Problem solving and programming are at the heart of Computer Science, combining logical thinking with practical implementation. This topic focuses on strategies like top-down design and stepwise refinement, which help break complex problems into manageable tasks. By writing pseudocode, creating flowcharts, and adhering to programming best practices, students can develop structured, efficient, and maintainable solutions. These foundational skills are essential for tackling real-world challenges and building robust software systems.
Top-down design:
Start with a broad problem statement and recursively break it down.
Produces a hierarchy of subproblems.
Stepwise refinement:
Continuously refine each subproblem until it’s detailed enough to solve directly in code.
Purpose:
Improves clarity, reduces complexity, and helps create structured solutions.
Pseudocode:
A language-independent notation for designing algorithms.
Common keywords: IF, THEN, ELSE, WHILE, FOR, REPEAT, UNTIL.
Flowcharts:
Visual diagrams showing the flow of control in an algorithm.
Standard shapes: oval (start/end), parallelogram (input/output), rectangle (process), diamond (decision).
Importance:
Clarifies logic before coding.
Facilitates collaboration and review.
Naming conventions:
Use descriptive names for variables, functions, classes.
Improves readability and maintainability.
Commenting:
Explains why something is done, not just what.
Helps future maintainers (and your future self) understand logic.
Modularity:
Splitting code into functions, procedures, or modules.
Encourages reusability and simplifies debugging.
Black box testing:
Tester sees only inputs and outputs.
Internals of the system are not considered.
White box testing:
Tester examines the internal structure and flow of code.
Ensures every path in the code is tested.
Alpha testing:
Done in-house by the development team or dedicated test team.
Beta testing:
Done by a limited external group of potential end-users before final release.