Background: Modern software systems are often too large and complex for an individual developer to fully oversee, making it difficult to understand the implications of changes. Therefore, most collaborative software projects rely on code review as communication network to foster asynchronous discussions about changes before they are merged. Although prior qualitative studies have revealed that practitioners view code review as a communication network, no formal theory or empirical validation exists. Without formalization and confirmatory evidence, the theory remains uncertain, limiting its credibility, practical relevance, and future development.

Objective: In this thesis, our objective is to (1) formalize the theory of code review as a communication network, (2) empirically evaluate the theory across varied perspectives, contexts, and conditions by quantifying the capability of code review to diffuse information among its participants, (3) demonstrate its practical relevance by applying the theory to the domain of tax compliance in collaborative software engineering, and (4) examine how the role of code review as a communication network for collaborative software engineering may evolve in the future.

Methods: To formalize the theory of code review as a communication network, we developed and validated a simulation model that operationalizes its core propositions about information diffusion among participants. To empirically evaluate the theory, we employed two complementary research approaches. First, we used the simulation model to conduct in silico experiments with closed-source code review systems from Microsoft, Spotify, and Trivago, as well as open-source code review systems from Android, Visual Studio Code, and React, to estimate the upper bound of information diffusion in code review. Second, through an observational study, we quantified the diffusion of information in code review across social, organizational, and architectural boundaries at Spotify. To demonstrate the practical relevance of the theory, we analyzed the code review system of a multinational enterprise as a communication network to reveal the latent collaboration structure among developers across borders, which is taxable. To explore the future of code review as a communication network, we conducted a questionnaire survey with 92 practitioners to gather their expectations and discuss how these anticipated changes may reshape our understanding of code review.

Results: By formalizing the theory of code review as a communication network modelled as a time-varying hypergraph, we were able to empirically demonstrate that traditional time-agnostic models substantially overestimate information diffusion in code review. Throughout our empirical studies, we found substential evidence supporting the theory of code review as a communication network: We confirmed that code review is capable of diffusing information quickly and widely among participants, even at a large scale. We also observed extensive information diffusion across social, organizational, and architectural boundaries at Spotify corroborating our theory. However, we also found that information diffusion patterns in open-source code review systems differ significantly, suggesting that findings from open-source environments may not directly apply to closed-source contexts. Through applying the theory of code review as a communication network in the domain of tax compliance, we were able to uncover the significant and previously unrecognized tax risks associated with collaborative software engineering within multinational enterprises. While practitioners consider code review also in the future a core practice in collaborative software engineering, we identify a potential risk that generative AI may undermine code review’s role as a human communication network.

Conclusion: Our work on understanding code review as a communication network contributes not only to theory-driven, empirical software engineering research but also lays the groundwork for practical applications, particularly in the context of tax compliance. Future research is needed to explore the evolving role of code review as a communication network.

Background: Modern software systems are large and complex, requiring collaboration among developers with diverse skills to manage this complexity. Code review is an essential collaborative software engineering practice in which changes are discussed before they are integrated into the codebase, enhancing code quality and promoting knowledge sharing. GUI-based testing is a technique that verifies and validates a system’s behavior through its GUI by simulating user interactions. Like production code, it requires collaboration, as tests are created, reviewed, and maintained alongside production code. Code review practices for tests differ from those for production code. Omitting reviews of tests can lower their quality and increase maintenance costs. However, practices for reviewing GUI-based tests are not well understood, as academic literature mainly focuses on production code and low-level tests.

Objective: We aim to advance the understanding and practice of code review of GUI-based tests by (a) identifying code review guidelines; (b) investigating the specific practices, challenges, and information needs; (c) finding empirical evidence supporting the proposed guidelines; and (d) providing an outlook on how code review may evolve in the future.

Methods: First, we conduct a literature review of white and gray literature to identify guidelines for source and test code, and synthesize them for GUI-based tests. Next, we perform qualitative interviews with software testing professionals to identify practices, challenges, and information needs when reviewing GUI-based tests. To find empirical evidence for the proposed guidelines, we mine open-source software repositories. Finally, we conduct a questionnaire survey to gather practitioners’ expectations about the future importance of code reviews.

Results: We synthesized 33 guidelines for GUI-based tests from literature sources. In analyzing code review comments from open-source repositories, we found empirical evidence supporting 25 out of the 33 proposed guidelines. Practitioners acknowledge the importance of code reviews, but lack defined practices for reviewing GUI-based tests. We identified four practices, six challenges, and four information needs related to reviewing GUI-based tests. The survey results indicate that code review will remain an essential practice with an anticipated increase in code review activities, including those for GUI-based tests.

Conclusion: This thesis advances the understanding and practice of code review for GUI-based tests to improve both review effectiveness and the quality of the tests underreview. We present a set of empirically grounded guidelines derived from literature and refined through the analysis of code review comments of open-source repositories. Our research investigates current practices for reviewing GUI-based tests, highlighting the specific challenges and information needs that distinguish these reviews from those for production code. Finally, we highlight the relevance of our research for the future.