Do Languages Matter? Lecture 1: Overview. Why Article. Do Languages Matter? Why choose C vs C++ vs Java vs Python...!

Size: px
Start display at page:

Download "Do Languages Matter? Lecture 1: Overview. Why Article. Do Languages Matter? Why choose C vs C++ vs Java vs Python...!"

Transcription

1 Do Languages Matter? Why choose C vs C++ vs Java vs Python... Lecture 1: Overview CSC 131 Fall, 2014 Kim Bruce What criteria to decide? Scenarios: - ios app - Android App - Web App - Mac App - Windows app - System software - Scientific App - Scripting Do Languages Matter? Why Article Impact on programming practice SIGPLAN Education Board documents Learn widely-applicable design & implementation techniques Creating new domain specific languages or virtual machines Learning new computational models and speeding language learning Choosing the right language

2 Provide Abstractions PL s & Software Development Data Abstractions: - Basic data types: ints, reals, bools, chars, pointers - Structured: arrays, structs (records), objects - Units: Support for ADT s, modules, packages Control Abstractions: - Basic: assignment, goto, sequencing - Structured: if...then...else, loops, functions - Parallel: concurrent tasks, threads, message-passing Development process: - requirements - specification - implementation - certification or validation - maintenance Evaluate languages based on goals Goals of Some older PL s PL Choice Languages & their goals: - BASIC - quick development of interactive programs - Pascal - instruction - C - low-level systems programming - FORTRAN, Matlab - number-crunching scientific What about large-scale programs? - Ada, Modula-2, object-oriented languages Languages designed to support specific software methodologies. Language affect way people think about programming process. Hard for people to change languages if requires different way of thinking about process.

3 Paradigms or whatever you want to call them History of PL s Not crisp boundaries - Procedural - Functional - Logic or Constraint-programming - Object-oriented Machine language Assembly language High-level language Single highly-trained programmer Teams of programmers History of PLs Course Goals ve C Scheme Objective C Self Javascript Newer: Scala, Dart, Rust, NewSpeak, Swift, Grace, Pyret Upon completion of course should be able to: - Quickly learn programming languages, & how to apply them to effectively solve programming problems. - Rigorously specify, analyze, & reason about the behavior of a software system using a formally defined model of the system s behavior. - Realize a precisely specified model by correctly implementing it as a program, set of program components, or a programming language.

4 Administrivia Administrivia Web page at - Text by Mitchell: being revised now If needed, get account at - account_request.php - Do it early Recommended: - CS 81, Computability and Logic For computability and parsing Homework - Generally due every week on Thursday night. Posted on Friday - All homework must be turned in electronically Prefer Tex ed, but can scan in if want to write up by hand... but must be legible On-Line Discussions Grace Will be on Piazza You will receive an invitation later this week. - Do not throw it away You can ask and answer questions on-line. - TA s and I will monitor and respond. New language designed for teaching novices - Under development at Pomona, Portland State, and Victoria University, Wellington, NZ - Several published papers, nearly complete implementations Goal: Integrate current ideas in programming languages into a simple, general-purpose language aimed at novices.

5 Why New Language for Novices? Existing Languages Woefully Out-of-date Most popular languages too complex & lowlevel. Complexity necessary for professionals, but... - Accidental complexity of language can overwhelm essential complexity. - Minimize language complexity so can focus on programming/design complexity. C (1972), C++ (1983), Python (1989), Java (1994) History of pedagogical languages: - Basic, Logo, Pascal -... but not recently# - Miniworlds different: Alice, Karel the Robot, Greenfoot Java Problems public static void main(string [] args) Primitives versus objects, == versus equals Flawed implementation of generics Static versus instance on variables & methods float versus double versus int versus long 19 >>> class aclass: """A simple example class""" val = 47 def f(self): return 'hello world' >>> x = aclass() >>> x.value = 17 >>> x.val 47 >>> x.f() 'hello world' Python Problems 20 disappearing self? uncaught typos no information hiding Fine for scripting, but not large-scale software development

6 What if we could have: Hello World in Grace: Low syntactic overhead of Python, but with information hiding consistent method declaration & use required variable declarations optional (& gradual) type-checking direct definition of objects first-class functions print "hello world" Objects def mysquare = object { var side := 10 Consistent method area { indenting is side * side required# But no method stretchby(n) { semicolons. side := side + n Defaults: #instance variables and constants are confidential (protected), methods are public# Annotations can override the defaults 23 Objects contain declarations definitions: - def x:number = 17 variables: - var y: String := hello methods: - method m(w:number,z:string) -> Done {... types: - type Point = {x -> Number y -> Number... Types are optional

7 Typed Objects type Square = { area -> Number stretchby(n:number) -> Done like Void def mysquare:square = object { var side:number := 10 method area -> Number { side * side method stretchby(n:number) -> Done { side := side + n 25 Classes Classes take parameters and generate objects class square.withside(s:number) -> Square { var side:number := s method area -> Number { side * side method stretchby(n:number) -> Done { side := side + n print "Created square with side {s" Type annotations can be omitted or included 26 Or Object w/factory Method def square = object { method withside(s:number) -> Square { object{ var side:number := s method area -> Number { side * side method stretchby(n:number)-> Done { side := side + n print "Created square with side {side" 27 What is type of square? Blocks Syntax for anonymous functions def double = {n -> n * n double.apply(7) // returns 49# // block is implicitly object w/apply method def nums = alist.from(1)to(100) def squares = nums.map {n -> n * n Blocks can take 0 or more parameters 28 function multipart method names

