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Introduction
Dr. Liam O’Connor
University of Edinburgh LFCS UNSW, Term 3 2020
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Who are we?
I am Liam O’Connor, a lecturer at the University of Edinburgh, and former convenor of this course. I am pre-recording the first 5 weeks of lectures for this iteration, to ensure a smooth hand-over to..
Dr. Christine Rizkallah, who is the new lecturer in charge. She is a lecturer at UNSW who works on, among other things, trustworthy systems and formal methods projects with data61.
Vivian Dang and Matthew di Meglio are the tutors for this year. Vivian works with Christine on security type systems, and Matthew will be imminently starting his PhD at Edinburgh.
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Contacting Us
http://www.cse.unsw.edu.au/~cs3161
Forum
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There is a Piazza forum available on the website. Questions about course content should typically be made there. You can ask us private questions to avoid spoiling solutions to other students.
I highly recommend disabling the Piazza Careers rubbish.
Administrative questions should be sent to cs3161@cse.unsw.edu.au.
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What do we expect?
Maths
This course uses a significant amount of discrete mathematics. You will need to be reasonably comfortable with logic, set theory and induction. MATH1081 is neither necessary nor sufficient for aptitude in these skills.
Programming
We expect you to be familiar with C and at least one other programming language. Course assignments 1 and 2 are in Haskell. Only very simple Haskell is required, but some self-study may be needed.
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Assessment
Assignment 0 Assignment 1 Assignment 2 Final Exam
15% 17.5% 17.5% 50%
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Start this week on Thursday and Friday.
You may change tutorials, just seek approval first. Please attempt some of the questions beforehand.
Tutorials
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Assignment 0
Focuses on theory and proofs.
It will be released in Week 3 and due in Week 4.
Aim to have marks back by census date (not guaranteed).
10% penalty for one day late, 25% for two, 50% for three and 100% for four+.
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Assignments
Given a formal specification, implement in Haskell.
Released around Week 5 and Week 8
Approximately 2 weeks to complete each assignment.
10% penalty for one day late, 25% for two, 50% for three and 100% for four+.
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Lectures
My lectures (Weeks 1-5) will be pre-recorded, Christine’s delivered through Blackboard Collaborate in the lecture time slot.
We may use the lecture time slot for consultations in Weeks 1-5. All board-work will be done digitally and made available to you. Separate lecture notes are also published.
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Books
There is no textbook for this course. Regular written lecture notes are made available throughout the semester, along with challenge exercises.
Much of the course material is covered in these two excellent books, however their explanations may differ and the usual disclaimers apply — this course does not follow these books exactly:
Types and Programming Languages by Benjamin Pierce, MIT Press. https://www.cis.upenn.edu/~bcpierce/tapl/
Practical Foundations for Programming Languages by Bob Harper, Cambridge University Press. http://www.cs.cmu.edu/~rwh/pfpl.html
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Course Content
This is a programming language appreciation course. This means we focus on the three R’s of computer science, giving you the skills to:
Read and understand new programming languages; Write your own programming languages; and
Reason about programming languages in a rigorous way.
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Why Read?
The choice of programming language affects nearly every aspect of a system: Design
Development Costs and Productivity Safety and Security
Performance
The Obvious
Learning to read and understand new programming languages is a vital skill in any computing discipline.
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Why Write?
You may not implement a general-purpose programming language like C or Haskell in your career.
However..
Every company has its own hand-rolled domain-specific language for accomplishing some task, often embedded in another language in a very ad-hoc and ugly way.
Example
XSLT, Perl scripts for processing text files, CSE’s give system, etc.
Learn how to make a PL properly and save yourself and your colleagues from headaches.
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Why Reason?
Programming languages are formal languages. Formal specification and proof allows us to:
Design languages better, avoiding undefined behaviour and other goblins. Make languages easier to process and parse. COMP3131
Give a mathematical meaning to programs, allowing for formal verification of programs. COMP4161, COMP2111, COMP6721
Develop algorithms to find bugs automatically. COMP3153
Rigorously analyse optimisations and other program transformations.
