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CS1000 Introduction to Computer Science

CS1000 Introduction to Computer Science. Instructor Soufiane Noureddine Lectures Tu/Th: 12:15-13:30 (B650) Office Hours Tu/Th: 11:00-12:00 (C520). What Computer Science Is Not. Computer Science (CS) = Study of Computers? CS began earlier than computers (branch of math)

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CS1000 Introduction to Computer Science

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  1. CS1000Introduction to Computer Science Instructor Soufiane Noureddine Lectures Tu/Th: 12:15-13:30 (B650) Office Hours Tu/Th: 11:00-12:00 (C520)

  2. What Computer Science Is Not • Computer Science (CS) = Study of Computers? • CS began earlier than computers (branch of math) • Theoretical CS (pencil and paper) • Computer is only the basic tool in CS (e.g. beaker for chemistry, microscope for biology etc.)

  3. What Computer Science Is Not • CS = Study of how to write programs? • Use of programming languages e.g. Pascal, Lisp, C, etc. • Very important but also only a tool in CS for verifying ideas and concepts after their analysis. • Example: “Searching in a list” • Analyze the problem • Design a searching method • Write a program • Get quantitative and qualitative results.

  4. What Computer Science Is Not • CS = Study of computer applications and software? • Application: e.g. spreadsheets, word processors, databases … • Comparison: • Mechanical Engineer Computer Scientist Conceives a car conceives computer/software Builds and tests it builds and tests it • User Gets a driver license Gets some certificate Drives the car Exploits the computer/software

  5. Definition of CS • No real consensus (yet). • A good definition that emphasizes the notion of “algorithm” is: • CS is the study of algorithms including their: • Formal and mathematical properties • Hardware realizations • Linguistic realizations • Applications

  6. Algorithm • Informally: Effective and precise recipe to get the result for some problem: • “Recipe”: Set of commands/instructions • “Effective”: The result is obtainable after some time • “Precise”: exactness, only understandable and doable commands

  7. Simple Example for an algorithm • “Breakfast” • 1. Get a slice of bread • 2. Butter it • 3. Eat the buttered slice • 4. If still hungry then resume from step 1, otherwise drink a cup of tea and stop.

  8. Other examples for algorithms • Backing a pie • Using the telephone set • Programming the VCR • Doing tax calculation • …

  9. Summing up the first n integers • 1 + 2 + 3 + … + n ? • Algorithm • 1. Get the number n • 2. Set m to n+1 • 3. Set n to n multiplied by m • 4. Divide n by 2 • 5. Display the result n

  10. The Concept of Algorithm • Inventor: Abu Jaafar Mohammed Ibn-Musa Al-Khawarizmi • Arabic mathematician of the 8th century • Born in Khawarizm (Persia) • Lived in Baghdad where he worked in Beitu Alhikma (House of Wisdom) under the Khalif Al-Maamoon. • Wrote two famous books: • One is a treatise on the calculation using Arabic numerals, his name was translated in Latin to Algorismus, from there the word algorithm. • The other is even more famous since it introduced “algebra” as a new fundamental branch of mathematics. The book is Kitab Aljabr Wal Muqabala (Book of Restoration and Reduction) -> Aljabr had been translated to Algebra.

  11. The Concept of Algorithm • The main benefit of algorithms is that we can automate the solution for every problem we can find an algorithm for solving it. • Formal definition of an algorithm: • An algorithm is a well-ordered collection of unambiguous and effectively computable operations that when executed produces a result and halts in a finite amount of time.

  12. The Concept of Algorithm • Well-ordered collection • We have to always know what to do next. • Counterexample: • 1. Get a slice of bread • 2. Butter it • 3. Eat buttered slice • 4. Repeat -> 4th step: repeat what? -> not an algorithm!

  13. The Concept of Algorithm • Unambiguous + effectively computable operations • Operations: units of work the computer can do. • Different levels of operations are possible: • Example: “Breakfast” • 1. Eat buttered bread until “full” • 2. Drink a cup of tea • 3. Stop • -> Step 1 may be too “high” for a kid • Step 1 is a sequence of (sub-)operations, it also forms an algorithm! • Possible algorithm for Step 1: • 1. Get a slice of bread • 2. Butter it • 3. Eat the buttered slice • 4. If still hungry resume from 1

  14. The Concept of Algorithm • Operations should be unambiguous • directly doable • need not be further explained (e.g. using sub-operations) • Unambiguous operations are also called primitives • Any operation must be doable • Unambiguous (understandable) but not doable operations are not welcome for algorithms • Hence only effectively computable operations should be used

  15. The Concept of Algorithm • Examples of unambiguous but not effectively computable operations: • List all positive numbers • Divide by 0 • Compute for ever • Print the exact value of p • That produces a result • Any algorithm should produce a result observable to the end user. • Result may be: • Answer • Error message • …

  16. The Concept of Algorithm • And halts in a finite amount of time • Practically one of the most crucial properties of algorithms • Algorithms that work well but cannot stop are useless • Example: “Endless Loop” • 1. Get a slice of bread • 2. Butter it • 3. Eat the buttered slice • 4. Repeat from step 1 • 5. Drink a cup of tea • 6. Stop • Common flaw in the design of algorithms: Endless loops

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