Today, code for input data validation is typically written manually in an ad-hoc manner. For commonly-used electronic data formats, input validation is, at a minimum, a problem of scale whereby specifications of these formats comprise hundreds to thousands of pages. Input validation thus translates to thousands or more conditions to be checked against the input data before the data can be safely processed. Manually writing the code to parse and validate input, and then manually auditing whether that code implements all the necessary checks completely and correctly, does not scale. Moreover, manual parser coding and auditing typically fails even for electronic data formats specifically designed to be easier to perform such tasks, e.g., JSON and XML. A variety of critical vulnerabilities have been found in major parser implementations for these formats.