8 Blocks block, evaluated repeatedly Blocks make it simple to define new control structures as methods while {boolexp do { somestuff squares.foreach {n -> if (n.iseven) then {print n boolean expression, evaluated once Parentheses can be dropped if argument bounded by { or # No parens needed for parameterless methods Running Grace Compilers generating C or Javascript Use web-based editor/compiler at minigrace 29 Grace on the Web Go to: Click on New at top to start new program (& choose name) or click on Upload Build button under edit window will compile code. When changes to Run press to execute Error messages not great yet. Right-click (& Save link as ) to save. Avoid Hoare s Billion Dollar Mistake No built-in null Accessing uninitialized variable is error Replace null by: sentinel objects, or error actions 32

9 Sentinel Objects A real object, tailored for the situation, e.g.: def emptylist = object { method asstring {"<emptylist>" method do(action) { method map(function) {self method size {0 name for object # being defined Sentinel Objects Simplifies code, eliminates testing for null class alist.cons(value, taillist) { method asstring {"({head:{tail)" method head {value boolean method tail {taillist expression, no conditional evaluated code method do(action) { once action.apply(head) tail.do(action) method map(function) { alist.cons(function.apply(head), tail.map(function)) method size {1 + tail.size Error Actions Grace encourages the use of blocks to specify error actions or default values: var x := table.at(key)ifabsent{ return unknown(key) Pattern Matching Provides type-safe switch/case match(myval) case{ n: Number -> "The number {n seen" case{ s: String -> "The string "++s++" seen" case{ true: Boolean -> "This is true" 35 36

10 Variant Types def absent = object {... type OptionNumber = Number singleton(absent) var x: OptionNumber := table.lookup(key) match(x) case {x':number ->... x'... case {_ -> return unknown(key) Questions? val: A B iff val:a or val:b Allows elimination of null 37

Why a New Language? Seeking Grace: a New Object-Oriented Language for Novices. OO Teaching Frustrations. Java Problems. Java is 20 years old in 2015

Why a New Language? Seeking Grace: a New Object-Oriented Language for Novices. OO Teaching Frustrations. Java Problems. Java is 20 years old in 2015 Seeking Grace: a New Object-Oriented Language for Novices Andrew Black, Kim Bruce, Michael Homer, James Noble, Amy Ruskin, & Richard Yannow Why a New Language? Java is 20 years old in 2015 Showing its

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Winter 2017 Lecture 7b Andrew Tolmach Portland State University 1994-2017 Values and Types We divide the universe of values according to types A type is a set of values and

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Fall 2016 Lecture 7a Andrew Tolmach Portland State University 1994-2016 Values and Types We divide the universe of values according to types A type is a set of values and a

More information

More Examples. Lecture 24: More Scala. Higher-Order Functions. Control Structures

More Examples. Lecture 24: More Scala. Higher-Order Functions. Control Structures More Examples Lecture 24: More Scala CSC 131 Fall, 2014 Kim Bruce MyList, MyArrayList, SinglyLinkedList - Val vs var - Can create Array[T] (unlike Java), though need implicit ClassManifest - foreach(f)

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Fall 2017 Lecture 7b Andrew Tolmach Portland State University 1994-2017 Type Inference Some statically typed languages, like ML (and to a lesser extent Scala), offer alternative

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Winter 2018 Lecture 7b Andrew Tolmach Portland State University 1994-2018 Dynamic Type Checking Static type checking offers the great advantage of catching errors early And

More information

Programming Languages and Techniques (CIS120)

Programming Languages and Techniques (CIS120) Programming Languages and Techniques () Lecture 20 February 28, 2018 Transition to Java Announcements HW05: GUI programming Due: THURSDAY!! at 11:59:59pm Lots of TA office hours today Thursday See Piazza

More information

CS 11 java track: lecture 1

CS 11 java track: lecture 1 CS 11 java track: lecture 1 Administrivia need a CS cluster account http://www.cs.caltech.edu/ cgi-bin/sysadmin/account_request.cgi need to know UNIX www.its.caltech.edu/its/facilities/labsclusters/ unix/unixtutorial.shtml

More information

Where do we go from here?

Where do we go from here? Where do we go from here? C++ classes and objects, with all the moving parts visible operator overloading templates, STL, standards, Java components, collections, generics language and performance comparisons

More information

Semantic Analysis. How to Ensure Type-Safety. What Are Types? Static vs. Dynamic Typing. Type Checking. Last time: CS412/CS413

Semantic Analysis. How to Ensure Type-Safety. What Are Types? Static vs. Dynamic Typing. Type Checking. Last time: CS412/CS413 CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 13: Types and Type-Checking 19 Feb 07 Semantic Analysis Last time: Semantic errors related to scopes Symbol tables Name resolution This lecture:

More information

Closures. Mooly Sagiv. Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming

Closures. Mooly Sagiv. Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming Closures Mooly Sagiv Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming Summary 1. Predictive Parsing 2. Large Step Operational Semantics (Natural) 3. Small Step Operational Semantics

