Donatien Koulla Moulla

Work place: Faculty of Mines and Petroleum Industries, University of Maroua, Maroua, P.O. Box 46, Cameroon

E-mail: moulladonatien@gmail.com

Website:

Research Interests: Software

Biography

Dr. Donatien K. Moulla is a Lecturer in computer science at the Faculty of Mines and Petroleum Industries, University of Maroua, Cameroon. He received his Ph.D. degree in computer science from the University of Ngaoundéré. He earned his Bachelor's and Master's degrees from the department of Mathematics and Computer Science in the same university. He has more than 8 years of teaching and research experience in information systems development and software engineering. His research interests include software estimation, software measurement, software quality and Open Source Software projects.

Author Articles
Duration Estimation Models for Open Source Software Projects

By Donatien Koulla Moulla Alain Abran Kolyang

DOI: https://doi.org/10.5815/ijitcs.2021.01.01, Pub. Date: 8 Feb. 2021

For software organizations that rely on Open Source Software (OSS) to develop customer solutions and products, it is essential to accurately estimate how long it will take to deliver the expected functionalities. While OSS is supported by government policies around the world, most of the research on software project estimation has focused on conventional projects with commercial licenses. OSS effort estimation is challenging since OSS participants do not record effort data in OSS repositories. However, OSS data repositories contain dates of the participants’ contributions and these can be used for duration estimation. This study analyses historical data on WordPress and Swift projects to estimate OSS project duration using either commits or lines of code (LOC) as the independent variable. This study proposes first an improved classification of contributors based on the number of active days for each contributor in the development period of a release. For the WordPress and Swift OSS projects environments the results indicate that duration estimation models using the number of commits as the independent variable perform better than those using LOC. The estimation model for full-time contributors gives an estimate of the total duration, while the models with part-time and occasional contributors lead to better estimates of projects duration with both for the commits data and the lines of data.

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