Autonomous suggestion of issue request content in an issue tracking system

Abstract

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.

We claim: 
     
         1 . A networked issue tracking system for tracking issue records and suggesting content to a user, the networked issue tracking system comprising:
 a client device executing a client application that provides a graphical user interface; and   a host service communicably coupled to the client application of the client device over a network and comprising a processor configured to:   receive, from the client application, a first content item extracted from a first issue request field of the graphical user interface, the first issue request field pertaining to a first issue request;   determine a first issue type based at least in part on the first content item;   using a predictive model, identify a second issue record stored by the host service based on the second issue record having a second issue type that corresponds to the first issue type and having at least one content item that corresponds to content extracted from the first issue request;   extract a second content item from the second issue record; and   transmit a suggested content item that is based on the second content item to the client application, the suggested content item being entered into a field of the graphical user interface.   
     
     
         2 . The networked tracking system of  claim 1 , wherein:
 the first issue request field is a description field that contains a description of a first issue to be addressed by the first issue request; and   the processor of the host service is further configured to analyze the description of the first issue request to determine a statistical likelihood that the description indicates either a positive sentiment or a negative sentiment.   
     
     
         3 . The networked tracking system of  claim 2 , wherein:
 in response to the analysis of the description indicating the negative sentiment, determining that an issue type is a bug report that relates to a software problem to be fixed; and   in response to the analysis of the description indicating the positive sentiment, determining that the issue type is a user story issue type that relates to a software function to be added or enhanced to a software program.   
     
     
         4 . The networked tracking system of  claim 2 , wherein:
 the host service determines the statistical likelihood that the description indicates either the positive sentiment or the negative sentiment by performing one or more of:
 subjectivity term identification; 
 objectivity term identification; 
 textual feature extraction; or 
 lemmatized word polarity tagging. 
   
     
     
         5 . The networked tracking system of  claim 1 , wherein:
 the host service is further configured to determine an assignee based on content extracted from the first issue request;   the assignee relates to a software development team that is responsible for the first issue request; and   the assignee is transmitted to the client application and entered into an assignee field of the first issue request interface.   
     
     
         6 . The networked tracking system of  claim 1 , wherein:
 the host service is further configured to determine an issue complexity based on content extracted from the first issue request; and   the host service is configured to determine a time estimate based on the issue complexity.   
     
     
         7 . The networked tracking system of  claim 6 , wherein:
 the issue complexity is determined, in part, based on a complexity of the second issue record.   
     
     
         8 . The networked tracking system of  claim 1 , wherein:
 the host service is configured to receive a first issue complexity from the client device;   the host service is configured to determine an estimated issue complexity based on a set of issue complexities associated with a set of issue records stored by the host service; and   the host service is configured to transmit the estimated issue complexity to the client device.   
     
     
         9 . A computer-implemented method of suggesting issue content to a user of a networked issue tracking system, the computer-implemented method comprising:
 causing a display of a graphical user interface on a client device running a client application of the networked issue tracking system;   extracting a first content item from a first issue request field of the graphical user interface, the first issue request field pertaining to a first issue request;   transmitting the first content item from the client device to a host service;   determining a first issue type based, at least in part, on the first content item;   identifying a second issue record stored by the host service based on the second issue record having a second issue type that corresponds to the first issue type and having at least one content item that corresponds to content extracted from the first issue request;   extracting a second content item from the second issue record;   transmitting a suggested content item that is based on the second content item to the client application; and   causing a display of the suggested content item into a field of the graphical user interface.   
     
     
         10 . The computer-implemented method of  claim 9 , wherein the first issue type is one of: a bug report, a user story, an epic story, or an initiative. 
     
     
         11 . The computer-implemented method of  claim 10 , wherein the first issue type is determined based on a sentiment analysis of at least the first content item. 
     
     
         12 . The computer-implemented method of  claim 11 , wherein:
 in response to the sentiment analysis indicating a positive sentiment, the first issue type is determined to be the user story, the epic story, or the initiative; and   in response to the sentiment analysis indicating a negative sentiment, the first issue type is determined to be the bug report.   
     
     
         13 . The computer-implemented method of  claim 9 , further comprising:
 determining an assignee based, at least in part, on an issue type and a project description extracted from the graphical user interface.   
     
     
         14 . The computer-implemented method of  claim 13 , further comprising:
 identifying a set of issue records that is associated with the assignee;   determining a complexity estimate based, at least in part, on the set of issue records;   transmitting one or more of: the complexity estimate or a time estimate that is based on the complexity estimate to the client device; and   causing a display of one or more of: the complexity estimate or the time estimate.   
     
     
         15 . The computer-implemented method of  claim 9 , further comprising:
 receiving a first time estimate or first complexity estimate from the client device;   identifying a set of issue records that correspond to the first issue request;   determining a modified complexity estimate based, at least in part on the set of issue records and the first time estimate;   transmitting one or more of: the modified complexity estimate or a modified time estimate that is based on the modified complexity estimate to the client device; and   causing a display of one or more of: the modified complexity estimate or the modified time estimate.   
     
     
         16 . A networked issue tracking system for tracking issue records and providing suggested issue content to a user, the networked issue tracking system comprising:
 a client device executing a client application of the networked issue tracking system, the client application providing a graphical user interface for receiving a first issue request, the graphical user interface comprising:
 an issue type field; 
 an issue description field; and 
 a time or complexity index field; and 
   a host service communicably coupled to the client application of the client device over a network and configured to:
 receive from the client application a first issue description extracted from the issue description field; 
 using a predictive model constructed from a data set that includes previously submitted issue requests and previously stored issue records, identify a second issue record having a second issue description and a second time or complexity index; 
 determine a predicted time or complexity index based, at least in part, on the second time or complexity index and the first issue description; and 
 cause a display of the predicted time or complexity index on the graphical user interface of the client device. 
   
     
     
         17 . The networked issue tracking system of  claim 16 , wherein:
 the predicted time or complexity index is determined based, at least in part, on a first issue type extracted from the issue type field.   
     
     
         18 . The networked issue tracking system of  claim 16 , wherein the predictive model includes a regression analysis performed on data extracted from the previously submitted issue requests and the previously stored issue records. 
     
     
         19 . The networked issue tracking system of  claim 18 , wherein, the regression analysis is used to determine the predicted time or complexity index. 
     
     
         20 . The networked issue tracking system of  claim 18 , wherein, the regression analysis is used to determine an issue type.