Algorithms
Übersicht
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.
Ziele
- 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
Mindmap
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Lektionshinweis
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Unterrichtsbewertung
Herzlichen Glückwunsch zum Abschluss der Lektion über Algorithms. Jetzt, da Sie die wichtigsten Konzepte und Ideen erkundet haben,
Sie werden auf eine Mischung verschiedener Fragetypen stoßen, darunter Multiple-Choice-Fragen, Kurzantwortfragen und Aufsatzfragen. Jede Frage ist sorgfältig ausgearbeitet, um verschiedene Aspekte Ihres Wissens und Ihrer kritischen Denkfähigkeiten zu bewerten.
Nutzen Sie diesen Bewertungsteil als Gelegenheit, Ihr Verständnis des Themas zu festigen und Bereiche zu identifizieren, in denen Sie möglicherweise zusätzlichen Lernbedarf haben.
- 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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Empfohlene Bücher
Weiterlernen mit offenen Quellen
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Lehrbuchabschnitt
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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Lehrbuchabschnitt
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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