More information

Question No: 1 ( Marks: 1 ) - Please choose one One difference LISP and PROLOG is. AI Puzzle Game All f the given

Question No: 1 ( Marks: 1 ) - Please choose one One difference LISP and PROLOG is. AI Puzzle Game All f the given MUHAMMAD FAISAL MIT 4 th Semester Al-Barq Campus (VGJW01) Gujranwala faisalgrw123@gmail.com MEGA File Solved MCQ s For Final TERM EXAMS CS508- Modern Programming Languages Question No: 1 ( Marks: 1 ) -

More information

CS 565: Programming Languages. Spring 2008 Tu, Th: 16:30-17:45 Room LWSN 1106

CS 565: Programming Languages. Spring 2008 Tu, Th: 16:30-17:45 Room LWSN 1106 CS 565: Programming Languages Spring 2008 Tu, Th: 16:30-17:45 Room LWSN 1106 Administrivia Who am I? Course web page http://www.cs.purdue.edu/homes/peugster/cs565spring08/ Office hours By appointment Main

More information

Types. What is a type?

Types. What is a type? Types What is a type? Type checking Type conversion Aggregates: strings, arrays, structures Enumeration types Subtypes Types, CS314 Fall 01 BGRyder 1 What is a type? A set of values and the valid operations

More information

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 17: Types and Type-Checking 25 Feb 08

CS412/CS413. Introduction to Compilers Tim Teitelbaum. Lecture 17: Types and Type-Checking 25 Feb 08 CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 17: Types and Type-Checking 25 Feb 08 CS 412/413 Spring 2008 Introduction to Compilers 1 What Are Types? Types describe the values possibly

More information

Syntax Errors; Static Semantics

Syntax Errors; Static Semantics Dealing with Syntax Errors Syntax Errors; Static Semantics Lecture 14 (from notes by R. Bodik) One purpose of the parser is to filter out errors that show up in parsing Later stages should not have to

More information

22c:111 Programming Language Concepts. Fall Types I

22c:111 Programming Language Concepts. Fall Types I 22c:111 Programming Language Concepts Fall 2008 Types I Copyright 2007-08, The McGraw-Hill Company and Cesare Tinelli. These notes were originally developed by Allen Tucker, Robert Noonan and modified

More information

Semantic Analysis. Outline. The role of semantic analysis in a compiler. Scope. Types. Where we are. The Compiler Front-End

Semantic Analysis. Outline. The role of semantic analysis in a compiler. Scope. Types. Where we are. The Compiler Front-End Outline Semantic Analysis The role of semantic analysis in a compiler A laundry list of tasks Scope Static vs. Dynamic scoping Implementation: symbol tables Types Static analyses that detect type errors

More information

Organization of Programming Languages (CSE452) Why are there so many programming languages? What makes a language successful?

Organization of Programming Languages (CSE452) Why are there so many programming languages? What makes a language successful? Organization of Programming Languages (CSE452) Instructor: Dr. B. Cheng Fall 2004 1 Why are there so many programming languages? Evolution -- we've learned better ways of doing things over time Socio-economic

More information

Computer Components. Software{ User Programs. Operating System. Hardware

Computer Components. Software{ User Programs. Operating System. Hardware Computer Components Software{ User Programs Operating System Hardware What are Programs? Programs provide instructions for computers Similar to giving directions to a person who is trying to get from point

More information

CS 61C: Great Ideas in Computer Architecture. Lecture 2: Numbers & C Language. Krste Asanović & Randy Katz

CS 61C: Great Ideas in Computer Architecture. Lecture 2: Numbers & C Language. Krste Asanović & Randy Katz CS 61C: Great Ideas in Computer Architecture Lecture 2: Numbers & C Language Krste Asanović & Randy Katz http://inst.eecs.berkeley.edu/~cs61c Numbers wrap-up This is not on the exam! Break C Primer Administrivia,

More information

Two Types of Types. Primitive Types in Java. Using Primitive Variables. Class #07: Java Primitives. Integer types.

Two Types of Types. Primitive Types in Java. Using Primitive Variables. Class #07: Java Primitives. Integer types. Class #07: Java Primitives Software Design I (CS 120): M. Allen, 13 Sep. 2018 Two Types of Types So far, we have mainly been dealing with objects, like DrawingGizmo, Window, Triangle, that are: 1. Specified

More information

Agenda. CS 61C: Great Ideas in Computer Architecture. Lecture 2: Numbers & C Language 8/29/17. Recap: Binary Number Conversion

Agenda. CS 61C: Great Ideas in Computer Architecture. Lecture 2: Numbers & C Language 8/29/17. Recap: Binary Number Conversion CS 61C: Great Ideas in Computer Architecture Lecture 2: Numbers & C Language Krste Asanović & Randy Katz http://inst.eecs.berkeley.edu/~cs61c Numbers wrap-up This is not on the exam! Break C Primer Administrivia,

More information

The Compiler So Far. CSC 4181 Compiler Construction. Semantic Analysis. Beyond Syntax. Goals of a Semantic Analyzer.

