Software Metrics

This Sommerville topic covers measuring software. You compute size metrics (LOC, function points), complexity metrics (cyclomatic, Halstead), and quality metrics (defect density, MTBF), and interpret them to guide engineering decisions.

Relation 1 —

Write this relation with symbols exactly as in Software Engineering — Roger Pressman before substituting numbers. Examiners award partial marks for a correct setup even when arithmetic slips.

Relation 2 —

Write this relation with symbols exactly as in Software Engineering — Roger Pressman before substituting numbers. Examiners award partial marks for a correct setup even when arithmetic slips.

Relation 3 —

Write this relation with symbols exactly as in Software Engineering — Roger Pressman before substituting numbers. Examiners award partial marks for a correct setup even when arithmetic slips.

You cannot manage what you cannot measure, but metrics must be interpreted carefully. Size metrics estimate effort and normalise other measures — defect density (defects per KLOC) lets modules of different sizes be compared fairly. Cyclomatic complexity counts the independent paths through code, both flagging hard-to-test modules and setting a lower bound on the number of test cases needed for path coverage. Reliability metrics like MTBF summarise operational quality. The crucial discipline is using metrics to improve the process — targeting testing at complex modules, tracking defect trends — rather than as blunt instruments to rank or blame individuals, which distorts behaviour.

State assumptions explicitly before using any relation for software metrics — steady state, uniform properties, linear elastic material, ideal gas, incompressible flow, etc., as applicable.

Wrong assumptions invalidate the entire solution even when the formula is correct. In Software Engineering viva and GATE descriptive questions, listing valid assumptions often earns separate marks.

1. Read the question and list given data with SI units (common in Software Engineering papers).
2. Draw a neat labelled diagram where applicable — examiners in Indian universities award diagram marks even when arithmetic slips.
3. Identify which relation from this topic applies to software metrics.
4. Use equation 1: .
5. Use equation 2: .
6. Substitute values, compute, and verify units and sign (direction).
7. State conclusion in one line — e.g. safe/unsafe, stable/unstable, feasible/infeasible.

Software Metrics appears in product teams and IT services. In Indian it software curricula this topic is tested because it connects theory to SDLC, requirements, and quality.

GATE and semester exams often combine software metrics with earlier units — revise prerequisites before attempting mixed problems.

Industry interview panels sometimes ask: "Where did you use software metrics?" — answer with a lab, mini-project, or plant visit example if possible.

Students miscompute cyclomatic complexity (forgetting the +2P term or miscounting edges/nodes), compare raw defect counts across differently sized modules instead of defect density, and treat metrics as absolute judgements. Confusing MTBF with MTTR is a frequent slip.

Before attempting software metrics problems, confirm you can:

1. LOC and function points measure size differently
2. Halstead metrics derive from operators and operands
3. Metrics guide quality decisions, not individual blame

Revise the solved examples in Software Engineering — Roger Pressman and one previous-year GATE or university paper for this unit.