Algorithms
Akopọ
A satnav choosing the fastest route, a music app shuffling a playlist, a search engine ranking results: every one of these runs an algorithm, a precise sequence of steps that turns an input into an output. Before you can write a single line of Python, you need to be able to design, represent, trace and judge algorithms on paper.
This lesson builds the toolkit examiners expect on Paper 1: pseudocode and written descriptions of algorithms, trace tables for following a program's logic by hand, and the four standard algorithms named in the specification, linear search, binary search, bubble sort and merge sort. Everything here also feeds straight into Paper 2, where you will implement these same ideas as working Python code.
Awọn Afojusun
- Understand what an algorithm is, what algorithms are used for and be able to interpret algorithms (flowcharts, pseudocode, written descriptions, program code)
- Understand how to create an algorithm to solve a particular problem, making use of programming constructs (sequence, selection, iteration) and using appropriate conventions (flowchart, pseudocode, written description, draft program code)
- Understand the purpose of a given algorithm and how an algorithm works
- Understand how to determine the correct output of an algorithm for a given set of data
- Understand how to identify and correct errors in algorithms, including using trace tables
- Understand how to code an algorithm in a high-level language
- Understand how the choice of algorithm is influenced by the data structures and data values that need to be manipulated
- Understand how standard algorithms work (bubble sort, merge sort, linear search, binary search)
- Be able to evaluate the fitness for purpose of algorithms in meeting specified requirements efficiently, using logical reasoning and test data
Àwòrán ọpọlọ
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Akọ̀wé Ẹ̀kọ́
Àkọsílẹ̀ Ẹ̀kọ́ Pípé wà lórí Ohun Èlò Green Bridge
Gba ohun èlò Green Bridge CBT sórí fóònù tàbí kọ̀mpútà rẹ fún gbogbo ilé ìkàwé IGCSE: ìwé ìdánwò àtijọ́, ìlànà ìdíwọ̀n, àwòrán èrò, káàdì ìkẹ́kọ̀ọ́ àti ẹ̀kọ́ ohùn.
Ìdánwò Ẹ̀kọ́
Oriire fun ipari ẹkọ lori 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.
- Which of these is NOT one of the four standard ways to represent an algorithm? A) Pseudocode B) Flowchart C) Spreadsheet formula D) Written description Answer: C
- Binary search requires the data to be: A) Stored as a string B) Sorted C) Fewer than 10 items D) Stored in a database Answer: B
- A sorted list has 16 items. What is the maximum number of comparisons binary search needs to find any item? A) 16 B) 8 C) 4 D) 2 Answer: C
- In bubble sort, what happens on each pass through the list? A) The list is split in half B) Every item is compared to the first item only C) Neighbouring items are compared and swapped if out of order D) The list is searched for a target value Answer: C
- What is recorded in each row of a trace table? A) The line number of the source code only B) The values of variables at a point where they change C) The names of every variable used anywhere in the program D) The total running time of the algorithm Answer: B
Ṣiṣẹ́ lórí àwọn ìbéèrè wọ̀nyí nínú ohun èlò náà
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
Sample Algorithms by Problem
"Introduction to Computer Science: Sample Algorithms by Problem" 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/3-5-sample-algorithms-by-problem. Access for free at https://openstax.org/books/introduction-computer-science/pages/1-introduction
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Abala ìwé ẹ̀kọ́
Introduction to Data Structures and Algorithms
"Introduction to Computer Science: Introduction to Data Structures and 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/3-1-introduction-to-data-structures-and-algorithms. Access for free at https://openstax.org/books/introduction-computer-science/pages/1-introduction
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Ṣe Adaṣe Awọn Ibeere Idanwo Adaṣe
Ṣe o fẹ ṣe adaṣe awọn ibeere idanwo adaṣe nipa Algorithms? Ṣe igbasilẹ ohun elo Green Bridge CBT lati wọle si awọn ibeere idanwo adaṣe ati awọn ayẹwo adaṣe kikun fun koko-ọrọ yii.
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