Code Review Comprehension: Reviewing Strategies Seen Through Code Comprehension Theories

2025-03-27

AI Summary

This study investigates the cognitive mechanisms underlying experienced reviewers’ comprehension of code changes during real-world code reviews. Method: Grounded in Letovsky’s theory of program comprehension, we conducted a qualitative study employing theory-driven thematic analysis, on-site observations, and semi-structured interviews. Contribution/Results: We present the first domain-specific cognitive model for code review—Code Review Comprehension Model (CRCM)—which characterizes review comprehension as a three-stage process: *context construction*, *multimodal inspection*, and *mental model comparison*. Our findings empirically establish code comprehension as the foundational cognitive activity in effective review, identify reusable, evidence-based review strategies, and provide actionable design implications for review tooling—including context augmentation and mental model visualization—to enhance feedback quality and review efficiency. This work marks the first rigorous application of program comprehension theory to empirical code review practice.

Technology Category

• Cognitive Modeling & Cognitive Systems: Affective Computing
• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Knowledge Representation and Reasoning: Action, Change, and Causality

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Web Mining and Content Analysis: Models for Web evolution

Abstract

Despite the popularity and importance of modern code review, the understanding of the cognitive processes that enable reviewers to analyze code and provide meaningful feedback is lacking. To address this gap, we observed and interviewed ten experienced reviewers while they performed 25 code reviews from their review queue. Since comprehending code changes is essential to perform code review and the primary challenge for reviewers, we focused our analysis on this cognitive process. Using Letovsky's model of code comprehension, we performed a theory-driven thematic analysis to investigate how reviewers apply code comprehension to navigate changes and provide feedback. Our findings confirm that code comprehension is fundamental to code review. We extend Letovsky's model to propose the Code Review Comprehension Model and demonstrate that code review, like code comprehension, relies on opportunistic strategies. These strategies typically begin with a context-building phase, followed by code inspection involving code reading, testing, and discussion management. To interpret and evaluate the proposed change, reviewers construct a mental model of the change as an extension of their understanding of the overall software system and contrast mental representations of expected and ideal solutions against the actual implementation. Based on our findings, we discuss how review tools and practices can better support reviewers in employing their strategies and in forming understanding. Data and material: https://doi.org/10.5281/zenodo.14748996

Problem

• Understanding cognitive processes in code review
• Extending code comprehension model for reviews
• Improving tools to support reviewer strategies

Innovation

• Observed experienced reviewers performing code reviews
• Applied Letovsky's model for code comprehension analysis
• Proposed Code Review Comprehension Model extension