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Impact of Code Coverage Analysis on ROI

It might be difficult to link Code Coverage Analysis directly to the Return On Investment. How ever, as ROI is more or less related to the improved productivity, the path for calculating ROI from code coverage analysis would be

Code Coverage Analysis -> Improved Productivity -> Impact on ROI

To improve the productivity using Code Coverage Analysis, you might start defining some steps like

  • Introducing a Level 0 test (smoke test) which should focus on coverage than on functionality. (For eg, If you have N modules, the Level 0 tests will do a quick check on most or all of them, before going to detailed functionality tests)
  • Identifying and removing redundant test cases covering the same code
  • Find an optimum percentage of coverage, that gives you maximum test efficiency (As a standard, somewhere around 60% of code coverage will give you maximum testing productivity)

These days, various automated code coverage checks are available with in various IDEs.

Fig: Visual Sudio Code Coverage provides both a visual tool as well as tabular metrics on the effectiveness of your unit tests.

Maximum testing productivity will provide you the maximum number of bugs in least time.

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