The Compiler So Far. CSC 4181 Compiler Construction. Semantic Analysis. Beyond Syntax. Goals of a Semantic Analyzer. The Compiler So Far CSC 4181 Compiler Construction Scanner - Lexical analysis Detects inputs with illegal tokens e.g.: main 5 (); Parser - Syntactic analysis Detects inputs with ill-formed parse trees

More information

http://xkcd.com/224/ CS252 Programming Language Paradigms Prof. Tom Austin San José State University Fall 2014 What are some programming languages? Why are there so many? Different domains. Mobile devices

More information

CS/ENGRD 2110 FALL Lecture 2: Objects and classes in Java

CS/ENGRD 2110 FALL Lecture 2: Objects and classes in Java 1 CS/ENGRD 2110 FALL 2017 Lecture 2: Objects and classes in Java http://courses.cs.cornell.edu/cs2110 CMS VideoNote.com, PPT slides, DrJava 2 CMS. Visit course webpage, click Links, then CMS for 2110.

More information

Lecture 16: Static Semantics Overview 1

Lecture 16: Static Semantics Overview 1 Lecture 16: Static Semantics Overview 1 Lexical analysis Produces tokens Detects & eliminates illegal tokens Parsing Produces trees Detects & eliminates ill-formed parse trees Static semantic analysis

More information

Lecture 1: Course Introduction

Lecture 1: Course Introduction Lecture 1: Course Introduction CS164: Programming Languages and Compilers P. N. Hilfinger, 787 Soda Fall 2013 Acknowledgement. Portions taken from CS164 notes by G. Necula. Last modified: Thu Aug 29 16:03:34

More information

JavaScript: Introduction, Types

JavaScript: Introduction, Types JavaScript: Introduction, Types Computer Science and Engineering College of Engineering The Ohio State University Lecture 19 History Developed by Netscape "LiveScript", then renamed "JavaScript" Nothing

More information

CSc 372 Comparative Programming Languages

CSc 372 Comparative Programming Languages CSc 372 Comparative Programming Languages 1 : Introduction Christian Collberg collberg+372@gmail.com Department of Computer Science University of Arizona Copyright c 2007 Christian Collberg [1] Why learn

More information

Monty Python and the Holy Grail (1975) BBM 101. Introduction to Programming I. Lecture #03 Introduction to Python and Programming, Control Flow

Monty Python and the Holy Grail (1975) BBM 101. Introduction to Programming I. Lecture #03 Introduction to Python and Programming, Control Flow BBM 101 Monty Python and the Holy Grail (1975) Introduction to Programming I Lecture #03 Introduction to Python and Programming, Control Flow Aykut Erdem, Fuat Akal & Aydın Kaya // Fall 2018 Last time

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Fall 2016 Lecture 4a Andrew Tolmach Portland State University 1994-2016 Pragmatics of Large Values Real machines are very efficient at handling word-size chunks of data (e.g.

More information

CS558 Programming Languages

CS558 Programming Languages CS558 Programming Languages Fall 2016 Lecture 3a Andrew Tolmach Portland State University 1994-2016 Formal Semantics Goal: rigorous and unambiguous definition in terms of a wellunderstood formalism (e.g.

More information

Programming Languages: Lecture 11

Programming Languages: Lecture 11 1 Programming Languages: Lecture 11 Chapter 9: Subprograms Jinwoo Kim jwkim@jjay.cuny.edu Chapter 9 Topics 2 Introduction Fundamentals of Subprograms Design Issues for Subprograms Local Referencing Environments

More information

CS 314 Principles of Programming Languages

CS 314 Principles of Programming Languages CS 314 Principles of Programming Languages Lecture 15: Review and Functional Programming Zheng (Eddy) Zhang Rutgers University March 19, 2018 Class Information Midterm exam forum open in Sakai. HW4 and

More information

CSCI 2212: Intermediate Programming / C Review, Chapters 10 and 11

CSCI 2212: Intermediate Programming / C Review, Chapters 10 and 11 ... 1/16 CSCI 2212: Intermediate Programming / C Review, Chapters 10 and 11 Alice E. Fischer February 3, 2016 ... 2/16 Outline Basic Types and Diagrams ... 3/16 Basic Types and Diagrams Types in C C has

More information

http://xkcd.com/224/ CS 152: Programming Language Paradigms Prof. Tom Austin San José State University What are some programming languages? Taken from http://pypl.github.io/pypl.html January 2016 Why are

More information

SEMANTIC ANALYSIS TYPES AND DECLARATIONS

SEMANTIC ANALYSIS TYPES AND DECLARATIONS SEMANTIC ANALYSIS CS 403: Type Checking Stefan D. Bruda Winter 2015 Parsing only verifies that the program consists of tokens arranged in a syntactically valid combination now we move to check whether

More information

Closures. Mooly Sagiv. Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming

Closures. Mooly Sagiv. Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming Closures Mooly Sagiv Michael Clarkson, Cornell CS 3110 Data Structures and Functional Programming t ::= x x. t t t Call-by-value big-step Operational Semantics terms variable v ::= values abstraction x.

