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Database Testing: Maximum Coverage with a Minimum of Data

Kells Irish Restaurant & Pub
112 Sw 2nd Ave
Portland, OR 97204, US (map)



Maximum Coverage with a Minimum of Data: How Equivalence Classes can be used to narrow down the amount of data needed for analysis

In Quality Assurance, an Equivalence Class is the set of all inputs that can be seen as interchangeable with one another without impacting the results of the test, where only one of them needs to be tested in order to have confidence in the test results. Automation can certainly help facilitate running all scenarios, but it isn't always possible or practical to create a completely automated test suite. This lunch time presentation is ideal for the QA Engineer who is trying create a data set and complimentary set of test cases that accurately validates the code without having to run through a seemingly endless matrix of possibilities.

When making an analysis of the behavior of a system that is based on a large set of data, you have basically three options presented: Full data-set analysis, Analysis of a randomly sampled subset of the data, or Selection of a subset of data based on Equivalence Class Elimination.

In this presentation we will talk about the pro's and con's of each approach, and then focus on how to proceed with the Equivalence Class methodology in greater detail. Please join us for this informative and interactive discussion followed by a Q&A session.