shebe

Research [1][2] shows that 70-85% of developer code search value comes from keyword-based queries. Developers usually search with exact terms they already know (function names, API calls, error messages) and less so with natural language concepts. Github's codesearch famously runs without vector search. I wasn't aware of any BM25-only codesearch tools, so I created shebe. See releases at https://gitlab.com/rhobimd-oss/shebe/-/releases/v0.5.6-rc3 and give it a try. I'm continually validating and asking, is this really useful? see https://github.com/rhobimd-oss/shebe/blob/main/docs/testing/... [1] https://research.google/pubs/how-developers-search-for-code-... [2] https://sourcegraph.com/blog/keeping-it-boring-and-relevant-...

BM25 has been sufficient for my needs. I typically need to refer to codebases of existing tools as referential sources (istio, envoy, oauth2-proxy, tantivy index etc) so I just clone those repos, index them and search away. Built a cli and mcp tool for this workflow. https://github.com/rhobimd-oss/shebe One area where BM25 particularly shines is the refactoring workflow: let's say you want to upgrade your istio installation from 1.28 to 1.29 and maybe in 1.29 the authorizationpolicy crd has a breaking change in one of it's properties. BM25 allows you to efficiently enumerate all code locations in your codebase that need to change and then you can set the cli coders off using this list. Grep and LSP can still perform this enumeration but they have shortcomings. Wrote about it here https://github.com/rhobimd-oss/shebe/blob/main/WHY_SHEBE.md

Turned this into a science experiment and designed a test/workflow to rename the symbol MatrixXd -> MatrixPd in eigen and the results are promising at first glance. See https://github.com/rhobimd-oss/shebe/blob/main/WHY_SHEBE.md#...