薛智文 cwhsueh@csie.ntu.tw csie.ntu.tw/~chsueh/ 96 Spring

1. Compiler TH 6 7 8, DTH 102 薛智文 cwhsueh@csie.ntu.edu.tw http://www.csie.ntu.edu.tw/~chsueh/ 96 Spring

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3. Why Study Compilers? • Excellent software-engineering example --- theory meets practice. • Essential software tool. • Influences hardware design, e.g., RISC, VLIW. • Tools (mostly “optimization”) for enhancing software reliability and security. /43

4. Compilers & Architecture • Modern architectures have very complex structures, especially opportunities for parallel execution. • Sequential programs can only make effective use of these features via an optimizing compiler. • Hardware question: If we implemented this, could a compiler use it? /43

5. Software Reliability • Optimization technology (data-flow analysis) used in: • Lock/unlock errors. • Buffers not range-checked. • Memory Leaks. • SQL injection bugs.. /43

6. What this Course Offers? • Compiler methodology for both compiler implementation and related applications. • Theoretical framework. • Key algorithms. • Hands-on experience. • Nongoal: build a complete optimizing compiler. /43

7. Course Outline • Part 1 --- Introduction. • Part 2 --- Scanner. • Part 3 --- Parser. • Part 4 --- Syntax-Directed Translation. • Part 5 --- Symbol Table. • Part 6 --- Intermediate Code Generation. • Part 7 --- Run Time Storage Organization. • Part 8 --- Optimization. • Part 9 --- How to Write a Compiler. • Part 10 --- A Simple Code Generation (PSEUDO) Example. /43

8. Introduction source program Compiler target program input output • Compiler is one of language processors. /43

9. What is a Compiler? source program Compiler target program input output • Definitions: • The software system translatesdescription of computations into a program executable by a computer. • Source and target must be equivalent! • Compiler writing spans: • programming languages; • machine architecture; • language theory; • algorithms and data structures; • software engineering. • History: • 1950: the first FORTRAN compiler took 18 man-years; • now: using software tools, can be done in a few months as a student’s project. /43

10. An Interpreter Interpreter source program output input /43

11. A Hybrid Compiler source program Translator intermediate program Virtual Machine output input /43

12. A Language-Processing System Preprocessor Compiler Assembler Linker/Loader modified source program target assembly program relocatable machine code target machine code source program library files relocatable object files /43

13. Applications 3 + 5 – 6 * 6 3 5 + 6 6 * – • Computer language compilers. • Translator: from one format to another. • query interpreter • text formatter • silicon compiler • infix notation  postfix notation: • pretty printers • · · · • Software productivity tools. /43

14. Relations with Computational Theory • Computational theory: • a set of grammar rules ≡ the definition of a particular machine. • also equivalent to a set of languages recognized by this machine. • a type of machines: a family of machines with a given set of operations, or capabilities; • power of a type of machines ≡ the set of languages that can be recognized by this type of machines. /43

15. A Language-Processing System Preprocessor Compiler Assembler Linker/Loader modified source program target assembly program relocatable machine code target machine code source program library files relocatable object files /43

16. Phases of a Compiler character stream Lexical Analyzer (scanner) tokenstream Syntax Analyzer (parser) abstract-syntax tree Semantic Analyzer annotated abstract-syntax tree Intermediate Code Generator intermediaterepresentation Machine-Independent Code Optimizer optimizedintermediaterepresentation Code Generator relocatablemachinecode Machine-Dependent Code Optimizer target-machinecode Error Handling Symbol Table /43

17. Lexical Analyzer (Scanner) • Actions: • Reads characters from the source program; • Groups characters into lexemes , i.e., sequences of characters that “go together”, following a given pattern ; • Each lexeme corresponds to a token . • the scanner returns the next token, plus maybe some additional information, to the parser; • The scanner may also discover lexical errors, i.e., erroneous characters. • The definitions of what a lexeme, token or badcharacter is depend on the definition of the source language. /43

18. Scanner Example for C Symbol Table • Lexeme: C statement position = initial + rate＊ 60; (Lexeme) position = initial + rate＊ 60 ; < id,1> <=> <id,2> <+> <id,3> <＊> <60> <;> (Token) ID ASSIGN ID PLUS ID TIME INT SEMI-COL • Arbitrary number of blanks (white spaces) between lexemes. • Erroneous sequence of characters, that are not parts of comments, for the C language: • control characters • @ • 2abc /43

