Conformance Corpus Targets CellML 2.0 Tool Disagreements Over Real Number Validity

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CellML is an XML format for describing biological mathematical models, and researchers rely on multiple tools agreeing on which models are valid. Each implementation typically tests only against its own reading of the specification, so differing interpretations can go unnoticed until a model is accepted by one tool and rejected by another. The author built the CellML 2.0 Conformance Corpus, a shared set of test files whose expected verdicts derive from the specification text, drawing on the earlier cellml-validation project for CellML 1.x. The first slice covers real-number edge cases, such as leading plus signs, digitless strings, empty values, and out-of-range numbers, across five places where real numbers may appear. Each file tests a single rule, paired with a valid control, and files the spec leaves undecided are placed in a separate category that does not score tools. An independent grammar-based self-check verifies the expected verdicts.

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