MULTI-OBJECTIVE SOFTWARE PROJECT COST ESTIMATION USING RECENT MACHINE LEARNING APPROACHES

Authors : Doğay Derya, Osman Berkcan Derya, Tansel Dökeroğlu

Pages : 1-14

Doi:10.55185/researcher.1350323

View : 81 | Download : 48

Publication Date : 2024-07-31

Article Type : Other

Abstract :Software projects are gaining strategic importance day by day, even in the daily operations of companies in various sectors. With the increasing need, many companies develop software by creating projects both within their own structure and for the needs of different sectors. Accurately estimating the workforce needed for software projects is crucial to accurately estimating project costs and ensuring timely completion. Since the 1970s, the field of software effort estimation has been the subject of extensive research in the literature. While non-algorithmic methods such as expert opinion were used in the beginning, as the problems became more complex and technology and hardware features diversified, the need for different solution approaches emerged. To overcome these difficulties, algorithmic methods such as regression and model-based estimation have been developed. In recent years, however, with advances in technology, especially in the last decade, there has been a growing interest in applying Machine Learning-based models and Artificial Intelligence to software cost estimation. The focus of this study is to explore Machine Learning based prediction methods in the context of software projects. The aim is to analyze their effectiveness by investigating how these methods can improve software cost estimation.
Keywords : Yazılım Maliyet Tahmini, Yazılım Efor Tahmini, Yapay Zeka, Makine Öğrenimi, Özellik Seçimi