code-complexity
Measure the churn/complexity score. Higher scores reveal hotspots where refactorings should happen.
Quoting Michael Feathers (source here):
Often when we refactor, we look at local areas of code. If we take a wider view, using information from our version control systems, we can get a better sense of the effects of our refactoring efforts.
Note: code-complexity currently measures complexity using either:
- lines of code count (all languages)
- cyclomatic complexity (JavaScript/TypeScript)
- halstead complexity (JavaScript/TypeScript)
Usage
$ npx code-complexity <path-to-git-directory or URL> [options]Help
Usage: code-complexity <target> [options]
Measure the churn/complexity score. Higher values mean hotspots where refactorings should happen.
Options:
-V, --version output the version number
--filter <strings> list of globs (comma separated) to filter
-cs, --complexity-strategy [strategy] choose the complexity strategy to analyze your codebase with (allowed values: sloc, cyclomatic, halstead).
-f, --format [format] format results using table, json or csv
-l, --limit [limit] limit the number of files to output
-i, --since [since] limit analysis to commits more recent in age than date
-u, --until [until] limit analysis to commits older in age than date
-s, --sort [sort] sort results (allowed valued: score, churn, complexity or file)
-d, --directories display values for directories instead of files
-h, --help display help for command
Examples:
$ code-complexity .
$ code-complexity https://github.com/simonrenoult/code-complexity
$ code-complexity foo --limit 3
$ code-complexity ../foo --sort score
$ code-complexity /foo/bar --filter 'src/**,!src/front/**'
$ code-complexity . --limit 10 --sort score
$ code-complexity . --limit 10 --directories
$ code-complexity . --limit 10 --sort score -cs halstead
$ code-complexity . --since=2021-06-01 --limit 100
$ code-complexity . --since=2021-04-01 --until=2021-07-01
Output
$ npx code-complexity https://github.com/simonrenoult/code-complexity --sort=score --limit=3
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโฌโโโโโโโโฌโโโโโโโโ
โ file โ complexity โ churn โ score โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโผโโโโโโโโผโโโโโโโโค
โ src/cli.ts โ 103 โ 8 โ 824 โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโผโโโโโโโโผโโโโโโโโค
โ test/code-complexity.test.ts โ 107 โ 7 โ 749 โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโผโโโโโโโโผโโโโโโโโค
โ .idea/workspace.xml โ 123 โ 6 โ 738 โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโดโโโโโโโโดโโโโโโโโSpecial thanks
A special thanks to a few contributors that helped me make code-complexity better.
- Alexander Dormann (alexdo) for fixing the
ENOBUFS(and apologies for stealing your code). - Scott Brooks (scottamplitude) for initiating the work on complexity strategies