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Software testing is the act of checking whether software satisfies expectations. Software testing can provide objective, independent information about the quality of software and the risk of its failure to a user or sponsor. [1] Software testing can determine the correctness of software for specific scenarios, but cannot determine correctness ...
The software release life cycle is the process of developing, testing, and distributing a software product (e.g., an operating system ). It typically consists of several stages, such as pre-alpha, alpha, beta, and release candidate, before the final version, or "gold", is released to the public. An example of a basic software release life cycle.
Alpha testing. Alpha testing is a technique common to older video games used to render translucent objects by rejecting pixels from being written to the framebuffer. If the alpha value of a translucent fragment (pixel) is below a specified threshold, it will be discarded.
Alpha testing is simulated or actual operational testing by potential users/customers or an independent test team at the developers' site. Alpha testing is often employed for off-the-shelf software as a form of internal acceptance testing, before the software goes to beta testing. Beta testing. Beta testing comes after alpha testing and can be ...
In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. For example, an innocent person may be convicted. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false. For example: a guilty person may be not convicted.
A statistical hypothesis test typically involves a calculation of a test statistic. Then a decision is made, either by comparing the test statistic to a critical value or equivalently by evaluating a p -value computed from the test statistic. Roughly 100 specialized statistical tests have been defined.
The Alpha test was a verbal test for literate recruits and was divided into eight test categories, which included: following oral directions, arithmetical problems, practical judgments, synonyms and antonyms, disarranged sentences, number series completion, analogies and information, whereas the Beta test was a nonverbal test used for testing ...
Uniformly most powerful test. In statistical hypothesis testing, a uniformly most powerful ( UMP) test is a hypothesis test which has the greatest power among all possible tests of a given size α. For example, according to the Neyman–Pearson lemma, the likelihood-ratio test is UMP for testing simple (point) hypotheses.