Towards understanding software change request assignment

Abstract

Context: Change Request (CR) repositories play an important role in the software maintenance and evolution process. Through a CR repository, software changes are reported and assigned to developers. Finding the appropriate developer to a CR is crucial for obtaining the lowest, economically feasible, fixing time. Nevertheless, assigning CRs is a labor-intensive and time consuming task. Although many work have proposed automated approaches for CR assignment, they have been implemented without investigating the fundamental aspects which characterize the task itself. Objective: This paper investigates the effort that is taken to assign CR to appropriate developers and identifies the fundamental aspects that characterize it, such as the strategies to perform the assignments and the complexity involved in them. Such investigation improves the current knowledge on the topic, providing researchers and practitioners with useful information towards developing effective solutions. Method: A survey was performed with software developers to understand CR assignment in the Brazilian Federal Organization for Data Processing. The questionnaire was composed of 38 questions, being them both open-ended and closed-ended. We analyzed the answers of 36 respondents. Results: We find that: there is a significant amount of time being spent on assignments (e.g., assigning 20 CRs can take up to 3.3 hours); there are many strategies used to assign CRs, which are complementary to those used in current automated solutions; and CR assignment is very complexity due to a process that requires cognitive abilities for information seeking, communication, and memorization. Conclusion: CR repositories are fundamental to software maintenance, however assigning CRs to developers is an expensive activity. Although we understand that fully and totally accurate automation of assignments is unlikely, further improvements on this direction are feasible and necessary to reduce costs. This way, this paper brings relevant findings to guide new research on automated CR assignment.