Module Structural Analysis Supporting Device
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Solution Overview
Problem
Structural analysis of large-scale systems with many modules is difficult due to the complexity of understanding the distributed functions across multiple modules, even with tools like module block diagrams and flowcharts.
Innovation Solution
A device that converts modules into secondary modules by expanding and processing sentences between specific start and end locations, generating secondary sentences that collect and organize functions, allowing for easier analysis and maintenance by adding hierarchy IDs and operand information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If modules are divided into many small processing sections to achieve structured programming, then program maintainability and modularity are improved, but understanding the overall system function becomes more difficult
Solution Approach 1:
The patent implements nesting by embedding processing section names and module call information within the expanded module view. When a module is expanded, it contains nested references to its constituent processing sections, which themselves may contain nested module calls. This hierarchical nesting allows users to drill down from the overall module level to individual processing sections while maintaining context of the complete system structure.
Solution Approach 2:
The patent introduces processing section names as intermediary elements between modules and their internal logic. Instead of directly exposing raw code or detailed implementation, the system uses named processing sections as mediators that represent functional blocks. These intermediaries simplify the view by abstracting complex internal logic into named entities that can be easily referenced and understood in the expanded module context.
2Loss of information
If detailed internal processing of each module is examined to understand system function, then functional understanding is improved, but analysis time and effort increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-expanding modules to generate a comprehensive view that includes all processing section names and module call information before analysis begins. This pre-processing step creates an expanded module structure that already contains the detailed functional information needed for understanding, eliminating the need for analysts to manually trace through each module's internal processing step-by-step.
Solution Approach 2:
The patent segments the analysis process into two distinct views: the original compact module view for overview and the expanded module view for detailed functional analysis. By segmenting the information presentation this way, users can quickly switch between high-level system overview and detailed functional breakdown without being overwhelmed by the complete detail at all times, thus reducing overall analysis time.
3Loss of information
If all processing sections and module calls are expanded in detail, then complete functional information is obtained, but the amount of information becomes overwhelming and hard to analyze
Solution Approach 1:
The patent implements local quality by providing different levels of detail in different parts of the system view. The expanded module view contains detailed processing section information where needed, while maintaining references to the broader system context. This allows dense functional information to be presented locally within specific module expansions without overwhelming the entire system view, as users can selectively expand only the modules relevant to their analysis.
Solution Approach 2:
The patent adds a hierarchical dimension to the module representation by creating an expanded view that includes nested processing sections and module calls. This dimensional transformation organizes the overwhelming amount of information into a multi-level hierarchy, where the vertical dimension represents the expansion depth from module to processing section to nested module calls, making the information more manageable and analyzable.
Data Source
AI summary
A device supporting the structural analysis of a module comprises: a storage means storing at least one module; and a conversion means that converts a prescribed target module among the modules stored by the storage means to a secondary module and stores same in the storage means. The conversion means reads the target module from the storage means and sequentially outputs to the secondary module each sentence written from a prescribed processing start location in the target module to a prescribed processing end location. The conversion means also recursively develops a sentence written in processing units etc., for execution, and outputs same to the secondary module, when the sentence is a module internal processing unit or a sentence that executes another module.