Arial, Helvetica, sans-serif">1) Testers may wish to increase the rate of fault detection of a test suite-that is, the likelihood of revealing faults earlier in a run of regression tests during that test suite.
Some experts focus their attention on this goal. Informally, we describe this goal as one aimed at improving our test suite's rate of fault detection: we describe a specific function that quantifies this goal.
2) Testers may wish to increase the coverage of coverage code in the system under test at a faster rate, allowing a code coverage criterion to be met earlier in the test process.
3) Testers may wish to increase their confidence in the reliability of the system under test at a faster rate.
4) Testers may wish to increase the rate at which high-risk, faults are detected by a test suite, thus locating such faults earlier in the testing process.
5) Testers may wish to increase the likelihood of revealing faults related to specific code changes earlier in the regression testing process.
The above goals are stated qualitatively. To measure the success of a prioritization technique in meeting any such goal, however, we need to describe the goal quantitatively.
Pros or Motivations of meeting the very first goal:
A) An improved rate of fault detection during regression testing can let software engineers begin their debugging activities earlier than might otherwise be possible, speeding the release of the software.
B) An improved rate of fault detection can also provide faster feedback on the system under test, and provider earlier evidence when quality goals have not been met, allowing strategic decisions about release schedules to be made earlier than might otherwise he possible.
Few Cons too are like:
In a testing situations where the amount of available testing time is uncertain (for example, when market pressures may force a release of the producer prior to execution of all test cases), such prioritization can increase the likelihood that whenever the testing process is terminated, testing resources will have been spent more cost-effectively in relation to potential fault detection than they might otherwise have been.
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