Why Large Pull Requests Slow Down Development: A Beginner's Guide

As a software engineer, you might have come across the term "change amplification." It refers to the phenomenon where a seemingly simple change in code requires modifications in multiple places. This complexity can have a significant impact on the pace of development, making even small changes cumbersome and time-consuming.

Understanding Change Amplification

Imagine a scenario where you need to change a color in your website's banner. In the past, such a change would require updating the code for every page on the website. However, modern web development practices have evolved to centralize these elements, reducing the need for widespread code changes.

Change amplification, as described by software engineer John Ousterhout, is a symptom of complexity. It occurs when a simple change requires modifications in many different places within a codebase. This not only makes development slower but also indicates a problematic level of coupling within the system.

Measuring the Impact of Pull Request Scope

To understand the impact of change amplification on engineering efficiency, let's consider the concept of pull requests (PRs). PRs are a common practice in software development, where developers submit their code changes for review and merging into the main codebase.

By analyzing data from 1.5 million PRs, we can observe some interesting patterns:

• PRs that change fewer files are merged much faster. This suggests that high-velocity engineering teams should aim to minimize the number of files affected by each PR.
• Even a slight increase in the number of files changed can significantly delay the time required to merge the PR. This indicates higher risks, coupled code, and a higher chance of failing continuous integration processes.
• Review complexity also increases with the number of files changed, requiring more time and cognitive effort from reviewers. The probability of encountering rebase conflicts, which further slow down development, also increases.

Examining Review Efficiency for Different PR Sizes

Another interesting observation concerns the review process for PRs of varying sizes. Surprisingly, when PRs become larger and more complex, the time spent reviewing each file decreases. This seems counterintuitive, but there are a few reasons behind this phenomenon:

• Reviewers may shift their strategy from a meticulous line-by-line assessment to a broader, risk-oriented evaluation of larger PRs. They focus on identifying patterns and verifying auto-generated or repetitive changes.
• Cognitive limits can cause reviewers to lose focus across a large number of files, inadvertently speeding up the review process.

The takeaway from this data is that smaller PRs lead to faster merges, while larger PRs receive less concentrated focus from reviewers. This means that engineering teams aiming for high-quality code and an efficient review process should keep PRs small and manageable.

Best Practices for Minimizing Complexity

To minimize the complexity and change amplification in your codebase, here are some best practices to consider:

1. Limit the number of files changed: Aim to keep your PRs to three or fewer files changed. Beyond this threshold, there is a significant increase in the time required to merge the PR.
2. Try "stacking": Stacking is a source control workflow that involves parallelizing review and development. It allows you to submit smaller, more manageable PRs as you write code, keeping you unblocked while waiting for review. Tools like Graphite can help you implement this workflow if you're using GitHub.
3. Simplify your software design: Complexity often arises from an accumulation of dependencies and obscurities in the codebase. By simplifying your software design, you can reduce change amplification, cognitive load, and the potential for unknown issues. This makes it easier and safer to modify the codebase in the future.

In conclusion, understanding the impact of change amplification and the importance of keeping pull requests small and manageable is crucial for software engineers. By following best practices and minimizing complexity, you can increase development velocity while reducing the risk of regressions in your codebase.

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Tags :

#SoftwareEngineering #DevelopmentEfficiency #CodeReview #ComplexityReduction #AgileDevelopment #CodeQuality