| Component | Role | Examples |
|---|---|---|
| Input | The 'What' (Raw Data) | Keyboard strokes, sensor readings, file data |
| Process | The 'How' (Action) | Sorting, arithmetic, logical comparisons |
| Output | The 'Result' (Information) | Printed reports, screen alerts, motor movement |
Input vs. Output: Inputs are the prerequisites for a task, whereas outputs are the fulfillment of that task. An input is what the computer 'receives,' while an output is what the computer 'gives.'
Process vs. Output: A process is an internal operation that is often invisible to the user, while the output is the visible or tangible evidence that the process occurred.
Read the Scenario Carefully: Exams often provide a short paragraph describing a real-world system; underline every piece of data mentioned and every action described. This ensures you don't miss 'hidden' inputs like configuration settings or constants.
Check Data Types: When identifying inputs, consider if they are integers, strings, or booleans, as this often influences the type of processing required. For instance, a 'Yes/No' input is a boolean that usually leads to a decision process.
Verify the Loop: Ensure that the identified processes actually use the identified inputs to produce the identified outputs. If a process doesn't use an input, that input might be unnecessary; if an output has no corresponding process, your logic is incomplete.
Confusing Process with Output: Students often list the result of a calculation as the process itself. Remember that 'Calculating the sum' is the process, while 'The Sum' is the output.
Overlooking Automatic Inputs: Some inputs are not provided by users but are retrieved from the system clock or internal databases. Always check if the algorithm requires external data that isn't explicitly typed in by a person.
Vague Descriptions: Avoid using vague terms like 'the answer' for an output; instead, use specific terms like 'The calculated area in square meters' to demonstrate a precise understanding of the problem.
