Quick interview answer
Equivalence partitioning, boundary value analysis, decision tables, and state transition testing let you cover behavior with fewer, high-value cases.
Detailed explanation
Equivalence partitioning groups inputs expected to behave the same, so you test one representative per class. Boundary value analysis targets edges (min-1, min, max, max+1) where defects cluster. Decision tables handle combinatorial business rules cleanly, avoiding missed rule combinations. State transition testing models systems with defined states (e.g., order status) and verifies valid/invalid transitions. Combining these with pairwise testing for multi-parameter forms further trims redundant combinations without losing meaningful coverage.
1// Boundary values for an age field accepting 18-652const testValues = [17, 18, 19, 64, 65, 66];3testValues.forEach(age => {4 const expectedValid = age >= 18 && age <= 65;5 // assert form accepts/rejects accordingly6});Real-world example
For an age-verification form, boundary value analysis alone caught an off-by-one bug where age 65 was incorrectly rejected.
Interview tip
Give a concrete boundary example on the spot — it shows you apply the technique, not just recite the name.
