Automation for a deeper understanding of the pull request impactHave you struggled to get your pull requests merged? Or getting a good understanding of someone’s change when reviewing one? For effective code review, one must use the time to understand the change thoroughly. The changed functionality, all added, removed and changed dependencies and the impacted modules. Imagine if all those would be visualized automatically? Now it’s possible to run free Softagram analysis for any opensource pull request. You get visual change analysis directly to GitHub pull request comment field.
Make your reviewer’s life easier and run the Softagram analysis and visualization after opening the pull request.
How to use open source pull request analysis with Softagram Bot?
- Go to https://softagram.com/pull-request-bot/
- Authenticate yourself with GitHub ID (To avoid spam and get your GitHub id to the report)
- Give the pull request numbers to bot (just paste the url from GitHub pull request)
Want to see the Softagram-bot in action?
Why you need pull request visualization?If your development slows down due to the need to wait days for someone to accept your change. On the other hand, as a reviewer, you have not enough time to read the code and understand the impact of the change. Technical debt is made in small steps. Fast decisions in pull request reviews for bug fixes or feature development causes low-quality merges and increasing maintenance burden. Softagram continuous analytics creates deep analytics with machine learning algorithms from each pull request. The Impact reports show visually the changed files and how the whole system is affected by the change. It focuses on analyzing the dependencies and change of dependencies and visualizing them in easy to read informative charts. Impact Report finds the hidden impact of the change, as well as e.g. un_wanted new dependencies or missing unit tests. Based on the rules it can automatically create an issue for the contributor to be fixed before the merge.
Benefits of automatically generated analytics for each pull requestSimilar pull request analysis that you can do for the open-source projects, can be also done for your own project. This automation can be added to GitHub, GitLab, Atlassian Bitbucket or Azure DevOps (VSTS /TFS) projects. Naturally, every change you’ll make to your process should be evaluated by the ROI. Please see the ways AI drove analytics, visualization, and a fully integrated report ´will change your process and improve your code. INCREASE
- Quality of the merges and your software
- The amount of pull request accepted per day, due automated visual analytics
- Software design knowledge due to dependency graphs
- Time of pull request acceptance due to clear points to focus the attention
- Release cycle time due to faster reviews
- Bad quality code merges with transparency and rules
- Unwanted dependencies that degrade your software architecture!
- Merges without analyzing its impact on the system
Activate pull request analysis for your project.You can try the report for any pull request in GitHub open source project here. Continuous analysis for open source GitHub project; Contact us via Chat (below right) or email: email@example.com to activate it. For private repositories, cloud users can sign in and activate analysis (free trial for first 2 weeks):
- GitHub users: https://github.com/apps/softagram
- BitBucket/GitLab/Azure DevOps : https://softagram.com/softagram-cloud/#process