US 12,216,657 B2Granted

Contextual searches in software development environments

AssigneeInternational Business Machines Corporation

InventorsJeffrey Bisti, Justin Paul Largo, Colton Jarrett Cox

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Abstract

A computer-implemented method, a computer system and a computer program product introduce context to searches within a software development environment. The method includes receiving a search query from a user in the software development environment. The method also includes obtaining activity data from the software development environment. In addition, the method includes determining a context for the search query based on the activity data. The method further includes performing a search by entering search parameters in a search engine, where the search parameters include the search query and the context. Lastly, the method includes displaying a list of search results in the software development environment, where a weight based on the context is applied to each search result and the list of search results is displayed in order of the weight.

Claims17

Dependent claims

A computer-implemented method for identifying content relevant to a task being performed within a software development environment (SDE), the computer-implemented method comprising:

receiving a search query from a user in the SDE;
obtaining activity data and prior interactions of the SDE from the SDE;
training one or more machine learning models using the activity data, the SDE's prior interactions, and tasks known to the one or more machine learning models through the SDE's prior interactions;
integrating the one or more trained machine learning models in the SDE;
determining a context for the received search query and whether the received search query has sequential context using the one or more trained machine learning models;
predicting one or more steps in a programming objective in the activity data and a subsequent step in the programming objective using the one or more trained machine learning models upon determining that the received search query has sequential context;
introducing the determined context, as well as the predicted one or more steps and the subsequent step in the programming objective, to the received search query using the one or more trained machine learning models to modify search parameters of the received search query;
performing a search using a search engine integrated with the SDE, using the modified search parameters of the received search query;
and
displaying a list of search results in the SDE, wherein the search results are weighted using the one or more trained machine learning models based on the determined context, as well as the predicted one or more steps and the subsequent step in the programming objective.

7 more elements

A computer system for identifying content relevant to a task being performed within a software development environment (SDE), the computer system comprising:

one or more processors, one or more computer-readable memories, and one or more computer-readable storage media;
program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to receive a search query from a user in the SDE;
program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to obtain activity data and prior interactions of the SDE from the SDE;
program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to train one or more machine learning models using the activity data, the SDE's prior interactions, and tasks known to the one or more machine learning models through the SDE's prior interactions;
program instructions, stored on at least one of the one or more storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to integrate the one or more trained machine learning models in the SDE;
program instructions, stored on at least one of the one or more storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to determine a context for the received search query and whether the received search query has sequential context using the one or more trained machine learning models;
program instructions, stored on at least one of the one or more storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to predict one or more steps in a programming objective in the activity data and a subsequent step in the programming objective using the one or more trained machine learning models upon determining that the received search query has sequential context;
program instructions, stored on at least one of the one or more storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to introduce the determined context, as well as the predicted one or more steps and the subsequent step in the programming objective, to the received search query using the one or more trained machine learning models to modify search parameters of the received search query;
program instructions, stored on at least one of the one or more storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to perform a search using a search engine integrated with the SDE, using the modified search parameters of the received search query;
and
program instructions, stored on at least one of the one or more computer-readable storage media for execution by at least one of the one or more processors via at least one of the one or more memories, to display a list of search results in the SDE, wherein the search results are weighted using the one or more trained machine learning models based on the determined context, as well as the predicted one or more steps and the subsequent step in the programming objective.

8 more elements

A computer program product for identifying content relevant to a task being performed within a software development environment (SDE), the computer program product comprising:

one or more computer-readable storage media;
program instructions, stored on at least one of the one or more computer-readable storage media, to receive a search query from a user in the SDE;
program instructions, stored on at least one of the one or more computer-readable storage media, to obtain activity data and prior interactions of the SDE from the SDE;
program instructions, stored on at least one of the one or more computer-readable storage media, to train one or more machine learning models using the activity data, the SDE's prior interactions, and tasks known to the one or more machine learning models through the SDE's prior interactions;
program instructions, stored on at least one of the one or more computer-readable storage media, to integrate the one or more trained machine learning models in the SDE;
program instructions, stored on at least one of the one or more computer-readable storage media, to determine a context for the received search query and whether the received search query has sequential context using the one or more trained machine learning models;
program instructions, stored on at least one of the one or more computer-readable storage media, to predict one or more steps in a programming objective in the activity data and a subsequent step in the programming objective using the one or more trained machine learning models upon determining that the received search query has sequential context;
program instructions, stored on at least one of the one or more computer-readable storage media, to introduce the determined context, as well as the predicted one or more steps and the subsequent step in the programming objective, to the received search query using the one or more trained machine learning models to modify search parameters of the received search query;
program instructions, stored on at least one of the one or more computer-readable storage media, to perform a search using a search engine integrated with the SDE, using the modified search parameters of the received search query;
and
program instructions, stored on at least one of the one or more computer-readable storage media, to display a list of search results in the SDE, wherein the search results are weighted using the one or more trained machine learning models based on the determined context, as well as the predicted one or more steps and the subsequent step in the programming objective.

8 more elements

Dependencies are inferred from the claim text.