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Algorithmic Thinking

Algorithmic Thinking. Chapter 10. Exercise. Write instructions to make a peanut butter and jelly sandwich. You have: jar of peanut butter jar of jelly bagged loaf of bread butter knives. Algorithm. al · go · rithm : a step-by-step procedure for solving a problem

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Algorithmic Thinking

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  1. Algorithmic Thinking Chapter 10

  2. Exercise • Write instructions to make a peanut butter and jelly sandwich. • You have: • jar of peanut butter • jar of jelly • bagged loaf of bread • butter knives

  3. Algorithm • al·go·rithm:a step-by-step procedure for solving a problem • program: instructions for a computer; an algorithm expressed in a programming language (vs. natural language) • The programming language we will use in this class is called JavaScript.

  4. Programming is just like Legos…

  5. Why Programming Is Hard • Programming is a fairly detail-oriented task. There is no room for mistakes. • Did you forget a semi-colon? • Did you use the wrong capitalization? • If you keep making the same small mistakes, you will get easily frustrated. • Learn from your mistakes and make sure to minimize them. • Programming requires the ability to think logically.

  6. Logic Test • Computers are stupid. • Computers can't read minds. • Computers don't make mistakes. • Therefore, if your computer program is not doing what you want … it is because YOU made a mistake!

  7. Exercise • You have a list of items and their retail prices. Write an algorithm to determine which item is the most expensive.

  8. Exercise • Write an algorithm to sort a list of one million numbers. • How do you start thinking up a solution? • Start small: How do you sort a list of four numbers? • Experience helps: How were similar problems solved? I think the bubble sort would be the wrong way to go. Barack Obama, when asked by Google CEO Eric Schmidt about "the most efficient way to sort a million 32-bit integers", 11/14/2007

  9. Algorithmic Efficiency • Not all algorithms are created equal. • The most obvious solution is not necessarily the most efficient. • Could be the difference between an instant and waiting a lifetime (or more!) • If we wait long enough, will the question of algorithm efficiency disappear as faster and faster computers come into existence? • No. There will always be bigger problems to solve with more and more data. • In this class, do not consider efficiency when writing programs—stick with the most obvious algorithm.

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