Efficiency Of Algorithms
Akopọ
Ask a class of thirty to add up the numbers from 1 to 100 and most of them start at the left and work along. One of them writes 5050 after a few seconds, because 1 and 100 make 101, and so do 2 and 99, and there are fifty such pairs. Both people solve the same problem. Both get the same answer. One did ninety-nine additions and the other did about three operations, and that gap is the entire content of this lesson.
You will learn why more than one algorithm can solve the same problem, what makes one of them more efficient than another, and how to compare two algorithms by counting the work they do rather than by timing them on a stopwatch. You will also learn where this specification stops: it asks only about time efficiency, and it never asks for a formal mathematical comparison. Knowing the boundary of a topic is worth marks, because it tells you what a question can and cannot be asking.
Awọn Afojusun
- Understand that more than one algorithm can be used to solve the same problem. Compare the efficiency of algorithms explaining how some algorithms are more efficient than others in solving the same problem.
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Ṣe ìdánrawò káàdì wọ̀nyí nínú áàpù
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Oriire fun ipari ẹkọ lori Efficiency Of Algorithms. Ni bayi ti o ti ṣawari naa awọn imọran bọtini ati awọn imọran, o to akoko lati fi imọ rẹ si idanwo. Ẹka yii nfunni ni ọpọlọpọ awọn adaṣe awọn ibeere ti a ṣe lati fun oye rẹ lokun ati ṣe iranlọwọ fun ọ lati ṣe iwọn oye ohun elo naa.
Iwọ yoo pade adalu awọn iru ibeere, pẹlu awọn ibeere olumulo pupọ, awọn ibeere idahun kukuru, ati awọn ibeere iwe kikọ. Gbogbo ibeere kọọkan ni a ṣe pẹlu iṣaro lati ṣe ayẹwo awọn ẹya oriṣiriṣi ti imọ rẹ ati awọn ogbon ironu pataki.
Lo ise abala yii gege bi anfaani lati mu oye re lori koko-ọrọ naa lagbara ati lati ṣe idanimọ eyikeyi agbegbe ti o le nilo afikun ikẹkọ. Maṣe jẹ ki awọn italaya eyikeyi ti o ba pade da ọ lójú; dipo, wo wọn gẹgẹ bi awọn anfaani fun idagbasoke ati ilọsiwaju.
- On this specification, exam questions about the efficiency of algorithms refer only to: A. Memory efficiency B. Network efficiency C. Storage efficiency D. Time efficiency Answer: D
- An algorithm takes 2 seconds on 1000 items and 8 seconds on 2000 items. Approximately how long would it take on 4000 items? A. 10 seconds B. 16 seconds C. 32 seconds D. 64 seconds Answer: C
- A binary search is used on a sorted list of 1000 items. What is the maximum number of comparisons it will make? A. 3 B. 10 C. 500 D. 1000 Answer: B
- Which statement about two algorithms that solve the same problem is correct? A. The faster algorithm is always the better choice B. Two correct algorithms must do the same amount of work C. Only one algorithm can be correct for any problem D. The faster algorithm may have a condition on the data that the slower one does not Answer: D
- Algorithm A adds up the numbers from 1 to N with a loop. Algorithm B calculates N * (N + 1) DIV 2. Which statement is true when N is very large? A. Algorithm A does far more work than Algorithm B B. Algorithm B does far more work than Algorithm A C. Both do the same amount of work D. Algorithm B gives a different answer Answer: A
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Ṣiṣẹ́ lórí àwọn ìbéèrè wọ̀nyí nínú ohun èlò náà
Awọn Iwe Itọsọna Ti a Gba Nimọran
Ẹ̀kọ́ síwájú láti àwọn orísun ṣíṣí
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Abala ìwé ẹ̀kọ́
Formal Properties of Algorithms
"Introduction to Computer Science: Formal Properties of Algorithms" by OpenStax, OpenStax, Rice University, licensed under CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/). Source: https://openstax.org/books/introduction-computer-science/pages/3-3-formal-properties-of-algorithms. Access for free at https://openstax.org/books/introduction-computer-science/pages/1-introduction
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