A Review of Machine Learning Models for Software Cost Estimation

Abstract

Software cost estimation is a critical task in software projects development. It assists project managers and software engineers to plan and manage their resources. However, developing an accurate cost estimation model for a software project is a challenging process. The aim of such a process is to have a better future sight of the project progress and its phases. Another main objective is to have clear project details and specifications to assist stakeholders in managing the project in terms of human resources, assets, software, data and even in the feasibility study. Accurate estimation results with definitely helps the project manager to do better estimation for the project cost, the time required for various project phases and resources or assets. This paper builds a software cost estimation model using machine learning approach. Different machine learning algorithms are applied to two public datasets to predict the software cost in the early stages. Results show that machine learning methods can be used to predict software cost with a high accuracy rate. Contribution/Originality: This study contributes to the existing literature by enhancing the results of thirteen Machine Learning algorithms on two datasets. The evaluation criteria used in this work are R², MAE, RMAE, RAE, and RRSE. The aim of the proposed model is to predict the effort using dataset attributes and compare them with the actual effort in order to measure the error using different criteria.

Survey of Cost Estimating Software Development Using Machine Learning

“…In this research, Arslan (2019) [16] conducted an assessment of 13 machine learning algorithms using two distinct datasets. The evaluation was based on multiple criteria, including R², MAE, RMAE, RAE, and RRSE.…”

Development of Machine Learning Methods in Hybrid Energy Storage Systems in Electric Vehicles

“…Fuel usage, energy source diversification, and electric propulsion technologies are some of the measures increasingly adopted around the world to make vehicles cleaner and more efficient with the ultimate purpose of reducing greenhouse gas emissions and reaching a sustainable energy ecosystem [1][2][3]. Hybrid electric vehicles are expected to have significantly lower fuel consumption than conventional vehicles as well as substantially lower emissions [4][5][6].…”