5 ms·

How is this different (or better?) than existing products that offer the same service, such as Codacy. Have been a paying customer of Codacy’s for ~2 years and

How is this different (or better?) than existing products that offer the same service, such as Codacy. Have been a paying customer of Codacy’s for ~2 years and they support most languages out of the box at this point, with Git integration similar to your own. Curious on your thoughts.

sanketsaurav 7y ago
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 7y ago
  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.

sanketsaurav 7y ago

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 7y ago
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.