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Image credits: http://xkcd.com/353/

CS 354: Programming Languages

Alark Joshi

Copyright © 2009 Addison-Wesley. All rights

reserved.

Contact Information • Email: [email protected]

• Course Website:

o http://cs.boisestate.edu/~alark/cs354

• Office: MEC 302A

• Office Hours:

o Monday, Friday : 10-11am

o Tuesday, Thursday: 3-4pm

o Doodle poll

TA Information • Teaching Assistant

• Nathan Riskey

o [email protected]

o Graduate Student

o Work experience

• Office hours: To be announced soon

Administrivia • Roll call sheet going around – Please sign

and note your team assignment

• Piazza instead of a mailing list

o https://piazza.com/boisestate/fall2012/compsc

i354

o Better at managing responses, replies, helping

each other through assignments, homework,

projects etc.

Textbook & Resources • Concepts of Programming Languages by

Richard Sebesta, Addison Wesley publishing,

9th Edition, 2009.

• Course Wiki:

o cs354.pbworks.com

o Collaborative resource

o Feel free to edit and improve

Why study languages/programming languages?

• Look to the person sitting next to you

• Introduce yourself

• Make the longest list of reasons you can

think of in 2 minutes

• Longest list in class wins!

• Go!!!

• I will call on you to share from your list

Reasons from Sebesta 1. Increased capacity to express ideas

2. Improved background for choosing

appropriate languages

3. Increased ability to learn new languages

4. Better understanding of the significance of

implementation

5. Better use of languages that are already

known

6. Overall advancement of computing

Grade Breakdown • Quizzes – 21%

• Interpreter assignment – 15%

• Programming assignments – 15%

• Homework – 14%

• Final project - 35%

o Create a website for a programming language

o Work on a project using that programming

language

Final Project • P1 - Website for learning a new language:

weebly, pbworks or any other

• P2 - Create a detailed manual or YouTube

video with details regarding installation, IDE

setup and other relevant issues

• P3 - include 10/15 examples of increasing

difficulty to teach a novice about that

programming language

Final Project • P4 - Update website with a comprehensive

list of relevant resources, books, tutorials,

videos, etc.

• P5 - Propose 3 projects to me (and

anonymous reviewers) - We pick one for you

to implement by the end of the semester

• P6 - 5-min presentation in the class about

your project and what you propose to do

Final Project • P7 - Incorporate feedback from anonymous

reviewers to improve your website

• P8 – In-class presentation (25-mins)

• Final grade of the project based on

o Quality of the website

o Ability to follow along for reviewers

o Quality of final project

o Relevant documentation

Anonymous reviewers • Each student and some external software

partners will serve as anonymous reviewers

• Code review for programs and final project

• Monthly reports on the quality of the website

and the status of the project as described

on the website

Programming Assignments

• Interpreter assignments

o V1 and V2 – worth 15%

• Three language related assignments

o C# - 5%

• Assignment available – Due 10th Sept

o Python - 5%

o Scheme/ML/Haskell - 5%

Team-Based Learning • Long Lectures have been shown to produce

significant reduction in understanding as the

lecture progresses

• Team-based learning

o Apply

o Question

o Reflect upon and

o Discuss content in a group

TBL Quizzes • Each quiz will be taken first as an individual

• Same quiz will be taken as a team

o Instant feedback for the team

• TBL quizzes – individual vs team performance

• Quizzes – 21% of the final grade

o Quiz 1 - Chapter 1 of Sebesta on 5th Sept

Team Assignments • Teams assignments are going around

• Please meet your team now!

o Buzz Lightyear

o Dory

o Merida

o Nemo

o Remy

o Sulley

o Wall-E

Languages

1. Python

2. Javascript

3. CUDA

4. Lua

5. Haskell

6. C++

7. Ruby

8. Actionscript

9. Objective-C

10. Perl

11. Processing

12. Lisp

13. Matlab

14. R

Image credits: http://xkcd.com/519/

Language Evaluation Criteria

• Course objective #6:

o Evaluate a language on the basis of the

various features which it supports.

• How would you evaluate a language?

