Anomaly in software

From Wikipedia, the free encyclopedia

This article may require cleanup to meet Wikipedia's quality standards.
Please improve this article if you can. (April 2008)

Look up anomaly in
Wiktionary, the free dictionary.

In software testing an anomaly is anything that differs from expectation.^[1] This expectation can result from many things like from a document (e.g. the expected behaviour is not always written down explicitly, so the developer may implement it differently) or from a person's view (e.g. the person has different opinion regarding usability) or experiences (e.g. the specification is not clear on one thing and the person also knows competitor products, where such a feature is implemented or where the tested software behaves different than these).

1 Examples for anomalies
2 See also
3 References
4 External links

An anomaly also can point to a new feature or an usability problem, because the software may be correct with respect to the specification, but has room for improvement.

Another possibility for an anomaly is that a tester executed the test case incorrectly and therefore the expected result is also incorrect (Garbage In, Garbage Out). Some other common terms for software anomalies are: bug, fault, failure, error, defect, problem, deviation, glitch, incident, crash. According to IEEE, the word anomaly should be favored because it has a more neutral meaning.

'Software' in this article is more than just source code.^[2] It also refers to: programs, procedures and documentation, and data for the concerning processing on a computer system. Testing software ("testware") is also regarded as software in this context.

The time and place of anomalies can be pretty anywhere in the (Software development life cycle) - it should not be seen from end user perspective only. Most people see anomalies (e.g. failures) during analytical quality assurance measures, but in fact the reason for this anomaly probably occurred earlier. This is why preventive quality assurance are more important: anomalies are found earlier, which can result in lower costs.