Regular Expression Optimizer for CPU Usage Reduction
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Solution Overview
Problem
Regular expressions are difficult to use effectively due to their complexity, leading to unintended results and high resource consumption, as users often misuse syntax, and existing management methods rely heavily on user experience, resulting in inefficient search operations.
Innovation Solution
A regular expression optimizer that intercepts and preprocesses user-supplied regular expressions, transforming them into more manageable forms, such as replacing greedy quantifiers with lazy or possessive ones, to reduce CPU usage and convert expensive regular expression searches into substring searches, thereby improving response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If regular expressions are used to search for patterns in text data, then search capability and pattern matching power are improved, but CPU usage and resource consumption increase significantly
Solution Approach 1:
The patent applies preliminary action by preprocessing regular expressions before execution to convert them into optimized forms. The system analyzes and transforms complex regular expressions into equivalent but more efficient patterns, performing the optimization work in advance before the actual search operation, thereby reducing the computational resources needed during execution.
Solution Approach 2:
The patent utilizes parameter changes by modifying the structure and characteristics of regular expressions. It transforms greedy quantifiers into lazy or possessive quantifiers, and converts complex regex patterns into simpler equivalent forms, changing the parameters of the search pattern to achieve better performance while maintaining the same matching results.
2Measurement precision
If complex regular expressions are used to improve search accuracy, then search precision is improved, but execution duration and resource consumption increase
Solution Approach 1:
The system performs preliminary optimization of regular expressions by analyzing their structure and transforming them into more efficient equivalents before execution. This preprocessing step maintains the precise matching capability while significantly reducing the time required for execution.
Solution Approach 2:
The patent extracts and eliminates redundant or unnecessary components from regular expressions. By removing unnecessary complexity and keeping only the essential pattern-matching logic, it achieves the same search precision with reduced execution time and resource consumption.
3Productivity
If users manually program complex regular expressions to improve search performance, then search capability is improved, but ease of operation decreases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically optimize regular expressions without requiring user intervention. The optimization engine autonomously analyzes, transforms, and improves search patterns, eliminating the need for users to manually program complex expressions while still achieving high search performance.
Solution Approach 2:
The system introduces an intermediary optimization layer between the user's simple search request and the actual search execution. This intermediary automatically handles the complexity of regular expression optimization, translating user-friendly search criteria into optimized patterns without requiring users to understand complex regex syntax.
4Adaptability or versatility
If greedy quantifiers are used in regular expressions, then matching coverage is improved, but CPU efficiency decreases
Solution Approach 1:
The patent applies parameter changes by transforming the quantifier type in regular expressions. It systematically converts greedy quantifiers into lazy or possessive quantifiers, changing the matching behavior parameters to achieve the same coverage with significantly improved CPU efficiency and reduced backtracking.
Data Source
AI summary
Systems, methods, and other embodiments associated with processing regular expressions are described. One example method includes analyzing a rule for a regular expression and deleting the regular expression.