More information

Object-oriented programming. and data-structures CS/ENGRD 2110 SUMMER 2018

Object-oriented programming. and data-structures CS/ENGRD 2110 SUMMER 2018 Object-oriented programming 1 and data-structures CS/ENGRD 2110 SUMMER 2018 Lecture 1: Types and Control Flow http://courses.cs.cornell.edu/cs2110/2018su Lecture 1 Outline 2 Languages Overview Imperative

More information

The Pyth Language. Administrivia

The Pyth Language. Administrivia Administrivia The Pyth Language Lecture 5 Please make sure you have registered your team, created SSH keys as indicated on the admin page, and also have electronically registered with us as well. Prof.

More information

CS558 Programming Languages Winter 2018 Lecture 4a. Andrew Tolmach Portland State University

CS558 Programming Languages Winter 2018 Lecture 4a. Andrew Tolmach Portland State University CS558 Programming Languages Winter 2018 Lecture 4a Andrew Tolmach Portland State University 1994-2018 Pragmatics of Large Values Real machines are very efficient at handling word-size chunks of data (e.g.

More information

G Programming Languages Spring 2010 Lecture 4. Robert Grimm, New York University

G Programming Languages Spring 2010 Lecture 4. Robert Grimm, New York University G22.2110-001 Programming Languages Spring 2010 Lecture 4 Robert Grimm, New York University 1 Review Last week Control Structures Selection Loops 2 Outline Subprograms Calling Sequences Parameter Passing

More information

COS 140: Foundations of Computer Science

COS 140: Foundations of Computer Science COS 140: Foundations of Computer Science Variables and Primitive Data Types Fall 2017 Introduction 3 What is a variable?......................................................... 3 Variable attributes..........................................................

More information

CS61C Machine Structures. Lecture 3 Introduction to the C Programming Language. 1/23/2006 John Wawrzynek. www-inst.eecs.berkeley.

CS61C Machine Structures. Lecture 3 Introduction to the C Programming Language. 1/23/2006 John Wawrzynek. www-inst.eecs.berkeley. CS61C Machine Structures Lecture 3 Introduction to the C Programming Language 1/23/2006 John Wawrzynek (www.cs.berkeley.edu/~johnw) www-inst.eecs.berkeley.edu/~cs61c/ CS 61C L03 Introduction to C (1) Administrivia

More information

Final-Term Papers Solved MCQS with Reference

Final-Term Papers Solved MCQS with Reference Solved MCQ(S) From FinalTerm Papers BY Arslan Jan 14, 2018 V-U For Updated Files Visit Our Site : Www.VirtualUstaad.blogspot.com Updated. Final-Term Papers Solved MCQS with Reference 1. The syntax of PHP

More information

Static Semantics. Lecture 15. (Notes by P. N. Hilfinger and R. Bodik) 2/29/08 Prof. Hilfinger, CS164 Lecture 15 1

Static Semantics. Lecture 15. (Notes by P. N. Hilfinger and R. Bodik) 2/29/08 Prof. Hilfinger, CS164 Lecture 15 1 Static Semantics Lecture 15 (Notes by P. N. Hilfinger and R. Bodik) 2/29/08 Prof. Hilfinger, CS164 Lecture 15 1 Current Status Lexical analysis Produces tokens Detects & eliminates illegal tokens Parsing

More information

CS252 Advanced Programming Language Principles. Prof. Tom Austin San José State University Fall 2013

CS252 Advanced Programming Language Principles. Prof. Tom Austin San José State University Fall 2013 CS252 Advanced Programming Language Principles Prof. Tom Austin San José State University Fall 2013 What are some programming languages? Why are there so many? Different domains Mobile devices (Objective

More information

COSE212: Programming Languages. Lecture 3 Functional Programming in OCaml

COSE212: Programming Languages. Lecture 3 Functional Programming in OCaml COSE212: Programming Languages Lecture 3 Functional Programming in OCaml Hakjoo Oh 2017 Fall Hakjoo Oh COSE212 2017 Fall, Lecture 3 September 18, 2017 1 / 44 Why learn ML? Learning ML is a good way of

More information

General Concepts. Abstraction Computational Paradigms Implementation Application Domains Influence on Success Influences on Design

General Concepts. Abstraction Computational Paradigms Implementation Application Domains Influence on Success Influences on Design General Concepts Abstraction Computational Paradigms Implementation Application Domains Influence on Success Influences on Design 1 Abstractions in Programming Languages Abstractions hide details that

More information

BM214E Object Oriented Programming Lecture 4

BM214E Object Oriented Programming Lecture 4 BM214E Object Oriented Programming Lecture 4 Computer Numbers Integers (byte, short, int, long) whole numbers exact relatively limited in magnitude (~10 19 ) Floating Point (float, double) fractional often

More information

Lecture 1: Course Introduction

Lecture 1: Course Introduction Lecture 1: Course Introduction CS164: Programming Languages and Compilers P. N. Hilfinger, 787 Soda Spring 2015 Acknowledgement. Portions taken from CS164 notes by G. Necula. Last modified: Wed Jan 21

More information

SAMS Programming A/B. Lecture #1 Introductions July 3, Mark Stehlik

SAMS Programming A/B. Lecture #1 Introductions July 3, Mark Stehlik SAMS Programming A/B Lecture #1 Introductions July 3, 2017 Mark Stehlik Outline for Today Overview of Course A Python intro to be continued in lab on Wednesday (group A) and Thursday (group B) 7/3/2017

