Forecasting software development costs in scrum iterations using ordinary least squares method

Kostyantyn Kharchenko, Oleksandr Beznosyk (), Bogdan Bulakh, Bogdan Kyriusha and Vadym Yaremenko
Additional contact information
Kostyantyn Kharchenko: National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
Oleksandr Beznosyk: National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
Bogdan Bulakh: National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
Bogdan Kyriusha: National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»
Vadym Yaremenko: National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute»

Technology audit and production reserves, 2024, vol. 4, issue 2(78), 30-33

Abstract: During scrum iterations, it is possible to apply cost forecasting for software testing and operation, if the data from previous iterations are known. Since the data for estimating the scope of work and the deadline within one sprint are accumulated during the project execution, it is possible to use such data to build a forecasting algorithm for the estimated parameters of the subsequent sprints.The approach is based on refining the assessment provided by the development team and the scrum master in a specific metric. The main parameters for evaluation are the execution time and the amount of work performed. As a result of forecasting, it is possible to obtain clarifications for the team's assessment regarding the scope of work for the next sprint. This estimate is based on planned and actual data from the previous sprints.The article discusses the method of least squares and the proposed code for a machine learning model based on this method. An example and graphs for iterations in scrum and corresponding forecasting for the next sprints are presented.The use of the least squares method allows creating a mathematical model that can be adapted to different project conditions, providing flexibility and accuracy in forecasting. For example, the study uses the real data from the previous sprints, which includes the team's resource assessment and actual expenditures. Based on these data, a model was built that demonstrates a high correlation between predicted and actual costs, confirming the effectiveness of using the least squares method. So, the least squares method is an effective tool for forecasting software development costs in scrum iterations. This method allows development teams to better plan their resources and timelines, contributing to the overall efficiency of the project.

Keywords: cost forecasting; scrum; machine learning; least squares method; iterations; software development (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.uran.ua/tarp/article/download/310411/302196 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:baq:taprar:v:4:y:2024:i:2:p:30-33

DOI: 10.15587/2706-5448.2024.310411

Access Statistics for this article

More articles in Technology audit and production reserves from PC TECHNOLOGY CENTER
Bibliographic data for series maintained by Iryna Prudius ().