String Concatenation Optimization in Java Virtual Machines
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Solution Overview
Problem
Current string concatenation techniques in virtual machine environments, such as Java Virtual Machines, result in inefficient memory copying and performance degradation due to long chains of dependent calls and unnecessary buffer resizing, impacting system performance, especially in web applications.
Innovation Solution
A system and method that reduces memory copying by using a StringMaker structure with a fixed array for efficient string concatenation, automatically generating optimized code, collapsing concatenation chains into single function calls, and adapting to usage statistics to minimize allocations and bounds checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional buffer append methods are used for string concatenation, then the implementation is simple and flexible, but the system spends excessive CPU time copying buffer contents multiple times, degrading performance
Solution Approach 1:
The patent applies preliminary action by pre-calculating the total length of the concatenated string before allocation. The bytecode compiler analyzes the concatenation operation, determines the final string length in advance, and allocates exactly that much memory space. This eliminates the need for repeated buffer expansions and copying operations that occur in traditional append-based methods, directly resolving the performance issue while maintaining implementation simplicity through compiler-level optimization.
2Adaptability or versatility
If buffer size is doubled each time it is exhausted during concatenation, then the buffer can accommodate variable-length strings, but multiple memory copy operations are required, increasing CPU time consumption
Solution Approach 1:
The patent eliminates the need for adaptive buffer expansion by performing preliminary calculation of the total string length at compile time. The bytecode compiler analyzes the concatenation expression, sums the lengths of all component strings, and allocates the exact required memory space in advance. This prevents all subsequent buffer expansions and memory copy operations, reducing CPU time consumption while maintaining the ability to handle variable-length strings through static analysis.
3Ease of operation
If a chain of concatenation calls is used to build strings sequentially, then the code is easy to write and maintain, but each call depends on the previous call, creating a long dependency chain that reduces execution efficiency
Solution Approach 1:
The patent merges multiple sequential concatenation calls into a single optimized operation. The bytecode compiler combines the entire concatenation chain into one bytecode instruction that performs all concatenations in a single pass. This eliminates the sequential dependency chain where each call waits for the previous one to complete, reducing execution time while preserving the ease of writing and maintaining the original high-level concatenation code.
Solution Approach 2:
The compiler performs preliminary analysis of the concatenation chain to determine the total length and optimal execution strategy. By calculating the final string length and planning the entire concatenation sequence in advance, the compiler transforms the sequential dependent calls into a single efficient operation that executes without intermediate dependencies, directly addressing the execution time issue while keeping the source code simple and maintainable.
Data Source
AI summary
A system and method for efficient string concatenation in a virtual machine (VM), or other runtime environment, and particularly for use in a system that includes a Java Virtual Machine (JVM). An embodiment improves the performance of string concatenation significantly by analysing the string concatenation chains during bytecode compilation and replacing the dynamic string concatenation code with fixed size structures without bounds checks or locks. The resulting code is also more suitable for inlining.