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Both positive and negative testing play an important role. Positive testing ensures that the application does what it is implied for and performs each function as expected. Negative testing is opposite of positive testing. Negative testing discovers diverse approaches to make the application crash and handle the crash effortlessly. Example
This article discusses a set of tactics useful in software testing.It is intended as a comprehensive list of tactical approaches to software quality assurance (more widely colloquially known as quality assurance (traditionally called by the acronym "QA")) and general application of the test method (usually just called "testing" or sometimes "developer testing").
The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
[1] [2] For example, the happy path for a function validating credit card numbers would be where none of the validation rules raise an error, thus letting execution continue successfully to the end, generating a positive response. Process steps for a happy path are also used in the context of a use case. In contrast to the happy path, process ...
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
Precision and recall. In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly ...
The common practice of allowing a 5-10 percent margin for late execution reduces the potential number of false negatives in test execution. It is also suggested to treat test code with the same respect as production code. Test code must work correctly for both positive and negative cases, last a long time, and be readable and maintainable.
Regression testing is performed when changes are made to the existing functionality of the software or if there is a bug fix in the software. Regression testing can be achieved through multiple approaches; if a test all approach is followed, it provides certainty that the changes made to the software have not affected the existing functionalities, which are unaltered.