[sanketsaurav]

A few differentiators:

* More issue coverage — for Python, we detect 520+ issues. We also enable you to run things like type checking (if you're using type hints) just by enabling it in the config.

* Custom issues — we have an analyzer team that keeps adding new, novel checkers to the analyzer for common bugs and anti-patterns.

* Fewer false positives — we've optimized our analyzers for reporting less than 5% false positives. On the lowest level, we write augmentations to each checker to remove known false-positives and noise. On the application level, we enable users to very easily ignore issues (for a file, all test files, some file patterns), and also report a false positive. We monitor all false-positive reports and proactively improve our analyzers to resolve them.

* Autofix — we just released this, which allows you to automatically fix some commonly occurring issues directly from DeepSource. In future, we will add more autofixers for issues, so at least 70% issues that we detect can be reliably autofixed.

[punkohl]

Based on the points above, I am still not convinced this is significantly better than existing players, but I could be wrong. Additionally, some of the problems you've mentioned in other comments have already been solved by your competitors.

Do you think the fact that you're a late entrant into this market makes it difficult and/or challenging for your team? Why have your customers chosen you over other platforms? I'm mostly curious and not trying to put you down.