2.2.2 Computational Methods

What is a key feature that makes a problem solvable by computational methods?

• The problem is completely random and unpredictable.

• The problem can be broken down into a series of steps or rules.

• The problem has no defined input or output.

• The problem requires subjective human judgment only.

What is problem recognition in computational terms?

• Ignoring the problem.

• Identifying that a problem exists and defining its characteristics.

• Solving the problem immediately without analysis.

• Creating more problems.

What is problem decomposition?

• Combining multiple problems into one.

• Breaking down a complex problem into smaller, more manageable sub-problems.

• Ignoring the complexity of a problem.

• Making a problem more difficult to solve.

What is the "divide and conquer" approach?

• Solving a problem all at once.

• Breaking a problem into sub-problems, solving them independently, and combining the results.

• Avoiding solving sub-problems.

• Ignoring the problem's structure.

What is the use of abstraction in computational methods?

• Focusing on every detail of a problem.

• Simplifying a problem by focusing on essential features and ignoring irrelevant details.

• Making problems more complex.

• Avoiding problem-solving.

What is backtracking?

• Moving forward without considering previous steps.

• A problem-solving technique that explores potential solutions and reverts to a previous state if a solution cannot be found.

• Ignoring potential solutions.

• Only trying one solution.

What is data mining?

• Extracting valuable information and patterns from large datasets.

• Deleting data.

• Creating random data.

• Storing data without analysis.

What are heuristics?

• Exact solutions to problems.

• Problem-solving techniques that use practical methods or shortcuts to produce solutions that may not be optimal but are sufficient for a given set of circumstances.

• Ignoring problem constraints.

• Making problems more complex.

What is performance modelling?

• Ignoring system performance.

• Evaluating and predicting the performance of a system or algorithm under different conditions.

• Only focusing on code writing.

• Creating inefficient systems.

What is pipelining?

• Processing tasks one at a time.

• A technique where multiple instructions or processes overlap in execution.

• Avoiding parallel processing.

• Increasing processing time.