Script Canonical Form Graphs for Semantic Comparison
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Solution Overview
Problem
Existing methods for comparing computer scripts are limited in determining semantic similarities, as they rely on syntactical comparisons that fail to identify scripts performing the same function despite subtle differences, leading to redundant scripts and increased development costs.
Innovation Solution
A computer script analysis system generates script canonical form (SCF) representations, which are stored in a database, allowing for semantic comparison and similarity scoring, as well as searching based on script metadata conditions, thereby reducing duplication and improving development efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If syntactical comparison methods are used to compare computer scripts, then the comparison process is simple and fast, but the ability to identify semantically identical scripts is poor, leading to redundant scripts
Solution Approach 1:
The patent segments scripts into functional units and represents them as graphs where nodes represent operations and edges represent data flow. This segmentation enables semantic comparison by breaking down complex scripts into comparable atomic elements, resolving the contradiction between detection accuracy and system complexity.
Solution Approach 2:
The patent introduces an intermediary representation layer (script graphs with canonical forms) between the original scripts and the comparison process. This intermediary structure enables semantic equivalence detection while maintaining manageable system complexity by providing a standardized comparison interface.
2Reliability
If syntactical comparison is used, then the comparison method is easy to implement, but subtle differences such as whitespace and comments cause scripts to be incorrectly identified as different
Solution Approach 1:
The patent extracts and removes non-functional elements such as whitespace and comments during the graph generation process. This extraction ensures that scripts are compared based on their functional content only, improving reliability while keeping the implementation straightforward by filtering out noise during preprocessing.
Solution Approach 2:
The patent changes the parameter representation from exact syntactical matching to semantic equivalence based on graph structure. By transforming scripts into canonical graph forms where only functional elements matter, the system achieves reliable equivalence determination while maintaining ease of implementation through standardized transformation rules.
3Productivity
If semantic comparison methods are implemented to accurately identify script functionality, then script duplication is reduced, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary transformation of scripts into canonical graph forms and pre-computes their representations. This preliminary action enables faster subsequent comparisons by having the comparison-ready structure prepared in advance, thus improving productivity while minimizing additional processing time during actual comparison operations.
Data Source
AI summary
The present disclosure relates generally to analyzing and comparing computer scripts, and more specifically, to determining semantic similarities between syntactically different scripts. An example computing system includes a memory configured to store a database, wherein the database is configured to store script canonical form (SCF) representations of scripts, and wherein each SCF representation is a topologically-sorted, labeled, directed graph that includes tables and datasets as nodes, actions as edges, and predicates as labels. The system includes a processor configured to execute instructions stored in the memory to cause the computing system to perform actions including: generating a first SCF representation of a first script, and storing the first SCF representation of the first script in the database.