We’re proud to announce a new release of CodeScene, version 3.4!
CodeScene 3.4 introduces a direct Jira integration together with a new cost model for calculating time in development down to a file level. This feature enables you to see how much time you spend in hotspots and/or modules with lower code health, as well as measuring the effect of improvements.
The Delivery Performance module has been expanded with a new analysis of Planned vs Unplanned work. CodeScene 3.4. also adds support for automatically connecting the analyses to GitHub/BitBucket/GitLab/Azure webhooks for an automated code review of each pull request. The pull request review and CI/CD quality gates have also been expanded to provide detailed info on any code health degradations in order to make the analysis feedback easily actionable.
New Features
-
Direct Jira integration: Connect to Jira directly from a CodeScene analysis instead of using a separate plugin; much simpler.
-
Automated cost calculations for Hotspots: CodeScene introduces a new analysis that can deduce costs automatically based on your development history. Use this cost model to reason about the technical and organizational findings from a financial perspective. For example, how much time do you spend on defects in your top hotspots? What happens over time? As before, CodeScene offers a breakdown of the development costs on three separate levels: file-, architecture-, and system-level.
-
Connect CodeScene to GitHub/BitBucket/GitLab/Azure for Pull Request reviews: Each analysis project now has the option to automatically create webhooks that let you integrate CodeScene’s analysis info into pull requests.
-
Provide feedback on Code Health degradations: CodeScene’s virtual code reviewer – as well as the CI/CD and pull request reviews – now provide detailed feedback on why a piece of code degrades in health.
-
Separate time window for Hotspots calculations: This is an optional configuration that introduces a sliding window for hotspots while maintain the full trends.
Improvements
- The cost data has been merged into the hotspots map to offer a simple way to switch perspective, e.g. between hotspots and costs.