Lecture #1, Jan. 9, 2007

1. Lecture #1, Jan. 9, 2007 • Course Mechanics • Text Book • Down-loading SML • Syllabus - Course Overview • Entrance Exam • Standard ML • This weeks assignment • Top to bottom example • Lexical issues • Parsing and syntax issues • Translation issues

2. Acknowledgements The material taught in this course was made possible by many people. Here is a partial list: • Andrew Tolmach • Nathan Linger • Harry Porter • Jinke Lee

3. Class Web Page • The CS321 class web page can be found at: • www.cs.pdx.edu/~sheard/course/Cs321 • Contents of the page • Course Syllabus • Link to the ML home page • Copies of the PowerPoint slides used in lectures • Copies of the assignments • Project Description • Copies of the SML code illustrated in the lectures • The web page will be updated after each lecture.

4. Today’s Assignments Reading • Engineering a Compiler • Available In the PSU bookstore • Chapter 1, pp 1-26 • There will be a 5 minute quiz on the reading Wednesday. Search • Find the class webpage 1 page programming Assignment • Due Wednesday, Jan 10, 2007. In Just 2 Days!! • Login to some SML system. See how the system operates. Type in solutions (in a file) to the programming problems (In Class exercises 1 and 2 in this handout), load them into SML. Get them running, and print them out then turn them in on Wednesday. What matters here is that you try out the SML system, not that you get them perfect.

5. Course Information • CS321 - Languages and Compiler Design • Time: Monday & Wednesday 18:00-19:50 pm • Place: PCAT 138 • Instructor: Tim Sheard • office: room 115, CS Dept, 4th Ave Building, Portland State Univ. • phone: 503-725-2410 (work) 503-649-7242 (home) • office hours: Before class in my office (5:00-5:50), or by Appt. • Assignments • Reading from text and handouts (quizzes on reading) • Daily, 1 page programming assignments • 3 part programming project • Grading: • midterm exam (25%) • 3 parts of project (30%) • Daily 1 page assignments and quizzes (15%) • Final exam (30 %)

6. Examinations • Entrance Exam. • Do you know your REs and CFGs? • Quizzes on Reading Material. • There is a possible quiz on every reading assignment • There will be a quiz on Wednesday! • Mid Term exam • Wed. Feb 14, 2007. Time: in class. • Final exam • Monday, Mar. 19, 2007. Time: 6:00-7:50.

7. Text Book • Text: Engineering a Compiler • Keith D. Cooper, and Linda Torczon • Other Reference Materials • Auxilliary Material • Elements of Functional Programming (SML book) by Chris Reade, Addison Wesley, ISBN 0-201-12915-9 • Using the SML/NJ System http://www.cs.cmu.edu/~petel/smlguide/smlnj.htm • Class Handouts • Each class, a copy of that day’s slides will be available as a handout. • I will post files that contain the example programs used in each lecture on the class web page www.cs.pdx.edu/~sheard/course/Cs321 • I will post Assignments there as well.

8. Labs • Whenever you learn a new language its great to have someone looking over your shoulder. • In this spirit I have scheduled some lab times where people can work on learning ML while I am there to help. • FAB INTEL Lab (FAB 55-17) downstairs by the Engineering and Technology Manangement’s departmental offices • Friday Jan. 12, 2007. 4:00 – 5:30 PM • Tueday Jan. 16, 2007 4:00 – 5:30 • Friday Jan. 19, 2005. 4:00 – 5:30 PM • Labs are not required, but attendance of at least one is highly recommended!

9. Installing SML • Software can be obtained at: • http://www.smlnj.org/ • I am using the most recent version 110.60 • but it displays the version 110.57 when it runs • Browse the “documentation and Literature” section of the SML web page. Find some resources that you can use. • SML also runs on the PSU linux and Intel labs • linux • usepkg sml • then logout, or start a new shell • type: sm • Intel • In a commnd window • p:\programs\smlnj\addpkg.cmd • then logout, or start a new command window • then just type: • N:\>sml

10. Entrance Exam • CS321 has some pretty serious prerequisites. • Write a regular expression for the set of strings that begins with an “a” which is followed by an arbitrary number of “b”s or “c”s, and is ended by a “d”. e.g. ad, abbbd, abcbcbcd, etc. 2. Transform your regular expression into a DFA 3. Write a context free grammar that recognizes the same set of strings as your RE 4 Transform your CFG into a CFG that is left-recursion free.

