Variable Range Visualization for Memory Allocation Optimization
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Solution Overview
Problem
Determining and presenting data type information for variables across multiple variables in code is challenging, especially for unnamed variables and temporary expressions, as existing techniques struggle to efficiently allocate memory based on the actual range of values used.
Innovation Solution
A visualization system is developed that allows users to interactively analyze code by generating histograms representing the range of values for each variable, using simulation and static analysis to determine significant digits, and providing interfaces to modify data types and allocate memory efficiently based on actual usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing techniques are used to determine data type information, then code analysis can be performed, but memory allocation cannot be efficiently optimized based on actual value ranges
Solution Approach 1:
The system performs preliminary simulation execution of code before final memory allocation decisions. By running code with different data types and observing actual value ranges, the system proactively determines optimal data type assignments rather than relying on static analysis alone, enabling efficient memory allocation based on real runtime behavior
Solution Approach 2:
The visualization system provides feedback by displaying histograms of actual value ranges for each variable. Users can observe the distribution of values and use this information to make informed decisions about memory allocation, creating a feedback loop between code execution and optimization decisions
2Loss of information
If detailed analysis of unnamed variables and temporary expressions is performed, then complete data type information can be obtained, but the complexity of analysis increases
Solution Approach 1:
The system segments the code into manageable units (functions, loops, conditionals) and analyzes each separately. By breaking down complex code structures into smaller analyzable segments, the system can handle unnamed variables and temporary expressions without overwhelming complexity, processing each segment through the visualization interface
Solution Approach 2:
The visualization interface acts as an intermediary between the complex code analysis and the user. It translates complex analysis results into intuitive histograms and visual representations, making the information accessible without requiring users to directly engage with the underlying analysis complexity
3Productivity
If standard data types are used for all variables, then code simplicity is maintained, but memory utilization is suboptimal
Solution Approach 1:
The system enables dynamic adjustment of data types based on actual value ranges observed during execution. Rather than using fixed standard data types, the system allows flexible, adaptive data type selection that optimizes memory utilization while maintaining code readability through the visualization interface
Solution Approach 2:
The system changes the parameter of data type precision and allocation size based on the actual range of values each variable uses. By analyzing value distributions through histograms and adjusting data type parameters accordingly, the system optimizes memory utilization without significantly complicating code operation
Data Source
AI summary
A device, including one or more processors, may obtain program code, determine a group of variables based on the program code, execute the program code, determine values of the group of variables based on the executing of the program code, determine a dynamic range of a characteristic for each variable based on the values, generate a visualization that presents the dynamic range of the characteristic for the group of variables, and provide the visualization for display.