Automated Policy Complexity Analysis With Optimization Feedback
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Solution Overview
Problem
Existing code-based policies lack tools for identifying and optimizing runtime complexity, leading to performance issues without clear causes, as even simple-looking code can have high complexity, hindering efficient execution.
Innovation Solution
A runtime complexity tool that analyzes policy code through a user interface, calculating metrics such as time, size, and count complexity, and provides suggestions for optimization based on these metrics, distinguishing between variables that iterate and those that do not.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If code is written without runtime complexity analysis tools, then code can be authored simply, but performance and execution speed deteriorate due to undetected high complexity
Solution Approach 1:
The patent applies preliminary action by performing runtime complexity analysis before policy execution. The system statically analyzes policy code to calculate complexity metrics (time, space, count) and provides optimization suggestions before the policy is executed, allowing writers to fix complexity issues in advance without changing the ease of code authoring
Solution Approach 2:
The patent implements feedback by providing complexity metrics and optimization suggestions back to policy writers. The system analyzes the policy code, calculates complexity values, and returns actionable feedback including specific suggestions for improvement, enabling writers to refine their code while maintaining simple authoring processes
2Productivity
If runtime complexity analysis tools are implemented, then performance issues can be identified and optimized, but the complexity of the development process increases
Solution Approach 1:
The patent applies self-service by implementing automated complexity analysis that operates independently without requiring manual intervention. The system automatically parses policy code, traverses abstract syntax trees, calculates complexity metrics, and generates optimization suggestions without human involvement, thus improving execution speed without significantly increasing development process complexity
Solution Approach 2:
The patent replaces manual complexity analysis with an automated computational system. Instead of requiring policy writers to manually analyze and optimize their code (mechanical process), the system uses automated static analysis and algorithmic complexity calculation to perform the same function, reducing the perceived complexity in the development process
3Measurement precision
If complexity metrics are calculated for all variables, then accurate performance analysis is achieved, but the computational overhead and analysis time increase
Solution Approach 1:
The patent applies segmentation by dividing the complexity analysis into distinct categories: time complexity, space complexity, and count complexity. Each variable and expression is analyzed separately for each metric type, allowing the system to provide comprehensive and precise complexity measurements while organizing the analysis process efficiently to minimize overall analysis time
Data Source
AI summary
Some embodiments provide a method for identifying runtime complexity of a policy. The method receives, through a user interface (UI), a set of code defining a particular policy. For each variable in the particular policy, the method identifies a first occurrence of the variable in the particular policy to determine a number of values assigned to the variable. Variables determined to be assigned one value are separated from variables determined to be assigned more than one value. Based on the determinations for each variable, the method calculates a set of metrics that include at least time complexity, size complexity, and count complexity for the particular policy. The method then displays, through the UI, the calculated set of metrics along with a set of one or more suggestions for optimizing the particular policy based on the calculated set of metrics.