data. The main objective of this work is to analyze the influence of project duration constraints on efforts and to improve accuracy of system’s output when evolutionary computation based approach is applied to the NASA dataset to derive the software effort estimates. Proposed approach is validated by using 63 NASA project dataset. Empirical results show that application of the proposed approach for software effort estimates resulted in smaller mean magnitude of relative error (MMRE) for all cases and probability of a project(PRED) having a relative error of less than or equal to 0.35 as compared with results obtained with COCOMO is improved significantly for most of the cases.