Team knowledge sharing
Disclosed systems and methods relate to a knowledge sharing system for aggregating and disseminating knowledge related to programming. The knowledge system for aggregating and disseminating knowledge related to programming may organize or index knowledge according to topics. A topic may be any kind of transferrable piece of knowledge that may be shared. In some embodiments, knowledge organized under a topic may be comprised of a record of interactions with computing systems, and in some embodiments, knowledge organized under a topic may be comprised of text documents, code samples, documentation, web sites, records of discussions, or other kinds of reference materials.
1. A computer-implemented method comprising:
retrieving time-series information about an edit made to source code;
identifying one or more topics for the edit based on a code entity or a parameter included in the edit;
displaying the time-series information and the one or more topics to a user;
displaying a user interface for editing and annotating the time-series information about the edit made to source code;
identifying data in the time-series information as sensitive based on a prediction from a machine learning model;
highlighting the data identified as sensitive; and
providing a user interface element for changing a status of the data to sensitive or not sensitive.
2. The computer-implemented method of claim 1 , further comprising:
displaying the user interface element for the user to add user-edited information about the one or more topics.
3. A computer-implemented method comprising:
retrieving time-series information about an edit made to source code;
identifying one or more topics for the edit based on a code entity or a parameter included in the edit;
displaying the time-series information and the one or more topics to a user; and
computing an expected utility of prompting the user for entry of additional information about the one or more topics.
4. The computer-implemented method of claim 3 , further comprising when the expected utility exceeds a threshold, displaying a user interface element for the user to add user-edited information about the one or more topics.
5. The computer-implemented method of claim 4 , wherein the expected utility is based on a frequency that a topic is encountered by other users, a frequency that the topic is viewed by other users, an amount of existing information on the topic, a rate at which users contribute to the topic when prompted, or a computed value of a time of the user.
6. A computer-implemented method comprising:
retrieving time-series information about a command entered in a terminal, wherein the command is multi-layered;
parsing the command into one or more layers;
identifying one or more topics for the command based on the one or more layers;
displaying the time-series information or the one or more topics to a user;
displaying a user interface for editing and annotating the time-series information about one or more edits made to source code;
identifying data in the time-series information as sensitive based on a prediction from a machine learning model;
highlighting the data identified as sensitive; and
providing a user interface element for changing a status of the data to sensitive or not sensitive.
7. The computer-implemented method of claim 6 , further comprising:
displaying the user interface element for the user to add user-edited information about the one or more topics.
8. A computer-implemented method comprising:
retrieving time-series information about a command entered in a terminal, wherein the command is multi-layered;
parsing the command into one or more layers;
identifying one or more topics for the command based on the one or more layers;
displaying the time-series information or the one or more topics to a user; and
computing an expected utility of prompting the user for entry of additional information about the one or more topics.
9. The computer-implemented method of claim 8 , further comprising when the expected utility exceeds a threshold, displaying a user interface element for the user to add user-edited information about the one or more topics.
10. The computer-implemented method of claim 9 , wherein the expected utility is based on a frequency that a the topic is encountered by other users, a frequency that the topic is viewed by other users, an amount of existing information on the topic, a rate at which users contribute to the topic when prompted, or a computed value of a time of the user.