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The higher the percentage the more effective the testing. But how many defects are in the product at any given time? If each phase introduces more defects, this is a moving target. And how long are you going to wait for your customers to find all the defects you missed in testing? A month? A year? And suppose that the developers write software that has little or no defects? This means you will find little or no defects. Does that mean your testing is ineffective? Probably not, there are simply less defects to find than in a poor software product.

Consider a script-light or no-script environment. These testers don't script their cases so how can you measure their efficiency? Does this mean that they can't be efficient? I would argue they can. And what if the tests find no defects? Are they really efficient, no matter how many are written? Let's return to the purpose of testing – to identify and remove defects in software. This being the case, an efficient tester finds and removes defects more quickly than an inefficient one. The number of test cases is irrelevant.

Metrics (theoretically) allow the performance of the development cycle as a whole to be measured. They inform business and process decisions and allow development teams to implement process improvements or tailor their development strategies. Metrics are notoriously contentious however. Providing single figures for complex processes like software development can over-simplify things. There may be entirely valid reasons for one software development having more defects than another. Finding a comparative measure is often difficult and focussing on a single metric without understanding the underlying complexity risks making ill informed interpretations.

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