In-class-exercise3-2019-0320.docx - Name Student ID CS206B 2019 SPRING 1 | P a g e Name Student ID CS206B 2019 SPRING 2 | P a g e Name Student ID

In-class-exercise3-2019-0320.docx - Name Student ID CS206B...

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Name: Student ID: CS206B. 2019 SPRING 1 | P a g e
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Name: Student ID: CS206B. 2019 SPRING 2 | P a g e
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Name: Student ID: Problem 1. If the running time of an algorithm does not depend on the size of the input n , the algorithm runs in ______(a)_____ time. Using the big-Oh notation, we say the running time of such an algorithm is _____(b)______ . Fill in the blanks. (1 point @ each) Problem 2. Show that (n+1) 5 is O(n 5 ), based on the big-Oh definition. Problem 3. 1) Describe an efficient algorithm for finding the ten largest elements in an array of size n. 2) What is the running time of your algorithm? In your answer use the big-Oh notation, in terms of an array of size n . O(n) Problem 4. Order the following functions by increasing growth rate. (No partial credit) CS206B. 2019 SPRING 3 | P a g e
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Name: Student ID: Problem 5. Here is the story about the inventor of the game of chess. He asked only that his king pay him 1 grain of rice for the first square on the board, 2 grains for the second square, 4 grains for the third square.
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  • Summer '10
  • Big O notation, Analysis of algorithms

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