Atlassian Corporation Pty Ltd.

Atlassian Us, Inc.

Atlassian Inc.

Sukho Chung

Noam Bar-on

Jennifer Laetitia Prendki

An issue tracking system for tracking software development tasks is described herein. The issue tracking system may be configured to receive new issue requests from a client device and associate the new issue requests with one or more clusters of previously stored issue records. The issue tracking system may also determine similarity between issues in a first cluster of stored issue records and issues in a second cluster that is associated with a different software development project. Based on a determination that the issue similarity exceeds a threshold, the user may be prompted with one or more recommendations for a subsequent issue request or issue request content.

Issue tracking system using a similarity score to suggest and create duplicate issue requests across multiple projects

An issue tracking system configured to determine whether an issue request submitted by a user of the issue tracking system can, or should, be subdivided into two or more issue requests. In some implementations, the issue tracking system is configured to extract a content item of the issue request (e.g., title, description, and the like) in order to perform a semantic and/or syntactic analysis of that content item. Upon determining that the content item includes two or more clauses linked by a coordinating, subordinating, or correlative conjunction, the system can provide a recommendation to the user to submit discrete two or more issue requests, each one of which corresponds to a single linked clause of the content item.

Autonomous detection of compound issue requests in an issue tracking system

An issue tracking system configured to determine similarity between issue content items (e.g., title, type, description, and the like). Based on a determined similarity satisfying a threshold and/or using a predictive model, the issue tracking system may provide a user with a suggested supplemental content item to be submitted to the issue tracking system.

Autonomous suggestion of issue request content in an issue tracking system

An issue tracking system configured to determine similarity between issue content in an issue request issue content in a previously submitted issue record. Based on the similarity, the issue tracking system may determine a likelihood that a given issue is related to at least one additional issue. In response to a determination that likelihood exceeds a threshold, data can be extracted from the related issue to provide the user with a suggested supplemental issue request to be submitted to the issue tracking system.

Autonomous suggestion of related issues in an issue tracking system

A computer-implemented method comprises, generating, for each group of a plurality of groups of user accounts, a collaboration index value representing a first level of interaction of the each group with other groups of the plurality of groups, the interaction comprising a plurality of operations using a plurality of different computer-implemented applications or functions, generating, for each group of the plurality of groups, a productivity index value, each productivity index value representing a second level of productivity of the respective group, the productivity comprising creating or editing electronic documents using the plurality of different computer-implemented applications or functions, storing, in one or more data repositories, a plurality of first recommendation segments for a collaboration index, each of the first recommendation segments for the collaboration index indicating a range of collaboration index values, storing, in one or more data repositories, a plurality of second recommendation segments for a productivity index, each of the second recommendation segments for the productivity index indicating a range of productivity index values, assigning a first recommendation to each first recommendation segment for the collaboration index and to each second recommendation segment for the productivity index, determining a second recommendation for each group of the plurality of groups based at least on: the collaboration index value of the respective group, the productivity index value of the respective group, the plurality of first recommendation segments for the collaboration index, and the plurality of second recommendation segments for the productivity index and generating and causing displaying, at a computer associated with each group of the plurality of groups, a digital data display that indicates the second recommendation for the respective group.

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San Francisco, CA, United States of America

Sukho Chung