More information

CS 251 Intermediate Programming Methods and Classes

CS 251 Intermediate Programming Methods and Classes CS 251 Intermediate Programming Methods and Classes Brooke Chenoweth University of New Mexico Fall 2018 Methods An operation that can be performed on an object Has return type and parameters Method with

More information

CS61C : Machine Structures

CS61C : Machine Structures inst.eecs.berkeley.edu/~cs61c CS61C : Machine Structures Lecture 4 C Pointers 2004-09-08 Lecturer PSOE Dan Garcia www.cs.berkeley.edu/~ddgarcia Cal flies over Air Force We re ranked 13 th in the US and

More information

G Programming Languages Spring 2010 Lecture 6. Robert Grimm, New York University

G Programming Languages Spring 2010 Lecture 6. Robert Grimm, New York University G22.2110-001 Programming Languages Spring 2010 Lecture 6 Robert Grimm, New York University 1 Review Last week Function Languages Lambda Calculus SCHEME review 2 Outline Promises, promises, promises Types,

More information

CS 360: Programming Languages Lecture 12: More Haskell

CS 360: Programming Languages Lecture 12: More Haskell CS 360: Programming Languages Lecture 12: More Haskell Geoffrey Mainland Drexel University Adapted from Brent Yorgey s course Introduction to Haskell. Section 1 Administrivia Administrivia Homework 5 due

More information

What Is Computer Science? The Scientific Study of Computation. Expressing or Describing

What Is Computer Science? The Scientific Study of Computation. Expressing or Describing What Is Computer Science? The Scientific Study of Computation CMPSCI 630: Programming Languages Introduction Spring 2009 (with thanks to Robert Harper) Expressing or Describing Automating Understanding

More information

CS 231 Data Structures and Algorithms, Fall 2016

CS 231 Data Structures and Algorithms, Fall 2016 CS 231 Data Structures and Algorithms, Fall 2016 Dr. Bruce A. Maxwell Department of Computer Science Colby College Course Description Focuses on the common structures used to store data and the standard

More information

Ruby: Introduction, Basics

Ruby: Introduction, Basics Ruby: Introduction, Basics Computer Science and Engineering College of Engineering The Ohio State University Lecture 3 Ruby vs Java: Similarities Imperative and object-oriented Classes and instances (ie

More information

Programming Languages and Techniques (CIS120)

Programming Languages and Techniques (CIS120) Programming Languages and Techniques () Lecture 12 February 7, 2018 Partiality, Sequencing, Records Chapters 12, 13 Midterm 1 This Friday in class Review session Tonight, 6 7:30 PM DRLB A1 Announcements

More information

Organization of Programming Languages CS 3200/5200N. Lecture 09

Organization of Programming Languages CS 3200/5200N. Lecture 09 Organization of Programming Languages CS 3200/5200N Razvan C. Bunescu School of Electrical Engineering and Computer Science bunescu@ohio.edu Control Flow Control flow = the flow of control, or execution

More information

CS152 Programming Language Paradigms Prof. Tom Austin, Fall Syntax & Semantics, and Language Design Criteria

CS152 Programming Language Paradigms Prof. Tom Austin, Fall Syntax & Semantics, and Language Design Criteria CS152 Programming Language Paradigms Prof. Tom Austin, Fall 2014 Syntax & Semantics, and Language Design Criteria Lab 1 solution (in class) Formally defining a language When we define a language, we need

More information

So what does studying PL buy me?

So what does studying PL buy me? So what does studying PL buy me? Enables you to better choose the right language but isn t that decided by libraries, standards, and my boss? Yes. Chicken-and-egg. My goal: educate tomorrow s tech leaders

More information

Lecture 09. Ada to Software Engineering. Mr. Mubashir Ali Lecturer (Dept. of Computer Science)

Lecture 09. Ada to Software Engineering. Mr. Mubashir Ali Lecturer (Dept. of Computer Science) Lecture 09 Ada to Software Engineering Mr. Mubashir Ali Lecturer (Dept. of dr.mubashirali1@gmail.com 1 Summary of Previous Lecture 1. ALGOL 68 2. COBOL 60 3. PL/1 4. BASIC 5. Early Dynamic Languages 6.

More information

Compilers. Prerequisites

Compilers. Prerequisites Compilers Prerequisites Data structures & algorithms Linked lists, dictionaries, trees, hash tables Formal languages & automata Regular expressions, finite automata, context-free grammars Machine organization

More information

Functional Programming and Haskell

Functional Programming and Haskell Functional Programming and Haskell Tim Dawborn University of Sydney, Australia School of Information Technologies Tim Dawborn Functional Programming and Haskell 1/22 What are Programming Paradigms? A programming

More information

Review Chapter 6 in Bravaco. Short Answers 1. This type of method does not return a value. a. null b. void c. empty d. anonymous

Review Chapter 6 in Bravaco. Short Answers 1. This type of method does not return a value. a. null b. void c. empty d. anonymous Assignment 3 Methods Review CSC 123 Fall 2018 Notes: All homework must be submitted via e-mail. All parts of assignment must be submitted in a single e-mail with multiple attachments when required. Notes:

More information

Programming in C. What is C?... What is C?

