While testing for software quality assurance in Jira, QA engineers often need faster and more accurate ways to evaluate workflows, identify bottlenecks, and improve reporting outcomes. This is where efficiency testing becomes critical, especially when combined with Jira Query Language (JQL), a powerful query system designed for retrieving issues with precision.
JQL helps QA teams sift through hundreds—or even thousands—of issues and retrieve only what truly matters. As a result, teams can improve test execution performance, streamline QA process evaluation, and make data-backed decisions faster.
In this guide, we explore making JQL work for you for better QA reporting in Jira, using practical examples and proven Jira query language tips.
Making JQL Queries Work in Real QA Scenarios
Let’s look at creating JQL queries. These queries can be as simple as listing issues resolved daily or as critical as identifying defects that block the application lifecycle. By applying performance-focused testing techniques through JQL, QA teams gain better visibility into system behavior.
Hey… Who Moved My Ticket?
While working on my previous project, I noticed that some tickets had been declared closed by developers. In many cases, specification changes during the ticket lifecycle caused developers and testers to interpret the issue differently.
To identify such cases, I created a JQL query that surfaced issues raised by QA but closed by developers unintentionally. This approach supports operational testing efficiency by preventing miscommunication from slipping through the cracks.
JQL Syntax Used
reporter in (Ann,Kenny,Kevin)
AND issuetype = Bug
AND status in (Invalid, Done)
AND NOT status changed by (Ann,Kenny,Kevin)
AND project in (Prudent)
Why This Query Works
- reporter in (Ann, Kenny, Kevin)
Includes all QA team members. If user groups exist, you can replace names with:
reporter in (members of(“QA-Team”)) - issuetype = Bug
Retrieves only defect-related issues. - status in (Invalid, Done)
Filters closed tickets. - NOT status changed by (Ann, Kenny, Kevin)
Identifies tickets closed by someone outside QA. - project in (Prudent)
Limits results to the relevant project.
Clear Captions Case Study
Read OnPath’s ClearCaptions case study to see how strategic testing accelerated growth and reduced release risk for a high-stakes accessibility product.
What’s on Your Plate?
During a project, QA leads often need to review tickets reopened by individual testers. This helps measure validation workflow effectiveness and highlights recurring issues.
To view tickets reopened by Ann, I used the following JQL query:
reporter in (Ann,Kenny,Kevin)
AND issuetype = Bug
AND status changed from “Ready for QA” to Assigned
AND project in (Prudent)
AND status changed by Ann
This query isolates reopened issues, which is essential for continuous quality assessment and team-level reporting.
Let’s Get a Move On with JQL
As a QA team lead, ensuring that tickets move smoothly through their lifecycle is essential. However, dormant tickets can quietly clutter dashboards and distort reports.
By identifying issues with no recent activity, teams can improve testing throughput analysis and maintain clean backlogs.
JQL for Identifying Dormant Issues
reporter in (Ann,Kenny,Kevin)
AND issuetype = Bug
AND status changed BEFORE -1m
AND status in (Assigned)
AND project in (Prudent)
- status changed BEFORE -1m
Surfaces issues inactive for over 30 days.
This technique strengthens QA productivity assessment by highlighting stalled workflows.
Kudos to the Team
Monitoring resolved issues daily or weekly provides valuable insight into team performance. More importantly, it reinforces morale.
After all, a small step for the team… you know the rest!
JQL Syntax for Daily Resolutions
creator in (Ann,Kenny,Kevin)
AND updated > -1d
AND status changed to “Fixed on QA”
AND status = Resolved
This query supports outcome-driven testing evaluation by showcasing completed work.
Note:
If you run this filter on a Monday, adjust the timeframe to updated > -2d or -3d, depending on your last working day.
Why JQL Improves QA Reporting Efficiency
The real strength of JQL lies in its flexibility. Queries can reference system fields, custom fields, and functions, and they can be saved as reusable filters. As a result, teams always access the most up-to-date insights.
If you want to deepen your understanding, Atlassian’s advanced JQL documentation is an excellent resource. Refer here: https://confluence.atlassian.com/jira/advanced-searching-179442050.htm
So go ahead—use the power of JQL. May the force be with you!
Frequently Asked Questions (FAQs)
How does JQL support efficiency testing in QA?
JQL enables targeted issue tracking, helping teams identify delays, bottlenecks, and workflow gaps quickly.
Are Jira query language tips useful for large projects?
Yes. They become even more valuable as issue volume increases.
Can JQL improve QA reporting accuracy?
Absolutely. Saved filters and dynamic queries ensure consistent, real-time reporting.
Is JQL suitable for non-technical QA leads?
Yes. With practice, even non-technical users can create effective queries.
How often should JQL filters be reviewed?
Regular reviews ensure filters align with evolving project workflows.
Does JQL help with long-term QA performance tracking?
Yes. Historical queries support trend analysis and process optimization.
