©SoftMoore ConsultingSlide 1 Teaching Compiler Design.

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Presentation transcript:

©SoftMoore ConsultingSlide 1 Teaching Compiler Design

Compiler Course for Undergraduates A complete study of compilers could easily fill several graduate-level courses. Simplifications and compromises are necessary for a one-semester course that is accessible to undergraduate students. –Narrow focus a project-oriented course the “fun” part of studying compilers –Relatively simple source language but powerful enough to be interesting and challenging –Target is virtual machine with stack-based architecture simplifies code generation eliminates having to deal with general-purpose registers ©SoftMoore ConsultingSlide 2

Decisions, Decisions, Decisions Target Audience? –undergraduate students? –graduate students? –compiler professionals? This course: –advanced undergraduate students –also useful as basic introduction to graduate students Prerequisite? This course: –programming experience in both high-level and low-level languages –basic knowledge of algorithms and data structures (recursion, lists, stacks, hash tables, etc.) ©SoftMoore ConsultingSlide 3

Decisions, Decisions, Decisions (continued) Amount of Theory? –comprehensive versus minimal? This course: –minimal (must be able to understand and analyze context-free grammars) Tools? –scanner generators? –parser generators? –examples: Antlr, Coco/R, Flex/Bison, Lex/Yacc, JavaCC This course: –no tools other than compiler and IDE (e.g., Java and Eclipse) ©SoftMoore ConsultingSlide 4

Decisions, Decisions, Decisions (continued) Approach to parsing (check program for valid syntax)? –top down versus bottom up (or both)? –hard-coded versus table driven (or both)? –number of lookahead tokens? This course: –hard-coded –recursive descent (top down) with one token lookahead Intermediate Representation(s)? –high-level versus low level (or both)? –target machine independent? This course: –abstract syntax trees (high-level, target machine independent) ©SoftMoore ConsultingSlide 5

Decisions, Decisions, Decisions (continued) Source Language? –real programming language (e.g., C++, Java, Python, etc.)? –subset of real programming language? –simple language designed for teaching basics of compiler design This course: –simple language designed for teaching basics of compiler design –CPRL (Compiler PRoject Language) Implementation Language (language used to write the compiler)? This course: –flexible, but Java is recommended. Slides, handouts, and skeletal code will use Java. ©SoftMoore ConsultingSlide 6

Decisions, Decisions, Decisions (continued) Target Language? –real machine versus virtual machine (e.g., JVM) –machine code versus assembly language This course: –assembly language (simplifies code generation) –virtual machine (similar to JVM but simpler) ©SoftMoore ConsultingSlide 7

A Quote on LL(1) Recursive Descent Parsers “This pattern shows how to implement parsing decisions that use a single token of lookahead. It’s the weakest form of recursive-descent parser, but the easiest to understand and implement. If you can conveniently implement your language with this LL(1) pattern you should do so.” – Terence Parr ©SoftMoore ConsultingSlide 8

Course Project Implementation of a compiler for a small programming language Simple source language (CPRL) Simple target language (assembly language for CPRLVM, a simple stack-based virtual machine) Build a compiler one step at a time. Lots of template Java code to guide you though the process ©SoftMoore ConsultingSlide 9

Challenging Project Variations (for ambitious undergraduates or graduate students) Add one or more new features to the language –enum types –records/structures or classes –pointers and dynamic memory allocation (heap) –predefined environment with builtin procedures/functions (make Boolean a predefined enum type) Modify target language/machine –real machine, or assembly language for a real machine (e.g., Intel x86) –JVM or assembly language for JVM –Common Language Runtime (part of Microsoft’s.NET Framework) –C programming language (e.g., first C++ “compilers”) ©SoftMoore ConsultingSlide 10

Challenging Project Variations (continued) Implement the project in a language other than Java (e.g., Python or C#) Implement constraint analysis and code generation using the visitor design pattern Redesign code generation to allow for multiple targets –use a universal, machine-independent back end (e.g., LLVM) –use design patterns to create a code-generation factory ©SoftMoore ConsultingSlide 11