Program Fragment Analysis for Functionalization Candidate Extraction
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Solution Overview
Problem
Existing methods are limited in automatically extracting and presenting similar processes in a program, making it difficult to identify functionalization candidates for improving program maintainability.
Innovation Solution
A program creation assistance system that includes a program fragmentation unit, a fragment group extraction unit, a functionalization candidate extraction unit, and an output unit to automatically identify and present functionalization candidates by matching instruction groups, variable usage patterns, and variable types between program fragments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual extraction of similar processes is performed, then functionalization candidates can be identified, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces the manual mechanical process of extracting similar processes with an automated computer-based system. The extraction unit automatically identifies similar processes by comparing program structures and logical expressions, eliminating the need for manual analysis while maintaining extraction accuracy.
Solution Approach 2:
The patent introduces an intermediary extraction unit that acts as a bridge between the raw program code and the functionalization candidates. This unit automatically analyzes program structures, compares logical expressions, and identifies similar processes, serving as a mediator that automates the extraction process without requiring direct manual intervention.
2Productivity
If automated extraction of similar processes is implemented, then time consumption is reduced, but the ability to accurately identify functionalization candidates is limited
Solution Approach 1:
The patent segments the automated extraction process into multiple distinct units: a fragmentation unit that divides programs into logical blocks, an extraction unit that identifies similar processes, and a determination unit that validates functionalization candidates. This segmentation allows each unit to specialize in specific tasks, improving both efficiency and accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where the determination unit validates the results produced by the extraction unit. The system compares extracted similar processes against predefined criteria and program structure rules, providing feedback that ensures the accuracy of identified functionalization candidates while maintaining automated efficiency.
3Measurement precision
If program fragmentation is performed, then similar processes can be identified more effectively, but the system complexity increases
Solution Approach 1:
The patent designs the fragmentation unit to serve multiple functions: it divides programs into logical blocks, identifies boundaries between different processes, and prepares data for subsequent extraction and validation steps. This multi-functionality reduces the need for separate specialized components, managing system complexity while maintaining identification accuracy.
Data Source
AI summary
A program fragmentation unit (131) divides a target program into fragments according to groups of processing. A fragment group extraction unit (132) extracts, from among sets of fragments, each set in which instruction groups match between fragments, as a fragment group. A functionalization candidate extraction unit (136) extracts, from among sets of fragment groups, a set in which instruction groups match between fragment groups, usage patterns of a variable group match between the fragment groups, and types of variables match between the fragment groups, as a functionalization candidate. An output unit (140) outputs information on the functionalization candidate.