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The JIRA Ticket Analytics app downloads and analyzes issue tickets on a JIRA server. The infographic provides four charts:

  • Percentage of Reopened Tickets. This bar charts gives the number of tickets for each developer which was reopened after it had been closed. Essentially, this measures how often a developer fails to fix a problem on the first attempt.
  • Median Resolution Time. This chart plots the distribution of ticket resolution times for each developer. The blue bar gives the range of the 25% percentile (i.e. the time in which 25% of the tickets are resolved) to the median (i.e. the time in which half of the tickets are resolved). The red bar gives the time range from the median to the 75% percentile.
  • Top Words in Blocker Tickets. These are the words that appear frequently in tickets with "Blocker" priority.
  • Top Words in Critical Tickets. These are the words that appear frequently in tickets with "Critical" priority.

Connection and Import

The data is imported using the import jobs "Tickets" and "ReopenedTickets", both of which are based on the "JiraConnection" connector. You can change the setting in the connector to configure a different JIRA server. For the public JIRA server, select the following settings:

Root Path/jira/

In the two import jobs, you can configure, which tickets should be selected for the analysis. For example, if you configure the "Ticket" import job to use the query 

project="HADOOP" AND created >= "2008/01/01",

the app fetches all tickets in the HADOOP project which where created after January 1st, 2008. The  "ReopenedTickets" query must contain the clause 

(status was reopened OR status = reopened), 

so that the the app is able to compute the "Percentage of Reopened Tickets" chart correctly.


The actual analysis is done the 'Engineering" workbook. Here, the "TopReopened" sheet lists the developers sorted by percentage of reopened tickets, "sortedDuration" calculates the distribution of resolution times, and the "TopBlockerWords" and "TopCriticalWords" sheets give frequently occurring words. 

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