Automating user-specific performance customization in software controlled across multiple devices
A system automates user-specific performance customization in software controlled across multiple devices by conducting current user sessions in which programs are run and user interfaces are displayed at least in part controlled by user-specific program-specific configuration files. The system receives user commands across a network connection from user devices. The user commands include runtime instructions for the specific running programs for which actions are performed accordingly. The system automatically updating user-specific historical data according to received user requests and/or received user commands. Upon initiating a subsequent user session of any specific user, performance attributes of that user session are controlled according at least in part to the updated user-specific historical data in the user-specific profile.
1 . A system for automating user-specific performance customization in software controlled across multiple devices, the system comprising:
a computing system comprising at least one processor and at least one of a memory device and a non-transitory storage device, wherein said at least one processor executes computer-readable instructions stored at least in part by the at least one of a memory device and a non-transitory storage device; and
a network connection for operatively connecting multiple user devices to the computing system,
wherein, upon execution of the computer-readable instructions, the computing system is configured to perform steps comprising, for each user device of the multiple user devices:
receiving login credentials from a specific user device of the multiple user devices;
confirming validity of the login credentials with respect to a specific user;
initiating and conducting a current user session via the specific user device, the current user session comprising the computing system:
reading a user-specific profile associated with the received login credentials and the specific user, the user-specific profile comprising:
a user-specific program list identifying one or more programs available to the specific user;
for each program of the one or more programs identified in the user-specific program list, a user-specific program-specific configuration file; and
user-specific historical data stored over time from multiple prior user sessions of the specific user,
controlling performance attributes of the current user session according at least in part to the user-specific historical data;
at least one of reading an automatic start-up list comprising an identification of a specific program, and receiving a user request from the specific user device, the user request comprising a request to run the specific program;
authorizing running of the specific program thereby causing across the network connection displaying, by the specific user device, a user interface of the specific program at least in part controlled by the user-specific program-specific configuration file for the specific program, wherein the running of the specific program comprises executing code for the specific program, and wherein the running of the specific program is adjustable by modification of the user-specific program-specific configuration file for the specific program without modifying the code for the specific program;
receiving user commands across the network connection from the specific user device, the user commands comprising runtime instructions for the specific program;
performing actions, via the specific program, corresponding to the runtime instructions;
automatically updating the user-specific historical data in the user-specific profile according to at least one of: the received user request; and the received user commands; and
upon initiating a subsequent user session of the specific user, controlling performance attributes of the subsequent user session according at least in part to the updated user-specific historical data in the user-specific profile.
2 . The system according to claim 1 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises at least one of automatically establishing a display arrangement, automatically sizing a window, automatically positioning a window, and automatically displaying a background image in a window.
3 . The system according to claim 1 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises automatically setting a property on a form, automatically prepopulating at least one field, automatically setting whether a form should automatically perform a query, automatically setting whether a form should open a query dialog, automatically setting whether a form should create a new record, and automatically setting or revising whether at least one field in a form should start empty when initiated.
4 . The system according to claim 1 , wherein the code for the specific program is stored separate from the user-specific program-specific configuration file for the specific program.
5 . The system according to claim 1 , wherein the computing system, upon initiating and conducting the current user session via the specific user device, concurrently conducts multiple other user sessions for other users via other respective user devices.
6 . The system according to claim 1 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises using a controlling algorithm trained by a machine-learning technique.
7 . The system according to claim 6 , wherein the computing system further trains the controlling algorithm by the machine-learning technique, and the machine-leaning technique comprises:
ingesting user-specific historical data stored over time from multiple prior user sessions of each of multiple users; and
in at least one iteration of multiple iterations:
predicting subsequent user commands of at least some users of the multiple users based on the ingested historical data stored over time using a trained model based on weighted calculations;
receiving across the network connection actual subsequent user commands from the at least some users via respective user devices;
aggregating comparison data by comparing respectively the predicted subsequent user commands of the at least some users to the actual subsequent user commands from the at least some users; and
updating, using the aggregated comparison data, weights of the weighted calculation for use in one or more other iterations following the at least one iteration, in which further user commands of at least some users of the multiple users are predicted.
8 . A system for automating user-specific performance customization in software controlled across multiple devices, the system comprising:
a computing system comprising at least one processor and at least one of a memory device and a non-transitory storage device, wherein said at least one processor executes computer-readable instructions at least in part stored by the at least one of a memory device and a non-transitory storage device; and
a network connection for operatively connecting multiple mobile user devices to the computing system,
wherein, upon execution of the computer-readable instructions, the computing system is configured to perform steps comprising, for each mobile user device of the multiple mobile user devices:
receiving login credentials from a specific mobile user device of the multiple mobile user devices;
confirming validity of the login credentials with respect to a specific user;
initiating and conducting a current user session via the specific mobile user device, while concurrently conducting multiple other user sessions for other users via other respective mobile user devices, the current user session comprising the computing system:
reading a user-specific profile associated with the received login credentials and the specific user, the user-specific profile comprising:
a user-specific program list identifying one or more programs available to the specific user;
for each program of the one or more programs identified in the user-specific program list, a user-specific program-specific configuration file; and
user-specific historical data stored over time from multiple prior user sessions of the specific user,
controlling performance attributes of the current user session according at least in part to the user-specific historical data using a controlling algorithm trained by a machine-learning technique;
at least one of reading an automatic start-up list comprising an identification of a specific program, and receiving a user request from the specific mobile user device, the user request comprising a request to run the specific program;
authorizing running of the specific program thereby causing across the network connection displaying, by the specific mobile user device, a user interface of the specific program at least in part controlled by the user-specific program-specific configuration file for the specific program, wherein the running of the specific program comprises executing code for the specific program, and wherein the running of the specific program is adjustable by modification of the user-specific program-specific configuration file for the specific program without modifying the code for the specific program;
receiving user commands across the network connection from the specific mobile user device, the user commands comprising runtime instructions for the specific program;
performing actions, via the specific program, corresponding to the runtime instructions;
automatically updating the user-specific historical data in the user-specific profile according to at least one of: the received user request; and the received user commands; and
upon initiating a subsequent user session of the specific user, controlling performance attributes of the subsequent user session according at least in part to the updated user-specific historical data in the user-specific profile.
