Algorithms — A-Level Computer Science Revision
Revise Algorithms for A-Level Computer Science. Step-by-step explanation, worked examples, common mistakes and exam-style practice aligned to AQA, Edexcel and OCR.
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Go to Object-Oriented ProgrammingWhat is Algorithms?
An algorithm is a finite sequence of well-defined, computer-implementable instructions to solve a class of problems or to perform a computation. Key examples include sorting algorithms like Bubble Sort and Merge Sort, and searching algorithms like Binary Search.
Board notes: All boards (AQA, Edexcel, OCR) require knowledge of standard searching and sorting algorithms. AQA and OCR also expect students to be able to analyze the efficiency of algorithms.
Step-by-step explanationWorked example
To find a name in a sorted list of 1000 names, a binary search is highly efficient. First, check the middle name (at index 500). If the target name is alphabetically earlier, repeat the process on the first half (1-499); if later, on the second half (501-1000). This halves the search space with each comparison.
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Common mistakes
- 1Incorrectly implementing the base case in a recursive algorithm, leading to a stack overflow.
- 2Forgetting that a binary search requires the data to be sorted first.
- 3Underestimating the performance difference between algorithms, for example, using a O(n^2) sort on a large dataset.
Algorithms exam questions
Exam-style questions for Algorithms with mark-scheme style solutions and timing practice. Aligned to AQA, Edexcel and OCR specifications.
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Step-by-step method
Step-by-step explanation
4 steps · Worked method for Algorithms
Core concept
An algorithm is a finite sequence of well-defined, computer-implementable instructions to solve a class of problems or to perform a computation. Key examples include sorting algorithms like Bubble Sor…
Frequently asked questions
Why is Big O notation important?
Big O notation is used to describe the performance or complexity of an algorithm. It helps in choosing the most efficient algorithm for a given problem, especially as data size grows.
What is the difference between a greedy algorithm and a divide and conquer algorithm?
A greedy algorithm makes the locally optimal choice at each stage, while a divide and conquer algorithm breaks the problem into smaller subproblems, solves them recursively, and combines the solutions.