• Think-pair-share (2-2-2)

o 2 mins to think of metrics you would use

o 2 mins to share it with your partner/team

o 2 mins to share with the class

Language Evaluation Criteria

• Readability

• Writability

• Reliability

• Cost

Readability

The ease with which programs can

be read and understood

Evaluation Criteria: Readability

• Overall simplicity

o A manageable set of features and constructs

o Minimal feature multiplicity

o Minimal operator overloading

• Orthogonality

o A relatively small set of primitive constructs can

be combined in a relatively small number of

ways

o Every possible combination is legal

Evaluation Criteria: Readability

• Data types o Adequate predefined data types

• Syntax considerations

o Identifier forms: flexible composition

o Special words and methods of forming

compound statements

o Form and meaning: self-descriptive constructs,

meaningful keywords

Writability

The ease with which a language

can be used to create programs

Evaluation Criteria: Writability

• Simplicity and orthogonality

o Few constructs, a small number of primitives, a small set of

rules for combining them

• Support for abstraction

o The ability to define and use complex structures or

operations in ways that allow details to be ignored

• Expressivity

o A set of relatively convenient ways of specifying operations

o Strength and number of operators and predefined functions

Reliability

Conformance to specifications (i.e.,

performs to its specifications)

Evaluation Criteria: Reliability

• Type checking o Testing for type errors

• Exception handling o Intercept run-time errors and take corrective

measures

Evaluation Criteria: Reliability

• Aliasing o Presence of two or more distinct referencing

methods for the same memory location

• Readability and writability o A language that does not support “natural” ways

of expressing an algorithm will require the use of

“unnatural” approaches, and hence reduced

reliability

Evaluation Criteria: Cost

• Training programmers to use the language

• Writing programs (closeness to particular

applications)

• Compiling programs

• Executing programs

• Language implementation system:

availability of free compilers

• Reliability: poor reliability leads to high costs

• Maintaining programs

Image credits - http://xkcd.com/303/

Evaluation Criteria: Others

• Portability

o The ease with which programs can be moved

from one implementation to another

• Generality

o The applicability to a wide range of

applications

• Well-definedness

o The completeness and precision of the

language‟s official definition

Influences on Language Design

• Computer Architecture

o Languages are developed around the

prevalent computer architecture, known as the

von Neumann architecture

• Program Design Methodologies

o New software development methodologies

(e.g., object-oriented software development)

led to new programming paradigms and by

extension, new programming languages

The von Neumann Architecture

The von Neumann Architecture

• Fetch-execute-cycle (on a von Neumann

architecture computer)

initialize the program counter

repeat forever

fetch the instruction pointed by the counter

increment the counter

decode the instruction

execute the instruction

end repeat

Computer Architecture Influence

• Well-known computer architecture: Von Neumann

• Imperative languages, most dominant, because of

von Neumann computers

o Data and programs stored in memory

o Memory is separate from CPU

o Instructions and data are piped from memory to CPU

o Basis for imperative languages

• Variables model memory cells

• Assignment statements model piping

• Iteration is efficient

Programming Methodologies Influences

• 1950s and early 1960s: Simple applications; worry

about machine efficiency

• Late 1960s: People efficiency became important;

readability, better control structures

o structured programming

o top-down design and step-wise refinement

• Late 1970s: Process-oriented to data-oriented

o data abstraction

• Middle 1980s: Object-oriented programming

o Data abstraction + inheritance + polymorphism

Language Categories • Imperative

o Central features are variables, assignment statements, and iteration

o Include languages that support object-oriented programming

o Include scripting languages

o Include the visual languages

o Examples: C, Java, Perl, JavaScript, Visual BASIC .NET, C++

• Functional o Main means of making computations is by

applying functions to given parameters

o Examples: LISP, Scheme, ML, F#

Language Categories • Logic

o Rule-based (rules are specified in no particular order)

o Example: Prolog

• Markup/programming hybrid oMarkup languages extended to support

some programming

o Examples: JSTL, XSLT, LaTeX

Language Design Trade-Offs • Reliability vs. cost of execution

o Example: Java demands all references to array elements

be checked for proper indexing, which leads to increased

execution costs

• Readability vs. writability o Example: APL provides many powerful operators (and a

large number of new symbols), allowing complex

computations to be written in a compact program but at

the cost of poor readability

• Writability (flexibility) vs. reliability o Example: C++ pointers are powerful and very flexible but

are unreliable

2-2-2

Implementation Methods • Compilation

o Programs are translated into machine language; includes JIT systems

o Use: Large commercial applications

• Pure Interpretation o Programs are interpreted by another program known as an

interpreter

o Use: Small programs or when efficiency is not an issue

• Hybrid Implementation Systems o A compromise between compilers and pure interpreters

o Use: Small and medium systems when efficiency is not the first concern

Layered View of Computer

The operating system and language implementation are layered over machine interface of a computer