These tools are also very important for the pursuit of research in programming languages.
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Programmer
Source Language
Bridging the Gap
Computers can’t typically execute source code directly.
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Computer
Machine Code
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Programmer
Source Language
Bridging the Gap
A compiler translates from source code to a target language, typically machine code.
Example: C, C++, Haskell, Rust
Compiler
Computer
Machine Code
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Programmer
Source Language
Bridging the Gap
An interpreter executes a program as it reads the source code.
Examples: Perl, Python, JavaScript JIT compilers complicate this picture somewhat.
Interpreter
Computer
Machine Code
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Programmer
Source Language
Bridging the Gap
Some languages make use of a hybrid approach. First trans- lating the source language to an intermediate language (ab- stract or virtual machine), then interpreting that.
Examples: Java, C#
Compiler
Interpreter
Computer
Machine Code
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Stages of a Compiler
The first stage of a compiler is called a lexer, which, given an input string of source code, produces a stream of tokens or lexemes, discarding irrelevant information like whitespace or comments.
Example (C)
int foo () {
int i;
i = 11;
if (i > 5) {
i = i – 1;
return i; }
Ident “int” Ident “foo” lexer LParen RParen LBrace
=⇒
Ident “i”
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}
···
Ident “int” Ident “i” Semi
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Stages of a Compiler
A parser converts the stream of tokens from the lexer into a parse tree or abstract syntax tree:
Example (Arithmetic)
Lit 3 Times LParen Lit 2 Plus Lit 8 RParen
Times
Num 3 Plus
Num 2
Num 8
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Grammars
The structure of lexemes expected to produce certain parse trees is called a grammar.
Example (Informal grammar for C)
C function definitions consist of:
an identifier (return type), followed by
an identifier (function name), followed by
a possibly empty sequence of arguments, enclosed in parentheses, then a statement (function body)
Conclusions
This kind of definition is way too verbose and too imprecise to specify an implementation.
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Backus-Naur Form
Specify grammatical productions by using a bare-bones recursive notation. Non-terminals are in italics whereas terminals are in this typeface.
Example (C subset)
funDef ::= stmt ::=
stmts ::= expr ::=
Ident 1 Ident 2 ( args ) stmt
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locDec ::= args ::=
Ident1 Ident2 ; ε|···
expr ;|if(expr )stmt elsestmt
| return expr ; | { locDec stmts }
| while ( expr ) stmt
ε | stmt stmts
Number | Ident | expr 1 + expr 2 | Ident = expr | Ident ( expr )
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Program String
Lexer
Sequence of Tokens
Parser
Parse Tree
Semantic Analyser
Annotated Parse Tree
Code Generator
Machine Code
Optimiser
Intermediate Representation
Stages of a Compiler
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Program String
Lexer
Sequence of Tokens
Parser
Parse Tree
Semantic Analyser
Annotated Parse Tree
Code Generator
Machine Code
Stages of a Compiler
Semantic Analysis
Checks variable scoping
Static semantics checks: most
notably type checking.
Adds extra information to the
tree.
Optimiser
Intermediate Representation
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Program String
Lexer
Sequence of Tokens
Parser
Parse Tree
Semantic Analyser
Annotated Parse Tree
Code Generator
Machine Code
Stages of a Compiler
Optimisation
Loop unrolling, loop fusion Inlining, specialisation
Sometimes transforms the tree dramatically.
Optimiser
Intermediate Representation
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Program String
Lexer
Sequence of Tokens
Parser
Parse Tree
Semantic Analyser
Annotated Parse Tree
Code Generator
Machine Code
Stages of a Compiler
Code Generation
Register allocation and explicit control flow.
Links runtime system (e.g. GC)
Selects appropriate machine instructions
Optimiser
Intermediate Representation
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