Software Project Estimation with Machine Learning

Noor Azura Zakaria,Afrujaan Yakath Ali,Nur Hidayah Mohd Khalid,Amelia Ritahani Ismail,Nadzurah Zainal Abidin

doi:10.14569/ijacsa.2021.0120685

Noor Azura Zakaria, Afrujaan Yakath Ali + Show 3 more

Open Access

https://doi.org/10.14569/ijacsa.2021.0120685

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Abstract

This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. It determines the budget, time and resources needed to develop a software project. One of the well-established software project estimation models is Constructive Cost Model (COCOMO) which was developed in the 1980s. Even though such a model is being used, COCOMO has some weaknesses and software developers still facing the problem of lack of accuracy of the effort and cost estimation. Inaccuracy in the estimated effort will affect the schedule and cost of the whole project as well. The objective of this research is to use several algorithms of machine learning to estimate the effort of software project development. The best machine learning model is chosen to compare with the COCOMO.

Highlights

Problems are created for software professionals, their clients, and stakeholders from the impractical project strategy and budget overruns
In this research, machine learning algorithms are used to estimate the effort of a software project that is more accurate compared to the Constructive Cost Model (COCOMO) model
As for Vargha and Delaney A measure there is no effect of difference between actual effort and the predict value of COCOMO NASA 1 model, to support the statement rank sum p-value is used to measure the distribution between the control and experimental sample

Summary

Introduction

Problems are created for software professionals, their clients, and stakeholders from the impractical project strategy and budget overruns. Effort, and resources are estimated at the beginning of the development. Techniques and models were invented to assist the developers in estimating budget and effort. The problem of inaccuracy in estimation still becomes one of the problems for the developers and stakeholders. Even the emergence of one of a well-established project estimation model in the 1980s, COCOMO model, does not solve the problem of inaccuracy in software project estimation. In this research, machine learning algorithms are used to estimate the effort of a software project that is more accurate compared to the COCOMO model. COCOMO model datasets are used to build machine learning models

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