Tuning of Cost Drivers by Significance Occurrences and Their Calibration with Novel Software Effort Estimation Method

Brajesh Kumar Singh,A K Misra,Shailesh Tiwari,K K Mishra

doi:10.1155/2013/351913

Brajesh Kumar Singh, A K Misra + Show 2 more

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https://doi.org/10.1155/2013/351913

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Abstract

Estimation is an important part of software engineering projects, and the ability to produce accurate effort estimates has an impact on key economic processes, including budgeting and bid proposals and deciding the execution boundaries of the project. Work in this paper explores the interrelationship among different dimensions of software projects, namely, project size, effort, and effort influencing factors. The study aims at providing better effort estimate on the parameters of modified COCOMO along with the detailed use of binary genetic algorithm as a novel optimization algorithm. Significance of 15 cost drivers can be shown by their impact on MMRE of efforts on original 63 NASA datasets. Proposed method is producing tuned values of the cost drivers, which are effective enough to improve the productivity of the projects. Prediction at different levels of MRE for each project reflects the percentage of projects with desired accuracy. Furthermore, this model is validated on two different datasets which represents better estimation accuracy as compared to the COCOMO 81 based NASA 63 and NASA 93 datasets.

Highlights

Estimation is an important part of software engineering projects, and the ability to produce accurate effort estimates has an impact on key economic processes, including budgeting and bid proposals and deciding the execution boundaries of the project [1]
This study aims at providing the better effort estimate on the parameters of modified Constructive Cost Model (COCOMO) along with the detailed use of binary genetic algorithm as a novel optimization algorithm
Experiments were done by taking 63 COCOMO 81 based dataset used by NASA and various other calculations performed on it. 93 NASA projects from different centers for projects from the years of 1971 to 1987 were collected by Jairus Hihn, JPL, NASA, Manager of SQIP Measurement and Benchmarking Element

Summary

Introduction

Estimation is an important part of software engineering projects, and the ability to produce accurate effort estimates has an impact on key economic processes, including budgeting and bid proposals and deciding the execution boundaries of the project [1]. Effort estimation is a critical activity for planning and monitoring software project development and for delivering the product on time and within budget. The prediction of the effort to be consumed in a software project is, probably, the most sought after variable in the process of project management. The problem of accurate effort estimation is still open and the project manager is confronted at the beginning of the project with the same quagmires as a few years ago [3]. The software industry’s inability to provide accurate estimates of development cost, effort, and/or time is well known [4]

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