What is decomposition in computational thinking?

• A. Breaking a problem into smaller, manageable parts
• B. Running code more quickly
• C. Combining parts into a single unit
• D. Ignoring details of the problem

Answer: (A)

Breaking a problem into smaller, manageable parts is decomposition. In computational thinking, this helps you understand and tackle a large task by dividing it into pieces that are easier to design, implement, and test. For example, if you’re writing a program to manage a library, you can decompose the task into parts like cataloging books, managing borrowers, tracking due dates, and generating reports. Each part can be worked on separately and then combined to form the full system. This approach reduces complexity and makes it easier to reuse parts in other projects.

The other ideas aren’t about breaking problems apart: making code run faster focuses on efficiency, not how the problem is divided; putting parts together into one unit describes integration or composition, not decomposition; and ignoring details defeats the purpose of analyzing the problem in smaller steps.