Developers

BetterBugs equips developers with in-depth information about each reported bug

Developers can take advantage of the detailed bug reports provided by QA teams. Visual proof of issues, such as screenshots or screen recordings, combined with important technical details, such as system logs (both frontend and backend), network logs and requests, and system information with every bug report, allows developers to resolve issues efficiently.

Moreover, developers can use AI for debugging. BetterBugs AI Assistant enables faster debugging with auto-generated issue repro steps. You also get AI-powered impact analysis and bug diagnosis.

1

Get DevTools Logs (Frontend + Backend)

BetterBugs goes beyond traditional bug reports by offering a wealth of information. Developers receive bug reports from QA with technical logs, network logs, system details, and more. This comprehensive data allows developers to gain deeper insights into the bug, so the root cause analysis better, and resolve it much faster.

2

Visualize, Observe, and Fix Way Faster, Plus Better

BetterBugs provides a clear and detailed visual representation of the issue through screenshots or video recordings. This visual context, combined with the included steps (manual, plus AI), helps to follow the exact steps to identify the root cause and fix issues much better.

3

96% Faster Debugging Sessions with Perfect Bug Reports

BetterBugs equips developers with in-depth information about each reported bug. From error messages to system configurations and environments, developers can access relevant details for a quicker and more accurate debugging process. This level of information ensures that developers can focus on resolving the issue rather than spending time gathering data.

4

Smart Debugging with BetterBugs AI Assistant

Developers get all the necessary technical and visual in a well-structured bug report. Moreover, BetterBugs AI Assistant significantly accelerates the debugging process. Developers can dive straight into debugging the reported issues, and use AI-powered repro steps and insights, leading to more efficient software development and testing lifecycles.