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Data collection systems are an end-product of software development. Identifying and categorizing software or a software sub-system as having aspects of, or as actually being a "Data collection system" is very important. This categorization allows encyclopedic knowledge to be gathered and applied in the design and implementation of future systems.
The C test detects one exceptionally large variance value at a time. The corresponding data series is then omitted from the full data set. According to ISO standard 5725 [6] the C test may be iterated until no further exceptionally large variance values are detected, but such practice may lead to excessive rejections if the underlying data series are not normally distributed.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, [2] and business ...
Electronic data collection may be started and stopped as one of the actions described in the test scenario. When data access is restricted, so the transfer of data between organizations may require a Data Collection Plan. This can occur with classified military systems. Data is analyzed after testing is complete.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
The identification of test relevant aspects usually follows the (functional) specification (e.g. requirements, use cases …) of the system under test. These aspects form the input and output data space of the test object. The second step of test design then follows the principles of combinatorial test design. [4]
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Test data can be generated by the tester or by a program or function that assists the tester. It can be recorded for reuse or used only once. Test data may be created manually, using data generation tools (often based on randomness), [4] or retrieved from an existing production environment. The data set may consist of synthetic (fake) data, but ...