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Analyzing Quality of Jira Stories

As a part of the product management team, my responsibility is to create stories on Jira, with feature definitions and success criteria. A part of my job is also to monitor the quality of code for which we used Embold cloud. And for the longest time, I was wondering if we could get code quality of individual stories right inside Jira. So, when Embold connect app was released, my team was very happy since it helps us see code analysis data right inside Jira.

We use bitbucket for source code management. So, every time a developer commits her code, she just mentions the Jira ticket id to the commit subject. Embold automatically scans the code and displays the analysis on the Jira story.

 The information shown in Jira’s story includes:

  1. Number of Commit made for this story
  2. LOC churn
  3. When was the last commit made
  4. Number of issues added and fixed
  5. Number of
    1. Design issues
    2. Vulnerabilities
    3. Code issues
  6. List of issues
  7. We use the quality gate to ensure that a commit that violates the threshold gets committed unless issues are fixed.

It also has a cool feature where it suggests whom to assign the issue using machine learning.  This has helped new team members find the most likely assignee.


As I understand, Embold connects app currently only supports GitHub cloud, Bitbucket Cloud, and Jira cloud. Hope they add support for on-premises versions soon.

1 comment

Very useful app to collaborate with teams and organize work more efficiently and effectively. It enables people to detect the Jira story issues at ticket level and fixes it immediately. I found it so useful. Good job, Guys...


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