CEG 221 Introduction

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CEG 221Introduction

• Mr. David Lippa

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Overview

• Introduction
• Whats this course about? A synthesis of
  language, theory, and application
• Language
• Programming Languages
• Modular C programming
• Theory Algorithm development analysis
• Application Algorithm implementation
• Syllabus
• Review-ish
• Questions

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Programming LanguagesHigh-Level vs. Low-Level

• High-Level Languages
• Close to English, but slightly slower
• Easy to use and easily read/interpreted code
• Platform independent
• Low-Level Languages
• Difficult to use but very fast
• Typically is machine-specific

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The Language Why C?

• Strengths
• Powerful, Fast, Portable yet relatively
  high-level language
• Provides organizational structure for creation,
  testing, and verification of code
• Provides similar design paradigms to other
  engineering languages, such as FORTRAN
• Weaknesses
• Inferior to Object Oriented Programming (C,
  Java) for releasable applications that require
  GUIs or greater complexity

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Theory Algorithms

• Algorithm a series of steps that results in the
  performance of a task
• Common algorithms used in CS sorting, searching,
  populating data structures
• Algorithms are frequently analyzed based on the
  number of steps to complete the task based on the
  amount of elements to process.
• Basically, answer the question How much work
  does it take to process n elements in terms of n?
  (Big-Oh, Little-Oh notation not covered in this
  course)

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Algorithms An Example

• Assume a room full of people, each person is a
  processor. In practice, sorting that room full of
  people by height is faster than by first name.
  Common sense tells us this, right?
• Everyone is an independent processor and can
  figure out where he/she belongs. Takes at most n
  memory accesses (look around the room at n
  people) to sort by height with n processors n2
  steps of work.
• Sorting by name requires each person to ask every
  other person to figure out where he/she belongs.
  Takes n requests to each person (ask each person
  his/her last name) by n processors n2 steps of
  work.
• Theyre the same!?

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Algorithm Example (Continued)

• No theyre not the same
• Each person asking every other person takes
  longer than each person scanning their eyes
  around the room to find their place.
• One can either ask or listen, so it requires each
  processor to wait for its turn to speak
• Everyone can look at everyone else without any
  such conflicts
• THUS, sorting by height is the same
• Both take n2 work under analysis, but when
  implemented, come out differently
• This is part of Algorithm Analysis

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Algorithms Analysis Implementation

• There are various ways to implement sorting
  people in a classroom.
• Divide and conquer Selection Sort
• Divide and merge MergeSort
• Move each to the proper spot BubbleSort
• Each have best/worst cases. What you also need to
  look at is the average case.
• Pick the best depending on Best, Worst, Average
  Cases and the situation

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Syllabus
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Next TimeReview of Required Concepts

• Basic data types
• Normal basic types, size_t, time_t
• Basic programming structure
• Flow control / Repetition
• Scope
• Documentation of code
• Modular programming
• Libraries
• Pass by reference (in C, by pointer) vs. pass by
  value
• Basic algorithm development
• Design document
• Pseudo code

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QUESTIONS?

• My policy on questions
• You have the right to ask questions at ANY time
  in class.
• The only stupid question is the one you dont
  ask.
• Any questions?