Assessing the Effectiveness of MCR-KSM for Waiting Waste Reduction: An Empirical Study

Abstract: Modern Code Review (MCR) is a well-known and widely adopted quality assurance activity to develop quality software. Although it is a core activity for improving code quality, it generates various types of waste, including waiting waste, defect waste, and composite solution waste. Besides all other wastes, the waiting waste is the most critical one, leading to mental distress, delayed code merges, and project delays. Researchers have made efforts to reduce the production of waiting waste by providing various automated code review tools, techniques and models, one of them is the MCR Knowledge Sharing Model (MCR-KSM). The model claims that it supports sustainable software engineering by minimizing waiting waste reduction during MCR activities. This study aims to evaluate the effectiveness of MCR-KSM with respect to the reduction of waiting waste produced during MCR activities. The experiment methodology is employed for this purpose. This paper presents the experimental investigation approach along with the results. The experiment was conducted in dual sessions with 28 graduate students having similar educational and industrial experience. The tools and techniques, such as SPSS paired t-test and value stream mapping, are used for experimental data management and analysis. The study results revealed that the model significantly helps in the reduction of waiting waste production. The conducted study has implications for investigators to extend the research with different parameters and settings.

Nargis Fatima, Sumaira Nazir and Suriayati Chuprat. “Assessing the Effectiveness of MCR-KSM for Waiting Waste Reduction: An Empirical Study”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.9 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160937

@article{Fatima2025,
title = {Assessing the Effectiveness of MCR-KSM for Waiting Waste Reduction: An Empirical Study},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160937},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160937},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {9},
author = {Nargis Fatima and Sumaira Nazir and Suriayati Chuprat}
}