Syntax Tree Refactoring for Legacy Code Performance Bottlenecks
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Solution Overview
Problem
Legacy software often contains inefficient and outdated code that is difficult to maintain and optimize, leading to poor performance and security vulnerabilities, due to outdated programming techniques, inefficient algorithms, and lack of compatibility with modern systems.
Innovation Solution
An automated profiling and refactoring (APR) system that includes an automated runtime performance profiler and a source code analysis tool to identify inefficient functions and code violations, providing automated refactoring options to improve readability and compatibility with modern systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual optimization and refactoring of legacy software is performed, then code quality and performance can be improved, but the process becomes expensive and time-consuming due to the large code base and need for original authors' expertise
Solution Approach 1:
The system enables self-service automated refactoring by using AI models to autonomously analyze legacy code, identify inefficiencies, generate refactoring options, and apply optimizations without requiring manual intervention from original authors or experts, thus resolving the contradiction between improving code quality and reducing refactoring time
Solution Approach 2:
The patent replaces the mechanical manual process of code review and refactoring with an automated AI-based system that uses machine learning models to perform code analysis, pattern recognition, and transformation, substituting human expertise with computational intelligence to achieve both high quality and efficiency
2Productivity
If automated profiling and refactoring is implemented, then refactoring efficiency can be improved, but the complexity of the system increases
Solution Approach 1:
The system is segmented into distinct functional modules including code analysis module, AI model module, refactoring option generation module, and code transformation module, allowing each component to be independently developed, tested, and maintained while working together to achieve automated refactoring at high efficiency
Solution Approach 2:
The patent introduces intermediate representations such as abstract syntax trees and intermediate code formats that serve as mediators between the analysis phase and transformation phase, enabling complex refactoring operations to be broken down into manageable steps while maintaining system manageability
Data Source
AI summary
Disclosed herein are embodiments of systems, methods, and products for modernizing and optimizing legacy software. A computing device may perform an automated runtime performance profiling process. The performance profiler may automatically profile the legacy software at runtime, monitor the memory usage and module activities of the legacy software, and pinpoint/identify a subset of inefficient functions in the legacy software that scale poorly or otherwise inefficient. The computing device may further perform a source code analysis and refactoring process. The computing device may parse the source code of the subset of inefficient functions and identify code violations within the source code. The computing device may provide one or more refactoring options to optimize the source code. Each refactoring option may comprise a change to the source code configured to correct the code violations. The computing device may refactor the source code based on a selected refactoring option.