Programming in C. What is C?... What is C? C Programming in C UVic SEng 265 Developed by Brian Kernighan and Dennis Ritchie of Bell Labs Earlier, in 1969, Ritchie and Thompson developed the Unix operating system We will be focusing on a version

More information

Programming in C UVic SEng 265

Programming in C UVic SEng 265 Programming in C UVic SEng 265 Daniel M. German Department of Computer Science University of Victoria 1 SEng 265 dmgerman@uvic.ca C Developed by Brian Kernighan and Dennis Ritchie of Bell Labs Earlier,

More information

G Programming Languages - Fall 2012

G Programming Languages - Fall 2012 G22.2110-003 Programming Languages - Fall 2012 Lecture 3 Thomas Wies New York University Review Last week Names and Bindings Lifetimes and Allocation Garbage Collection Scope Outline Control Flow Sequencing

More information

COP4020 Programming Assignment 1 - Spring 2011

COP4020 Programming Assignment 1 - Spring 2011 COP4020 Programming Assignment 1 - Spring 2011 In this programming assignment we design and implement a small imperative programming language Micro-PL. To execute Mirco-PL code we translate the code to

More information

Equivalent Notations. Higher-Order Functions. (define (f x y) ( body )) = (define f (lambda (x y) ) ) Anonymous Functions.

Equivalent Notations. Higher-Order Functions. (define (f x y) ( body )) = (define f (lambda (x y) ) ) Anonymous Functions. Equivalent Notations Higher-Order Functions cs480 (Prasad L156HOF 1 (define (f x y ( body = (define f (lambda (x y ( body cs480 (Prasad L156HOF 2 Function Values (define tag (lambda (t l (cons t l (tag

More information

Lecture 7: Type Systems and Symbol Tables. CS 540 George Mason University

Lecture 7: Type Systems and Symbol Tables. CS 540 George Mason University Lecture 7: Type Systems and Symbol Tables CS 540 George Mason University Static Analysis Compilers examine code to find semantic problems. Easy: undeclared variables, tag matching Difficult: preventing

More information

Programming in C. What is C?... What is C?

Programming in C. What is C?... What is C? Programming in C UVic SEng 265 C Developed by Brian Kernighan and Dennis Ritchie of Bell Labs Earlier, in 1969, Ritchie and Thompson developed the Unix operating system We will be focusing on a version

More information

Algebraic data types. The case against null

Algebraic data types. The case against null Algebraic data types The case against null Motivation PL history (1970's) SML, OCaml, Haskell, Scala, F#, Rust, Swift Variants Null references User-defined Types compound ("Dunedin", 120_000) : string

More information

CS321 Languages and Compiler Design I Winter 2012 Lecture 13

CS321 Languages and Compiler Design I Winter 2012 Lecture 13 STATIC SEMANTICS Static Semantics are those aspects of a program s meaning that can be studied at at compile time (i.e., without running the program). Contrasts with Dynamic Semantics, which describe how

More information

Announcements. Java Review. More Announcements. Today. Assembly Language. Machine Language

Announcements. Java Review. More Announcements. Today. Assembly Language. Machine Language Announcements Java Review Java Bootcamp Another session tonight 7-9 in B7 Upson tutorial & solutions also available online Assignment 1 has been posted and is due Monday, July 2, 11:59pm Lecture 2 CS211

More information

Example: Haskell algebraic data types (1)

Example: Haskell algebraic data types (1) Example: Haskell algebraic data types (1) Type declaration: data Number = Exact Int Inexact Float Set of values: Each Number value consists of a tag, together with either an Integer variant (if the tag

More information

Org Comp Refs Typ vro Prop Deleg Attrib Version Part. Introduction Part I. Radu Nicolescu Department of Computer Science University of Auckland

Org Comp Refs Typ vro Prop Deleg Attrib Version Part. Introduction Part I. Radu Nicolescu Department of Computer Science University of Auckland Introduction Part I Radu Nicolescu Department of Computer Science University of Auckland 1 August 2017 1 / 50 1 Organisation and Contents 2 Compiling C# 3 References 4 Types 5 var, ref and out 6 Properties

More information

CMSC 330: Organization of Programming Languages. OCaml Imperative Programming

CMSC 330: Organization of Programming Languages. OCaml Imperative Programming CMSC 330: Organization of Programming Languages OCaml Imperative Programming CMSC330 Spring 2018 1 So Far, Only Functional Programming We haven t given you any way so far to change something in memory

More information

Programming with Math and Logic

Programming with Math and Logic .. Programming with Math and Logic an invitation to functional programming Ed Morehouse Wesleyan University The Plan why fp? terms types interfaces The What and Why of Functional Programming Computing

More information

Concepts of Programming Languages

Concepts of Programming Languages Concepts of Programming Languages Lecture 1 - Introduction Patrick Donnelly Montana State University Spring 2014 Patrick Donnelly (Montana State University) Concepts of Programming Languages Spring 2014

More information

LECTURE 3. Compiler Phases

LECTURE 3. Compiler Phases LECTURE 3 Compiler Phases COMPILER PHASES Compilation of a program proceeds through a fixed series of phases. Each phase uses an (intermediate) form of the program produced by an earlier phase. Subsequent

