Algorithms
Gbogbo ọrọ náà
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.
Ebumnobi
- 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
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Nnyocha Ọmụmụ
Ekele diri gi maka imecha ihe karịrị na Algorithms. Ugbu a na ị na-enyochakwa isi echiche na echiche ndị dị mkpa, ọ bụ oge iji nwalee ihe ị ma. Ngwa a na-enye ụdị ajụjụ ọmụmụ dị iche iche emebere iji kwado nghọta gị wee nyere gị aka ịmata otú ị ghọtara ihe ndị a kụziri.
Ị ga-ahụ ngwakọta nke ụdị ajụjụ dị iche iche, gụnyere ajụjụ chọrọ ịhọrọ otu n’ime ọtụtụ azịza, ajụjụ chọrọ mkpirisi azịza, na ajụjụ ede ede. A na-arụpụta ajụjụ ọ bụla nke ọma iji nwalee akụkụ dị iche iche nke ihe ọmụma gị na nkà nke ịtụgharị uche.
Jiri akụkụ a nke nyocha ka ohere iji kụziere ihe ị matara banyere isiokwu ahụ ma chọpụta ebe ọ bụla ị nwere ike ịchọ ọmụmụ ihe ọzọ. Ekwela ka nsogbu ọ bụla ị na-eche ihu mee ka ị daa mba; kama, lee ha anya dị ka ohere maka ịzụlite onwe gị na imeziwanye.
- 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
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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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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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Meecha Ajụjụ Ule Ọmarịcha
Ị chọrọ ime ajụjụ ule ọmarịcha gbasara Algorithms? Budata ngwa Green Bridge CBT iji nweta ajụjụ ule ọmarịcha na nyocha zuru ezu gbasara isiokwu a.
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