The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.

This paper presents the operational difference technique for generating, augmenting, and minimizing test suites. The technique is analogous to structural code coverage techniques, but it operates in the semantic domain of program properties rather than the syntactic domain of program text. The operational difference technique automatically selects test cases; it assumes only the existence of a source of test cases. The technique dynamically generates operational abstractions (which describe observed behavior and are syntactically identical to formal specifications) from test suite executions. Test suites can be generated by adding cases until the operational abstraction stops changing. The resulting test suites are as small, and detect as many faults, as suites with 100% branch coverage, and are better at detecting certain common faults. This paper also presents the area and stacking techniques for comparing test suite generation strategies; these techniques avoid bias due to test suite size.