Comparing Measured Agile Software Development Metrics Using an Agile Model-Based Software Engineering Approach versus Scrum Only

Autor: Moe Huss, Daniel R. Herber, John M. Borky
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Software, Vol 2, Iss 3, Pp 310-331 (2023)
Druh dokumentu: article
ISSN: 2674-113X
DOI: 10.3390/software2030015
Popis: This study compares the reliability of estimation, productivity, and defect rate metrics for sprints driven by a specific instance of the agile approach (i.e., scrum) and an agile model-Bbased software engineering (MBSE) approach called the integrated Scrum Model-Based System Architecture Process (sMBSAP) when developing a software system. The quasi-experimental study conducted ten sprints using each approach. The approaches were then evaluated based on their effectiveness in helping the product development team estimate the backlog items that they could build during a time-boxed sprint and deliver more product backlog items (PBI) with fewer defects. The commitment reliability (CR) was calculated to compare the reliability of estimation with a measured average scrum-driven value of 0.81 versus a statistically different average sMBSAP-driven value of 0.94. Similarly, the average sprint velocity (SV) for the scrum-driven sprints was 26.8 versus 31.8 for the MBSAP-driven sprints. The average defect density (DD) for the scrum-driven sprints was 0.91, while that of the sMBSAP-driven sprints was 0.63. The average defect leakage (DL) for the scrum-driven sprints was 0.20, while that of the sMBSAP-driven sprints was 0.15. The t-test analysis concluded that the sMBSAP-driven sprints were associated with a statistically significant larger mean CR, SV, DD, and DL than that of the scrum-driven sprints. The overall results demonstrate formal quantitative benefits of an agile MBSE approach compared to an agile alone, thereby strengthening the case for considering agile MBSE methods within the software development community. Future work might include comparing agile and agile MBSE methods using alternative research designs and further software development objectives, techniques, and metrics.
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