Algorithms for estimating truck factors: a comparative study

Abstract

Software development is a knowledge-intensive industry. For this reason, concentration of knowledge in software projects tends to be very risky, which increases the relevance of strategies that reveal how source code knowledge is distributed among team members. The truck factor (also known as the bus factor) is an increasingly popular concept—proposed by practitioners—that indicates the minimal number of developers that have to be hit by a truck (or leave the team) before a project is incapacitated. Therefore, it is a measure that reveals the concentration of knowledge and the key developers in a project. Due to the importance of this concept, algorithms have been proposed to automatically compute truck factors, using maintenance activity data extracted from version control systems. However, we still lack large studies that assess the results of truck factor algorithms. To fulfill this gap in the literature, this paper describes the results of three empirical studies. In the first study, we validate the results produced by three algorithms to estimate truck factors. To this purpose, we build an oracle of truck factors, gathered via a survey with 35 open-source project teams. In the second study, we provide a comparison between truck factors and core developers, a related concept commonly used to denote the key developers of open-source projects. Our results indicate that truck factor developers are in most cases a subset of core developers. Finally, as the algorithms proposed so far are based in commit data, in the third study, we investigate other factors that may impact the computation of truck factors.