What is the difference between traditional fault seeding and mutation analysis?

Question

BlackTom AI · Accepted Answer

To tackle the question, let's examine what each statement implies about fault seeding and mutation analysis.
Option 1: 'Faults are evaluated independently in mutation analysis' — This aligns with the core idea of mutation analysis, where individual mutants (faults) are created and assessed separately to observe their impact on the program's behavior. Evaluating faults independently helps determine each fault's intrinsic effect without interference from other faults.
Option 2: 'Faults are assumed to be equivalent in mutation analysis' — This is inaccurate. Mutation analysis relies on introducing distinct mutations to create diverse fault scenarios, and assuming equivalence would undermine the purpose of measuring how different faults affect the program; mutants are intentionally varied.
Option 3: 'Only complex faults are evaluated in mutation analysis' — Incorrect. Mutation analysis typically includes a range of faults, from simple to complex, to explore how susceptible the program is to a spectrum of mutations; limiting to only complex faults would miss the broader assessment.
In summary, the distinguishing feature highlighted by the correct option is the independent evaluation of each fault within mutation analysis, which is essential for attributing behavior to specific mutations and understanding their individual impact.

What is the difference between traditional fault seeding and mutation analysis?Single choice

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