19. Syntax Analyzer (Parser) • Actions: • Group tokens into grammatical phrases , to discover the underlying structure of the source • Find syntax errors , e.g., the following C source line: (Lexeme) index = 12 * ; (Token) ID ASSIGN INT TIMES SEMI-COL Every token is legal, but the sequence is erroneous! • May find some static semantic errors , e.g., use of undeclared variables or multiple declared variables. • May generate code, or build some intermediate representation of the source program, such as an abstract-syntax tree. /43

20. Parser Example for C = + < id,1> ＊ <id,2> <id,3> 60 • Source code: position = initial + rate＊ 60 < id,1> <=> <id,2> <+> <id,3> <＊> <60> • Abstract-syntax tree: • interior nodes of the tree are OPERATORS; • a node’s children are its OPERANDS; • each subtree forms a logical unit . • the subtree with ＊ at its root shows that ＊ has higher precedence than +, the operation “rate ＊ 60” must be performed as a unit, not “initial + rate”. • Where is ”;”? Symbol Table /43

21. Semantic Analyzer = + < id,1> = ＊ <id,2> + < id,1> <id,3> 60 ＊ <id,2> <id,3> int_to_float 60 • Actions: • Check for more static semantic errors, e.g., type errors . • May annotate and/or change the abstract syntax tree. Symbol Table /43

22. Intermediate Code Generator = + < id,1> ＊ <id,2> <id,3> int_to_float 60 • Actions: translate from abstract-syntax trees to intermediate codes. • One choice for intermediate code is 3-address code : • Each statement contains • at most 3 operands; • in addition to “=”, i.e., assignment, at most one operator. • An ”easy” and “universal” format that can be translated into most assembly languages. t1 = int_to_float(60) t2 = id3＊ t1 t3 = id2 + t2 id1 = t3 /43

23. Optimizer • Improve the efficiency of intermediate code. • Goal may be to make code run faster , and/or to use the least number of registers · · · • Current trends: • to obtain smaller, but maybe slower, equivalent code for embedded systems; • to reduce power consumption. t1 = int_to_float(60) t2 = id3＊ t1 t3 = id2 + t2 id1 = t3 t1 = id3＊ 60.0 id1 = id2 + t1 /43

24. Code Generation • A compiler may generate • pure machine codes (machine dependent assembly language) directly, which is rare now ; • virtual machine code. • Example: • PASCAL  compiler P-code interpreter execution • Speed is roughly 4 times slower than running directly generated machine codes. • Advantages: • simplify the job of a compiler; • decrease the size of the generated code: 1/3 for P-code ; • can be run easily on a variety of platforms • P-machine is an ideal general machine whose interpreter can be written easily; • divide and conquer; • recent example: JAVA and Byte-code. /43

25. Code Generation Example LDF R2, id3 MULF R2, R2, #60.0 LDF R1, id2 ADDF R1, R1, R2 STF id1, R1 t1 = id3＊ 60.0 id1 = id2 + t1 /43

26. Practical Considerations (1/2) • Preprocessing phase: • macro substitution: • #define MAXC 10 • rational preprocessing: add new features for old languages. • BASIC • C  C ++ • compiler directives: • #include <stdio.h> • non-standard language extensions. • adding parallel primitives /43

27. Practical Considerations (2/2) • Passes of compiling • First pass reads the text file once. • May need to read the text one more time for any forward addressed objects, i.e., anything that is used before its declaration. • Example: C language goto error_handling; · · · error_handling: · · · /43

28. Reduce Number of Passes • Each pass takes I/O time. • Back-patching : leave a blank slot for missing information, and fill in the empty slot when the information becomes available. • Example: C language when a label is used • if it is not defined before, save a trace into the to-be-processed table • label name corresponds to LABEL TABLE[i] • code generated: GOTO LABEL TABLE[i] when a label is defined • check known labels for redefined labels • if it is not used before, save a trace into the to-be-processed table • if it is used before, then find its trace and fill the current address into the trace • Time and space trade-off ! /43