More information

Functional Programming Lecture 1: Introduction

Functional Programming Lecture 1: Introduction Functional Programming Lecture 1: Introduction Viliam Lisý Artificial Intelligence Center Department of Computer Science FEE, Czech Technical University in Prague viliam.lisy@fel.cvut.cz Acknowledgements

More information

IA010: Principles of Programming Languages

IA010: Principles of Programming Languages IA010: Principles of Programming Languages Introduction and course organization Achim Blumensath blumens@fi.muni.cz Faculty of Informatics, Masaryk University, Brno Warm-up: A Quiz What does this program

More information

8/27/17. CS-3304 Introduction. What will you learn? Semester Outline. Websites INTRODUCTION TO PROGRAMMING LANGUAGES

8/27/17. CS-3304 Introduction. What will you learn? Semester Outline. Websites INTRODUCTION TO PROGRAMMING LANGUAGES CS-3304 Introduction In Text: Chapter 1 & 2 COURSE DESCRIPTION 2 What will you learn? Survey of programming paradigms, including representative languages Language definition and description methods Overview

More information

CSE450. Translation of Programming Languages. Lecture 11: Semantic Analysis: Types & Type Checking

CSE450. Translation of Programming Languages. Lecture 11: Semantic Analysis: Types & Type Checking CSE450 Translation of Programming Languages Lecture 11: Semantic Analysis: Types & Type Checking Structure Project 1 - of a Project 2 - Compiler Today! Project 3 - Source Language Lexical Analyzer Syntax

More information

Chapter 8 ( ) Control Abstraction. Subprograms Issues related to subprograms How is control transferred to & from the subprogram?

Chapter 8 ( ) Control Abstraction. Subprograms Issues related to subprograms How is control transferred to & from the subprogram? Control Abstraction Chapter 8 (81 84) Control Abstraction: Subroutines and parameters Programmer defined control structures Subprograms Procedures Functions Coroutines Exception handlers Processes Subprograms

More information

CS 360: Programming Languages Lecture 10: Introduction to Haskell

CS 360: Programming Languages Lecture 10: Introduction to Haskell CS 360: Programming Languages Lecture 10: Introduction to Haskell Geoffrey Mainland Drexel University Thursday, February 5, 2015 Adapted from Brent Yorgey s course Introduction to Haskell. Section 1 Administrivia

More information

Chapter 5 Names, Binding, Type Checking and Scopes

Chapter 5 Names, Binding, Type Checking and Scopes Chapter 5 Names, Binding, Type Checking and Scopes Names - We discuss all user-defined names here - Design issues for names: -Maximum length? - Are connector characters allowed? - Are names case sensitive?

More information

CS312: Programming Languages. Lecture 21: JavaScript

CS312: Programming Languages. Lecture 21: JavaScript CS312: Programming Languages Lecture 21: JavaScript Thomas Dillig Thomas Dillig, CS312: Programming Languages Lecture 21: JavaScript 1/25 Why Discuss JavaScript? JavaScript is very widely used and growing

More information

NOTE: Answer ANY FOUR of the following 6 sections:

NOTE: Answer ANY FOUR of the following 6 sections: A-PDF MERGER DEMO Philadelphia University Lecturer: Dr. Nadia Y. Yousif Coordinator: Dr. Nadia Y. Yousif Internal Examiner: Dr. Raad Fadhel Examination Paper... Programming Languages Paradigms (750321)

More information

CS1 Lecture 3 Jan. 22, 2018

CS1 Lecture 3 Jan. 22, 2018 CS1 Lecture 3 Jan. 22, 2018 Office hours for me and for TAs have been posted, locations will change check class website regularly First homework available, due Mon., 9:00am. Discussion sections tomorrow

More information

Types and Type Inference

Types and Type Inference CS 242 2012 Types and Type Inference Notes modified from John Mitchell and Kathleen Fisher Reading: Concepts in Programming Languages, Revised Chapter 6 - handout on Web!! Outline General discussion of

More information

Evolution of Programming Languages

Evolution of Programming Languages Evolution of Programming Languages 40's machine level raw binary 50's assembly language names for instructions and addresses very specific to each machine 60's high-level languages: Fortran, Cobol, Algol,

More information

Homework #3 CS2255 Fall 2012

Homework #3 CS2255 Fall 2012 Homework #3 CS2255 Fall 2012 MULTIPLE CHOICE 1. The, also known as the address operator, returns the memory address of a variable. a. asterisk ( * ) b. ampersand ( & ) c. percent sign (%) d. exclamation

More information

CS 251 Intermediate Programming Methods and More

CS 251 Intermediate Programming Methods and More CS 251 Intermediate Programming Methods and More Brooke Chenoweth University of New Mexico Spring 2018 Methods An operation that can be performed on an object Has return type and parameters Method with

More information

Java Bytecode (binary file)

Java Bytecode (binary file) Java is Compiled Unlike Python, which is an interpreted langauge, Java code is compiled. In Java, a compiler reads in a Java source file (the code that we write), and it translates that code into bytecode.

More information

LECTURE 17. Expressions and Assignment

LECTURE 17. Expressions and Assignment LECTURE 17 Expressions and Assignment EXPRESSION SYNTAX An expression consists of An atomic object, e.g. number or variable. An operator (or function) applied to a collection of operands (or arguments)

More information