Application Functionality Enhancement via Effectiveness Scores
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Solution Overview
Problem
In complex application landscapes, existing methods lack efficiency in identifying and optimizing application functionalities, leading to manual intervention and inefficiencies due to the absence of a systematic approach for comparing and updating functionalities based on effectiveness scores.
Innovation Solution
A computer-implemented method that analyzes application logs to form groups of functionalities performing similar functions, assigns effectiveness scores, and provides recommendations for updating each functionality automatically based on comparative scores, thereby enhancing application efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intervention is used to identify and update application functionalities, then accuracy in optimization can be maintained, but productivity and time consumption increase significantly
Solution Approach 1:
The system automatically identifies effective functionalities by analyzing application logs and autonomously updates less effective functionalities without requiring manual intervention. The computer system performs self-service by comparing effectiveness scores, generating update recommendations, and implementing updates automatically, thereby resolving the contradiction between maintaining accuracy and improving productivity.
Solution Approach 2:
The patent replaces the mechanical manual process of identifying and updating application functionalities with an automated computer-based system. The system uses algorithms to analyze logs, calculate effectiveness scores, and implement updates, substituting human manual work with automated computational processes that achieve both high accuracy and high speed.
2Manufacturing precision
If comprehensive analysis of all application functionalities is performed, then optimization quality improves, but device complexity and computational resources increase
Solution Approach 1:
The system segments the analysis by grouping application functionalities into sets based on their functional relationships. Instead of analyzing all functionalities simultaneously in a complex monolithic process, the system divides them into manageable groups, analyzes each group separately, and compares effectiveness within each group. This segmentation maintains comprehensive analysis quality while reducing the complexity of the overall system.
3Productivity
If automatic updates are implemented based on effectiveness scores, then productivity and time efficiency improve, but risk of errors and system stability may worsen
Solution Approach 1:
The system implements a feedback mechanism where application logs are continuously analyzed to determine effectiveness scores of functionalities. The automatic update process uses this feedback from actual system performance to make informed decisions about which functionalities to update. This feedback loop ensures that automatic updates are based on empirical evidence rather than arbitrary changes, maintaining system stability while achieving high productivity.
Data Source
AI summary
Provided are techniques for enhancing applications based on effectiveness scores. Application functionalities of applications in an application landscape are identified. Application logs for the applications are analyzed to identify how the application functionalities are executing. Groups of application functionalities are formed, where each of the groups includes different application functionalities that perform a similar function. For a group of the groups, an effectiveness score is assigned to each of the different application functionalities in that group. For each application functionality, a corresponding recommendation is identified on how that application functionality is to be modified based on the effectiveness score for that application functionality compared to the effectiveness score of each of the other application functionalities in the group. Each application functionality to be modified is automatically updated based on the corresponding recommendation. The applications in the application landscape are executed.