11. Academic Integrity Students are expected to be honest in their academic dealings. Dishonesty is dealt with severely. • Homework. Pass in only your own work. • Program assignments. Program independently. • Examinations. Notes and such, only as each instructor allows. OK to discuss how to solve problems with other students, but each student should write up, debug, and turn in his own solution.

12. Course Thesis • This course is about programming languages. We study languages in two ways. • From the perspective of the user • From the perspective of the implementer (compiler writer) • We will learn about some languages you may never have heard of. We will learn to program in one of them (Standard ML). Its good to learn a new language in depth. • This course is also about programming. There will be extensive programming assignments in SML. If you don’t do them - you won’t learn • You’re deluding yourself if you think you can learn the material without doing the exercises! • We will write a comiler for a Java subset. Its good to understand the implementation details of a language you already know.

13. This course is all about programming • What makes a good program? • Write at least 3 things on a piece of paper.

14. Standard ML • In this course we will use an implementation of the language Standard ML • The SML/NJ Homepage has lots of useful information: http://www.smlnj.org// • You can get a version to install on your own machine there. I will use the version 110.57 or 110.60 of SML. Earlier versions probably will work as well. I don’t foresee any problems with other versions, but if you want to use the identical version that I use in class then this is the one.

15. Characteristics of SML • Applicative style • input output description of problem. • First class functions • pass as parameters • return as value of a function • store in data-structures • Less Importantly: • Automatic memory management (G.C. no new or malloc) • Use of a strong type system which uses type inference, i.e. no declarations but still strongly typed.

16. Syntactic Elements • Identifiers start with a letter followed by digits or other letters or primes or underscores. • Valid Examples: a a3 a’b aF • Invalid Examples: 12A • Identifiers can also be constructed with a sequence of operators like: !@#$%^&*+~ • Reserved words include • fun val datatype if then else • if of let in end type

17. Interacting • The normal style for interaction is to start SML, and then type definitions into the window. • Types of commands • 4 + 5; • val x = 34; • fun f x = x + 1; • Here are two commands you might find useful. val pwd = OS.FileSys.getDir; val cd = OS.FileSys.chDir; • To load a file that has a sml program type Use “file.sml”;

18. The SML Read-Typecheck-Eval-Print Loop • Standard ML of New Jersey v110.57 [built: Mon Nov 21 21:46:28 2005] • - • - 3+5; • val it = 8 : int • - • - print "Hi there\n"; • Hi there • val it = () : unit • - • - val x = 22; • val x = 22 : int • - • - x+ 5; • val it = 27 : int • - • val pwd = OS.FileSys.getDir; • val pwd = fn : unit -> string • - val cd = OS.FileSys.chDir; • val cd = fn : string -> unit • - Note the semicolon when you’re ready to evaluate. Otherwise commands can spread across several lines.

19. In Class Exercise 1 • Define prefix and lastone in terms of head tail and reverse. • First make a file “S01code.sml” • Start sml • Change directory to where the file resides • Load the file ( use “S01code.html” ) • Test the function fun lastone x = hd (rev x) fun prefix x = rev (tl (rev x)) Standard ML of New Jersey v110.57 - K; - val cd = OS.FileSys.chDir; val cd = fn : string -> unit - cd "D:/work/sheard/courses/PsuCs321/web/notes"; - use "S01code.html"; [opening S01code.html] val lastone = fn : 'a list -> 'a val prefix = fn : 'a list -> 'a list val it = () : unit - lastone [1,2,3,4]; val it = 4 : int

20. In Class Exercise 2 • define map and filter functions • mymap f [1,2,3] = [f 1, f 2, f 3] • filter even [1,2,3,4,5] = [2,4] fun mymap f [] = [] | mymap f (x::xs) = (f x)::(mymap f xs); fun filter p [] = [] | filter p (x::xs) = if (p x) then x::(filter p xs) else (filter p xs); • Sample Session - mymap plusone [2,3,4] [3, 4, 5] - filter even [1,2,3,4,5,6] [2, 4, 6]

21. Course topics • Programming Language • Types of languages • Data types and languages • Types and languages • Compilers • Lexical analysis • Parsing • Translation to abstract syntax using modern parser generator technology. • Type checking • identifiers and symbol table organization, • Next Quarter in the second class of the sequence • Intermediate representations • Backend analysis • Transformations and optimizations for a number of different kinds of languages

22. Multi Pass Compilers • Passes • text • tokens • syntax trees • intermediate forms • (three address code, CPS code, etc) • assembly code • machine code • Each phase is from one form to another, OR from one form to the same form, which is often called a source to source transformation.

