Declarative Program Engine for Static Analysis

The patent segments the complex static analysis process into multiple distinct modules including a parser module that converts declarative program code into an abstract syntax tree, an analysis module that processes the AST, and a code generation module that produces executable analysis code. This modular segmentation reduces overall system complexity by breaking down the monolithic analysis process into manageable, independently configurable components that can be executed in stages

The patent introduces an abstract syntax tree (AST) as an intermediary representation between the declarative program code and the analysis logic. The AST serves as a standardized intermediate format that decouples the input program representation from the analysis algorithms, allowing complex analyses to be performed on a simplified, structured representation rather than directly on the original complex source code

The patent performs preliminary actions by pre-compiling declarative analysis programs into executable code before actual analysis execution. The system includes a code generation module that translates high-level declarative specifications into optimized imperative code, and a caching mechanism that stores pre-compiled analysis modules. This preliminary compilation transforms concise but slow declarative programs into high-performance executable code, maintaining ease of expression while dramatically improving runtime performance for large-scale programs

The patent changes the execution parameter of the analysis system by implementing a hybrid execution model that can switch between interpreting declarative programs directly and executing pre-compiled imperative code. The system dynamically selects the appropriate execution mode based on program size and analysis type, allowing it to maintain the simplicity of declarative expression for small programs while achieving imperative-level performance for large-scale analyses through parameter-driven execution strategy selection