When enough people leave a project, the project might stall due to lack of knowledgeable personnel. The minimum number of people who are required to disappear in order for a project to stall is referred to as bus-factor. The bus-factor has been found to be real and tangible and many approaches to measure it have been developed. These approaches are problematic: some of them do not scale to large projects, others rely on ad-hoc notions of primary and secondary developers, and others use arbitrary thresholds. None of them proposes a normalized measure of the bus-factor. Therefore, in this paper we propose a framework that, by modelling a project with a bipartite graph linking people to tasks, allows us to 1) quantify the bus-factor of a project with a normalized measure which does not rely on thresholds; and 2) increase the bus-factor of a project by reassigning people to tasks. We demonstrate our approach on a real case, discuss the advantages of our framework, and outline possibilities for future research.
Evaluating and Improving Projects’ Bus-Factor: A Network Analytical Framework
Piccolo, Sebastiano A.
;De Meo, Pasquale;Terracina, Giorgio
2025-01-01
Abstract
When enough people leave a project, the project might stall due to lack of knowledgeable personnel. The minimum number of people who are required to disappear in order for a project to stall is referred to as bus-factor. The bus-factor has been found to be real and tangible and many approaches to measure it have been developed. These approaches are problematic: some of them do not scale to large projects, others rely on ad-hoc notions of primary and secondary developers, and others use arbitrary thresholds. None of them proposes a normalized measure of the bus-factor. Therefore, in this paper we propose a framework that, by modelling a project with a bipartite graph linking people to tasks, allows us to 1) quantify the bus-factor of a project with a normalized measure which does not rely on thresholds; and 2) increase the bus-factor of a project by reassigning people to tasks. We demonstrate our approach on a real case, discuss the advantages of our framework, and outline possibilities for future research.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


