Dynamic Service Function Module Addition via Usage Frequency
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Solution Overview
Problem
Software developers face challenges in precisely extracting all functions that compose a service when character strings identified as functions are not included in text deliverables, leading to incomplete identification of service functions.
Innovation Solution
An information processing apparatus with a generation unit that analyzes user frequency of service function usage and a service function addition unit that dynamically adds functional modules to the service function based on usage frequency, eliminating the need for a traceability matrix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a traceability matrix is generated from character strings in text deliverables to identify service functions, then the process of identifying functions is automated, but the precision of function extraction deteriorates when character strings are not included in text deliverables
Solution Approach 1:
The system uses usage frequency data as feedback to supplement the traceability matrix. By monitoring actual usage patterns of service functions, the system can identify and add functional modules that were not captured in the initial text analysis, thereby improving extraction precision while maintaining automation.
Solution Approach 2:
The system performs preliminary extraction of functions from text deliverables using the traceability matrix, then subsequently uses usage frequency data to identify additional functional modules. This two-stage approach ensures that both automated extraction and precision requirements are met by building upon the initial results.
2Device complexity
If the service function is limited to character strings found in text deliverables, then the service definition remains simple, but the ability to add functional modules deteriorates
Solution Approach 1:
The service function definition transitions from a static set of character strings to a dynamic structure that can evolve based on usage frequency data. The system maintains the simplicity of the base definition while enabling dynamic addition of functional modules through automated analysis of usage patterns.
Solution Approach 2:
The system enables self-service functionality by automatically identifying and adding functional modules based on usage frequency data without requiring manual intervention. The system serves itself by using its own usage data to expand and refine the service function definition.
3Measurement precision
If functional modules are added based on usage frequency, then the service function becomes more complete, but the system complexity increases
Solution Approach 1:
The system automatically manages the addition of functional modules by using its own usage frequency data to identify and incorporate new modules. This self-service mechanism eliminates the need for manual configuration, thereby achieving completeness without proportionally increasing operational complexity.
Solution Approach 2:
The system uses usage frequency data as feedback to automatically determine which functional modules should be added. This feedback-driven approach ensures that only necessary modules are added based on actual usage patterns, maintaining system manageability while improving completeness.
Data Source
AI summary
An information processing apparatus includes a generation unit and a service function addition unit. The generation unit generates use record information indicating a frequency of use of a service function by a user. The service function addition unit adds, in accordance with the frequency of use, a functional module to the service function provided to the user.