9 . The system according to claim 8 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises at least one of automatically establishing a display arrangement, automatically sizing a window, automatically positioning a window, and automatically displaying a background image in a window.
10 . The system according to claim 8 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises automatically setting a property on a form, automatically prepopulating at least one field, automatically setting whether a form should automatically perform a query, automatically setting whether a form should open a query dialog, automatically setting whether a form should create a new record, and automatically setting or revising whether at least one field in a form should start empty when initiated.
11 . The system according to claim 8 , wherein:
the code for the specific program is stored separate from the user-specific program-specific configuration file for the specific program; and
performance of the specific program is adjustable by modification of the user-specific program-specific configuration file for the specific program without modifying the code for the specific program.
12 . A computer-implemented method for a computing system to securely customize user-specific run-time performance in software controlled across multiple devices, the computing system including at least one processor and at least one of a memory device and a non-transitory storage device storing computer-readable instructions, the at least one processor configured to execute the computer-readable instructions, and a network connection for operatively connecting multiple user devices to the computing system, the method comprising, upon execution of the computer-readable instructions, the computing system is configured to perform steps comprising for each user device of the multiple user devices:
receiving login credentials from a specific user device of the multiple user devices;
confirming validity of the login credentials with respect to a specific user;
initiating and conducting a current user session via the specific user device, the current user session comprising the computing system:
reading a user-specific profile associated with the received login credentials and the specific user, the user-specific profile comprising:
a user-specific program list identifying one or more programs available to the specific user;
for each program of the one or more programs identified in the user-specific program list, a user-specific program-specific configuration file; and
user-specific historical data stored over time from multiple prior user sessions of the specific user,
controlling performance attributes of the current user session according at least in part to the user-specific historical data;
at least one of reading an automatic start-up list comprising an identification of a specific program, and receiving a user request from the specific user device, the user request comprising a request to run the specific program;
authorizing running of the specific program thereby causing across the network connection displaying, by the specific user device, a user interface of the specific program at least in part controlled by the user-specific program-specific configuration file for the specific program, wherein the running of the specific program comprises executing code for the specific program, and wherein the running of the specific program is adjustable by modification of the user-specific program-specific configuration file for the specific program without modifying the code for the specific program;
receiving user commands across the network connection from the specific user device, the user commands comprising runtime instructions for the specific program;
performing actions, via the specific program, corresponding to the runtime instructions;
automatically updating the user-specific historical data in the user-specific profile according to at least one of: the received user request; and the received user commands; and
upon initiating a subsequent user session of the specific user, controlling performance attributes of the subsequent user session according at least in part to the updated user-specific historical data in the user-specific profile.
13 . The method of claim 12 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises at least one of automatically establishing a display arrangement, automatically sizing a window, automatically positioning a window, and automatically displaying a background image in a window.
14 . The method of claim 13 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises automatically setting a property on a form, automatically prepopulating at least one field, automatically setting whether a form should automatically perform a query, automatically setting whether a form should open a query dialog, automatically setting whether a form should create a new record, and automatically setting or revising whether at least one field in a form should start empty when initiated.
15 . The method of claim 12 , wherein the computing system, upon initiating and conducting the current user session via the specific user device, concurrently conducts multiple other user sessions for other users via other respective user devices.
16 . The method of claim 12 , wherein controlling performance attributes of the current user session according at least in part to the user-specific historical data comprises using a controlling algorithm trained by a machine-learning technique.
17 . The method of claim 16 , wherein the computing system further trains the controlling algorithm by the machine-learning technique, and the machine-leaning technique comprises:
ingesting user-specific historical data stored over time from multiple prior user sessions of each of multiple users; and
in at least one iteration of multiple iterations:
predicting subsequent user commands of at least some users of the multiple users based on the ingested historical data stored over time using a trained model based on weighted calculations;
receiving across the network connection actual subsequent user commands from the at least some users via respective mobile user devices;
aggregating comparison data by comparing respectively the predicted subsequent user commands of the at least some users to the actual subsequent user commands from the at least some users; and
updating, using the aggregated comparison data, weights of the weighted calculation for use in one or more other iterations following the at least one iteration, in which one or more other iterations further user commands of at least some users of the multiple users are predicted.