Programming Languages Tevfik Ko ar Lecture I January 17th 2006 1 Contact Information Prof Tevfik Kosar Office 292 Coates Phone 578 9483 Email kosar lsu edu Web http www cct lsu edu kosar Office hours Tue Thu 1 30pm 2 30pm Course web page http www cct lsu edu kosar csc4101 Provide me with your active email address to be added to the class mailing list 2 1 Roadmap Meet the Professor Background Teaching philosophy Motivation for the Course What expect to learn Introduction to the Course Material Administrative details Take Photos 3 Tevfik Kosar Joined LSU in August 2005 Education PhD University of Wisconsin Madison CS MS Rensselaer Polytechnic Institute NY CS BS Bosporus University Turkey CompE Teaching This semester CSC 4101 Programming Languages Next year CSC 4103 Operating Systems CSC 7700 Data Intensive Distributed Computing 4 2 Research Grid Computing Analogy to the Power Grid A special case for Distributed Computing Spans wide area networks and multiple administrative domains The Center for Computation Technology Spend half of my time there Office Johnston 333 Multi disciplinary research http www cct lsu edu 5 The Imminent Data deluge Exponential growth of scientific data 2000 2005 2010 2015 0 5 Petabyte 10 Petabytes 100 Petabytes 1000 Petabytes I am terrified by terabytes Anonymous I am petrified by petabytes Jim Gray Moore s Law outpaced by growth of scientific data 6 3 A High Energy Physics Project LHC The detectors at the LHC will probe fundamental forces in our Universe such as search for the yet undetected Higgs Boson Starting in 2006 the LHC accelerator will produce protonproton collisions with a rate of 109 events s Four detectors ATLAS CMS ALICE LHC B LHC Challenges 11 Petabytes of data per year 100 000 CPUs 5000 physicists in 300 institutes in 50 countries 7 A Bioinformatics Project BLAST Goal decode genetic information and map the genomes of humans and other species Uses comparative genomics compares unknown genetic sequences billions to known genomes in search of similarities Current dataset Several Petabytes Future Exponential Growth SCARY 8 4 An Educational Technology Project WCER Educational Video Processing Build histories of student learning for use in education research and instruction relying on video data Analyze and share large amount of video 1 hour DV video is 13 GB A typical educational research video uses 3 cameras 39 GB for 1 hour Current data set 500 Terabytes Future Several Petabytes 9 Astronomy Mapping of Universe detection of new galaxies and stars Current Datasets Project Data Volume DPOSS 3 TB 2MASS 12 TB SDSS 40 TB Future Productions Project Data Volume WFCAM MACHO MACHO 2MASS 2MASS SDSS SDSS DPOSS DPOSS GSC II GSC II COBE COBE MAP MAP NVSS NVSS FIRST FIRST GALEX GALEX ROSAT ROSAT OGLE OGLE 20 TB year VISTA 100 TB year LSST 1000 TB year 10 5 How to access and process distributed data TB TB PB PB 11 Interested Send an email to kosar lsu edu Register for a independent study CSC 4999 Take 3 credits for doing research in one of these interesting topics during one semester 12 6 Teaching Philosophy Goal For instructor teaching the material For student learning and applying the material in real life Grades are of second degree importance Do not memorize understand the material Exams may be openbook You are only responsible from material Covered in the class Part of projects or homework assignments 13 Programming Languages How many different programming languages are there More than 200 Can you name some of them Which ones have you used before Java C C Lisp Scheme Prolog 14 7 Language of the Computer Machine Language Consists of 0 s and 1 s Which refers to high and low voltage states 0010 0111 1010 1101 1111 1111 1101 0000 27bdffd0 afbf0014 0c1002a8 Assembly Language push bx mov bx div bx add dx Direct mapping to machine language Higher Level Languages C C Java Pascal Scheme Prolog First one Fortran 15 Why are there so many programming languages Special Purposes Each language is designed to solve a certain problem Perl for string parsing and manipulation C C for systems programming Java for platform independent programs Prolog for logic programming and AI Fortran for numerical computations Personal Preferences Evolution Learn better ways of doing things over time eg from go to to while loops case statements 16 8 What makes a language successful easy to learn BASIC Pascal LOGO Scheme easy to express things easy use once fluent powerful C Common Lisp APL Algol 68 Perl easy to implement BASIC Forth possible to compile to very good fast small code Fortran backing of a powerful sponsor COBOL PL 1 Ada Visual Basic wide dissemination at minimal cost Pascal Turing Java 17 Programming Paradigms Group languages as declarative functional Scheme ML pure Lisp FP logic constraint based Prolog VisiCalc RPG imperative von Neumann Fortran Pascal Basic C object oriented Smalltalk Eiffel C scripting languages PHP Perl Python JavaScript 18 9 Why study programming languages Help you choose a language Make it easier to learn new languages Syntactic similarities C vs Java Conceptual siilarities C vs Pascal Help you make better use of whatever language you use Choose among alternative ways Using arrays vs pointers Loops vs Recursion Simulate useful features in languages that lack them Faking pointers Faking modularity 19 Textbooks Required text Programming Language Pragmatics 2nd edition by Michael Scott Morgan Kauffman Publishers 2005 Recommended text Concepts of Programming Languages 6th edition Robert W Sebesta Addison Wesley 2003 There will be additional links for supplementary course material on the course web page 20 10 Grading The end of semester grades will be composed of Popup Quizzes Active Contribution Homework Projects Midterm Final 5 5 15 30 20 25 21 Reading Assignment Read chapter 1 from Programming Language Pragmatics PLP 22 11 Any Questions Hmm Hmm 23 12