23. The Top to Bottom Example text: tokens: syntax tree: z = x + pi * 12.0 id(z) eql id(x) plus id(pi) times float(12.0) = Id(z) + Id(z) * Id(x) Id(pi) float(12.0)

24. Passes (cont) Three address code: temp1 := pi * 12.0 z := x * temp1 Assembly level code: ld r1,x ld r2,pi add r1,r2 ldi r2,12.0 mul r1,r2 st r1,z

25. Lexical Analysis • Produces Tokens and Deals with: • white space • comments • reserved word identification • symbol table interface • Tokens are the terminals of grammars. • Lexical analysis reads the whole program, character by character thus it needs to be efficient. This implies fancy buffering techniques etc. Modern lexical generators handle these problems so we will ignore them.

26. Tokens, Patterns & Lexemes • Many strings from the input may produce the same TOKEN i.e. identifiers, integers constants, floats • A PATTERN describes a rule which describes which strings are assigned to a token. • A LEXEME is the exact sequence of input characters matched by a PATTERN.

27. Examples • lexeme pattern token • x <alpha><alpha>* Id "x" • abc <alpha><alpha>* Id "abc" • 152 <digit>+ Constant(152) • then then ThenKeyword • Many lexemes map to the same token. e.g. “x” and “abc” . • Note, some lexemes might match many patterns. e.g. "then" above. Need to resolve ambiguity. • Since tokens are terminals, they must be "produced" by the lexical phase with synthesized attributes in place. (e.g. name of an identifier). e.g. id(“x”) and constant(152)

28. Syntax, Parse Trees & Grammars • Syntax (the physical layout of the program) • Grammars describe precisely the syntax of a language. Two kinds of grammars which compiler writers use a lot are: regular, and context free • Informal Definitions of: Regular: concatenation, union, star Context Free: only one symbol on the lhs of a production

29. Example Grammar Sentence ::= Subject Verb Object Subject ::= Proper-noun Object ::= Article Adjective Noun Verb ::= ate | saw | called Noun ::= cat | ball | dish Article ::= the | a Adjective ::= big | bad | pretty Proper-noun ::= tim | mary Start Symbol = Sentence Example sentence: tim ate the big ball

30. Recursive Grammar Examples Recursive Grammars describe infinite languages list ::= [ num morenum ] morenum ::= , num morenum | <empty> derives [ 2 ], [2,4], [2,4,6] ... Exp ::= id | Exp + Exp | Exp * Exp | ( Exp ) derives x, x+x, x+x+x, ...

31. Parse Trees • Each nonterminal on the lhs of a production "roots" a tree: Each node in a tree with all its immediate children is derived from a single production of the grammar • We desire a program which constructs a parse tree from a string. Such programs are different for every grammar, we some times use tools to construct such programs (yacc).

32. Syntax Directed Translations • A syntax directed translation traverses a syntax tree and builds a translation in the process. Considerations • Tree Traversal orders • Left to right? • right to left? • in-order, pre-order, or post-order • Where does the information about what to do in the traversal come from? • Attribute grammars • Inherited attributes • Synthesized attributes

33. Example Translation Process Translation as an abstract syntax to abstract syntax transformer We represent this as a grammar with “actions” { ... }. The action is performed when that production is reduced. Exp ::= Term terms terms ::= + Term { print "+" } term | <empty> Term ::= Factor factors factors ::= * Factor { print "*" } factors | <empty> Factor ::= id { print id.name } | ( Exp )

34. Semantics • How do we know what to translate the syntax tree into? • How do we know if it is correct? • Semantics • denotational semantics • operational semantics • interpreters • Very useful in writing compilers since they give a reference when trying to decide what the compiler should do in particular cases.

35. Over view • Compilation is a large process • It is often broken into stages • The theories of computer science guide us in writing programs at each stage. • We must understand what a program “means” if we are to translate it correctly. • Many phases of the compiler try and optimize by translating one form into a better (more efficient?) form. • Most of compiling is about “pattern matching” languages and tools that support pattern matching are very useful.