Algorithms
Overview
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.
Objectives
- 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
Lesson Note
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Lesson Evaluation
Congratulations on completing the lesson on Algorithms. Now that youve explored the key concepts and ideas, its time to put your knowledge to the test. This section offers a variety of practice questions designed to reinforce your understanding and help you gauge your grasp of the material.
You will encounter a mix of question types, including multiple-choice questions, short answer questions, and essay questions. Each question is thoughtfully crafted to assess different aspects of your knowledge and critical thinking skills.
Use this evaluation section as an opportunity to reinforce your understanding of the topic and to identify any areas where you may need additional study. Don't be discouraged by any challenges you encounter; instead, view them as opportunities for growth and improvement.
- 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
Available on the Green Bridge App
Download the Green Bridge CBT app on your phone or computer to access full lesson notes, practice questions, and more.
Available on the Green Bridge App
Download the Green Bridge CBT app on your phone or computer to access full lesson notes, practice questions, and more.
Recommended Books
Practice Mock Questions
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