AUTONOMOUS SUGGESTION OF ISSUE REQUEST CONTENT IN AN ISSUE TRACKING SYSTEM

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.