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Enhancing Compiler Design with Attribute Grammars and Symbolic Interpretation Techniques

This lecture explores attribute grammars and evaluators, which provide a foundational framework for integrating context into programming languages. Despite their potential, the technology surrounding these methods is underdeveloped and challenging to implement. We delve into manual methods like symbolic interpretation and data-flow equations to compute attributes and manage control flow. The session further covers the transition from abstract syntax trees (AST) to intermediate code generation, along with stack and register machine implementations, addressing how to optimize code execution in compilers.

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Enhancing Compiler Design with Attribute Grammars and Symbolic Interpretation Techniques

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  1. COP 4620 / 5625Programming Language Translation /Compiler WritingFall 2003Lecture 10, 10/30/2003 Prof. Roy Levow

  2. Attribute Grammars:Manual Methods • Attribute grammars and evaluators provide a useful framework for providing context to a program • But the technology is not yet well developed • And it can be difficult to use • Thus, manual methods are frequently used

  3. Manual Methods.2 • Symbolic Interpretation • Uses interpreter approach on AST to compute attributes • Data-flow Equations • More general technique based on set equations to reveal relationships among attributes

  4. Symbolic Interpretation • Control flow graph can be constructed by threading nodes of AST • Possibly adding nodes for simplicity • A threading rule is provided for each kind of node • Then simulate run-time behavior of program • Requires wide compiler

  5. Flow Control & Threading

  6. Flow Control & Threading.2

  7. Flow Control & Threading.3

  8. Flow Control & Threading.4

  9. Symbolic Interpretation • Attach a stack representation to each arrow in the control flow graph indicating the items that might be on the stack at that time in program execution with relevant attributes • Cal also identify features such as uninitialized variables

  10. Stack Representation of If

  11. Symbolic Interpretation of If

  12. Data Flow Equations • Data Flow Equations • Used on well-structured programs • Used to evaluate properties of data values across a program • Liveness (accessed later) • Initialized before use • Describe condition leaving block in terms of condition on entry and effects of block

  13. Data Flow Equations.2 • Example • Can be used to check for uninitialized variables • Solve by setting conditions for entry to initial block and compute closure

  14. Intermediate Code • Intermediate Code is usually tree structured like the AST • But may be linear or have other forms • Intermediate Code features • Expressions, including assignment • Routine class, Procedure headings, Returns • Conditional and unconditional jumps • Administrative activities

  15. Intermediate Code.2 • Assume wide compiler • Traverse AST replacing language context structures with intermediate code instructions • Produce is Intermediate Code Tree but is often still referred to as AST (Skipping 4.1 on Interpretation)

  16. Code Generation • Can be viewed as tree rewriting • In which tree branches are replaced by linear code • Working through threaded AST

  17. Simple Code GenerationStack Machine • Identify code for each node • Replace node with corresponding code • Emit code in bottom-up order

  18. Example for Stack Machine

  19. Example for Stack Machine.2

  20. Example for Stack Machine.3

  21. Emit Code for Stack Machine

  22. Emitted Stack Machine Code Push_Local #b Push_Local #b Mult_Top2 Push_Cosnt 4 Push_Local #a Push_Local #c Mult_Top2 Mult_Top2 Subtr_Top2

  23. Execution Profile for Stack Machine

  24. Simple Code GenerationRegister Machine • Need to assign computational values to registers • Normally start with unlimited number of registers in intermediate code and then handle actual limitations • Follow machine architecture for one or both operands in registers • May specify target register for result or not

  25. Register Code for AST Nodes

  26. Register Code Generationwith Register Numbering

  27. Generated Register Code

  28. Register Code Generation • When the number of registers is limited and more are needed than are available • Spill values from registers to memory • See example with 2 registers on next slide

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