Video: Road to Zero Lint Failures: Tackling Code Quality Challenges at Scale

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Video Summary and Transcription
The talk focuses on LinkedIn's journey to achieve zero lint failures in their extensive codebase, which includes over 24,000 files and 100k commits. They implemented linting in three stages: during development, pre-commit, and pre-merge, to ensure code consistency and bug prevention. LinkedIn faced significant challenges due to the large number of existing lint failures and the continuous introduction of new ones. To tackle these challenges, they introduced a rule that required fixing all existing errors before enabling a new lint rule. They also developed tools like Checkup, which visualizes ESLint failures by team and rule, providing accountability and responsibility. LinkedIn incentivized developers to address lint failures by offering technical support, shout-outs, and a better developer experience. This initiative led to a 30% increase in perceived code quality, with the cleanup of over 6,000 lint failures involving 55 contributors. The success of this initiative highlights the importance of linting tools and strategies in maintaining high code quality in large-scale codebases.

This talk has been presented at React Summit US 2023, check out the latest edition of this React Conference.

FAQ

Lint roles at LinkedIn ensure consistency, bug prevention, and maintenance across the codebase. They help scale guidance to all teams, covering the latest code standards, preventing common mistakes, and maintaining deterministic code during migrations.

LinkedIn runs Lint roles in three stages: during development, pre-commit, and pre-merge. This approach alerts developers early to any Lint rule violations before involving other engineering team members.

LinkedIn faced scaling issues due to their extensive codebase, which included over 24,000 files and 100k commits, and an initial count of over 7,000 Lint failures. The increase in Lint failures was exacerbated by new code and Lint rules that did not address existing issues.

To reduce Lint failures, LinkedIn implemented measures such as blocking commits with Lint failures, setting Lint failure limits for teams, and enforcing standards through a two-step review process. Additionally, they introduced a rule requiring that all existing errors be fixed before a new Lint rule could be enabled at error severity.

LinkedIn used a combination of carrots over sticks, providing technical support, recognition, and a good developer experience. They offered immediate support for queries, shout-outs for cleaning up Lint failures, and tooling that simplified the identification and ownership of errors.

LinkedIn developed a tool that broke down ESLint failures by team and rule, updated nightly. They also used Checkup, a node runner that could analyze the entire codebase nightly and provide structured outputs for easy tracking and visualization of Lint failures.

The initiative to reduce Lint failures led to significant improvements in perceived code quality, with a 30% increase reported in quarterly surveys. The effort involved 55 unique contributors and resulted in the cleanup of over 6,000 Lint failures.

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