IB DP Computer Science B.1: Computational Thinking – Practice Questions

These are original questions written for Marlbridge, for revision and practice on this content. They are not reproduced past-paper questions, and they do not replicate the exam’s exact structure, question count or mark tariffs – the IB holds copyright in its own papers. Use these alongside the official past papers available through your school or the IB store.

Related: B.1 Computational thinking study guide and revision notes.

These questions practise the computational thinking process as the IB’s public subject brief for the 2027 course describes it: specify problems and success criteria, decompose, abstract and generalize, and test and evaluate. The detailed B.1 learning outcomes are in the full DP guide; use your school’s copy and official specimen material for exam-style wording.

Section A

1. State the four abilities that computational thinking involves. [4]

2. Explain why success criteria should be determined when a problem is specified, before a solution is designed. [2]

3. Distinguish between decomposition and abstraction. [2]

Section B

4. A library wants a program that lists every book that is overdue.

(a) Specify the problem: state the input, the output and one testable success criterion. [3] (b) Decompose the problem into at least three smaller problems. [3] (c) Identify two details about each book that are needed and one that can be abstracted away. [3]

5. A student’s solution to question 4 is tested only with a list in which every book is overdue. Evaluate this testing and suggest two further tests. [4]

6. Explain what is meant by generalizing a solution, using the library program as an example. [2]

7. The internal assessment requires students to develop a computational solution to a real-world problem of their own choosing. Explain how each of the four abilities would be used in the IA. [4]

Answers

1. Specify problems in terms of their computational context and determine success criteria [1]; decompose complex real-world problems into more manageable problems [1]; abstract problems and generalize them to enable algorithmic thinking [1]; test and evaluate solutions for improvements [1].

2. Success criteria define what the solution must achieve [1], so they guide the design and give a fixed standard to test and evaluate the finished solution against, rather than judging it afterwards by impression [1].

3. Decomposition breaks a complex problem into smaller, more manageable problems [1]. Abstraction removes details that do not matter to the solution, keeping only what is needed so an algorithm can be designed [1].

4. (a) Input: the list of loans with due dates, and today’s date [1]. Output: the titles (and borrowers) of overdue books [1]. Success criterion, e.g. every book whose due date is before today appears in the list and no other book does [1].

(b) Any three [1 each]: read the loan data; get today’s date; compare each due date with today; collect overdue books; display the list.

(c) Needed [2]: title (or book ID) and due date (also accept borrower). Abstracted away [1]: e.g. author, page count, cover colour, shelf position.

5. The test only checks one situation [1], so it cannot show that books which are not overdue are excluded, which the success criterion requires [1]. Further tests [2]: a list with no overdue books; a mixed list; a book due exactly today (boundary); an empty list.

6. Generalizing means expressing the solution so it works for a wider class of problems, not just the one example [1]; e.g. “select every item whose date is before a given date” could also list expired memberships or late assignments [1].

7. One mark per ability linked to the IA [4]: specify the client’s problem and agree success criteria; decompose it into parts that can be designed and programmed; abstract the essential data and generalize the processing into algorithms; test the product against the success criteria and evaluate it, recommending improvements.

Where marks are usually lost

• Success criteria that cannot be tested (“easy to use”, “works properly”).
• Listing steps of decomposition that are just restatements of the whole problem.
• Calling abstraction “hiding” without saying what detail is removed and why.
• Testing only expected cases, with no boundary or empty-input tests.

Frequently asked questions

Are these questions in the IB’s style? They are written to practise the process described in the subject brief. For exact command terms and mark tariffs, use the IB’s specimen papers and the full guide.

How long should I spend on B.1? The brief recommends 5 teaching hours at both SL and HL, but the process is used in every programming task, so practise it alongside B.2.