Compilation vs. Interpretation

• Compilation vs. interpretation

o not opposites

o not a clear-cut distinction

• Pure Compilation

o The compiler translates the high-level

source program into an equivalent target

program (typically in machine

language), and then goes away:


• Pure Interpretation

o Interpreter stays around for the execution

of the program

o Interpreter is the locus of control during

execution


• Interpretation:

oGreater flexibility

o Better diagnostics (error messages)

• Compilation

o Better performance


• Common case is compilation or simple

pre-processing, followed by

interpretation

• Most language implementations - mixture

of both compilation and interpretation

Compilation • Compilation does NOT have to produce

machine language for some sort of

hardware

• Compilation is translation from one

language into another, with full analysis of

the meaning of the input

Compilation • Compilation entails semantic understanding

of what is being processed; pre-processing

does not • A pre-processor is a program that processes its input data to

produce output that is used as input to another program

(usually compiler)

• A pre-processor will often let errors through.

A compiler hides further steps; a pre-

processor does not


• Implementation strategies:

o Preprocessor

• Removes comments and white space

• Groups characters into tokens (keywords,

identifiers, numbers, symbols)

• Expands abbreviations in the style of a macro

assembler

• Identifies higher-level syntactic structures

(loops, subroutines)



o Library of Routines and Linking

• Compiler uses a linker program to merge the

appropriate library of subroutines (e.g., math

functions such as sin, cos, log, etc.) into the

final program:



o Post-compilation Assembly

• Facilitates debugging (assembly language

easier for people to read)

• Isolates the compiler from changes in the

format of machine language files (only

assembler must be changed, is shared by

many compilers)

Compilation vs. Interpretation • Implementation strategies:

o The C Preprocessor (conditional

compilation)

• Preprocessor deletes portions of code,

which allows several versions of a program

to be built from the same source



o Source-to-Source Translation (C++)

• C++ implementations based on the early

AT&T compiler generated an intermediate

program in C, instead of an assembly

language:



oCompilation of Interpreted Languages

• The compiler generates code that makes

assumptions about decisions that won‟t be

finalized until runtime.

• If these assumptions are valid, the code runs

very fast.

• If not, a dynamic check will revert to the

interpreter.



oDynamic and Just-in-Time Compilation

• In some cases a programming system may

deliberately delay compilation until the last

possible moment.

o Lisp and Prolog invoke the compiler on the fly, to

translate newly created source into machine language


oDynamic and Just-in-Time Compilation

• The Java language definition defines a

machine-independent intermediate

form known as byte code. Byte code is

the standard format for distribution of

Java programs.

• The main C# compiler produces .NET

Common Intermediate Language (CIL),

which is then translated into machine

code immediately prior to execution.


• Compilers exist for some interpreted languages, but they aren't pure:

o selective compilation of compilable pieces and extra-sophisticated pre-processing of remaining source.

o Interpretation of parts of code, at least, is still necessary for reasons above.

• Unconventional compilers

o text formatters

o silicon compilers

o query language processors

von Neumann Bottleneck • Connection speed between a computer‟s

memory and its processor determines the speed of a computer

• Program instructions often can be executed much faster than the speed of the connection; the connection speed thus results in a bottleneck

• Known as the von Neumann bottleneck; it is the primary limiting factor in the speed of computers

Robot Programming • In groups of 2/3 select

a “robot” and a “robot

master”

• The “Dictionary”

contains a list of

commands that a

robot understands

• Invent new commands

Robot Programming • The goal is for the robot to go through a

maze, move an object and reach the end

• Your sub-group will write a program that will

be followed by the robot

• Every time you write a program, you hand it

over to the robot who will follow the

instructions

• Use a blank sheet of paper for every

program

10 mins

Robot Game Analysis • You invented a programming language to

program a fictional robot

o The commands you used/invented are the

commands for your new programming

language

o The commands were „executed‟ by your

„robot‟

o At times you didn‟t get the expected result – which you found out by „running‟ the robot

o Debugging and Re-execute

Image credits: alark/cs354/lectures/Introduction.pdf · ocs354.pbworks.com oCollaborative resource...

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