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The effects of change decomposition on code review-a controlled experiment.

Marco di Biase^1,2, Magiel Bruntink², Arie van Deursen¹

¹Delft University of Technology, Delft, The Netherlands.

Peerj. Computer Science

|April 5, 2021

Summary

Decomposing large code changes into smaller, coherent ones reduces wrongly reported issues and improves the code review process for developers. This practice enhances efficiency by minimizing noise and supporting reviewers in their tasks.

Keywords:

Change decomposition Code review Controlled experiment Pull-based development model

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Area of Science:

Software Engineering
Human-Computer Interaction
Empirical Software Engineering

Background:

Code review is a critical yet cognitively demanding software development process.
Prior research suggested that decomposing large change sets could improve code review efficiency.
Quantitative evidence supporting this hypothesis was previously lacking.

Purpose of the Study:

To quantitatively assess the impact of change decomposition on code review outcomes, including defect detection, issue reporting accuracy, and reviewer understanding.
To qualitatively explore how developers approach code reviews for both large and decomposed changes.
To analyze the influence of change decomposition on reviewer behavior and knowledge acquisition.

Main Methods:

A controlled experiment was conducted with 28 software developers (professionals and graduate students).
The study utilized a pull-based development model to simulate real-world code review scenarios.
Participants reviewed both large and decomposed code changes to compare outcomes.

Main Results:

Change decomposition resulted in a significant reduction in wrongly reported issues.
Reviewers exhibited increased context-seeking behavior when reviewing decomposed changes.
No significant impact was observed on the number of defects found or the understanding of change rationale.

Conclusions:

Decomposing code changes into smaller, conceptually coherent units is a beneficial software engineering practice.
This approach reduces noise and supports developers in performing effective code reviews.
Separating commits by concept is recommended to enhance code review quality and efficiency.