Abstract: Discrete sets of data are divided into collections in accordance with strata delineated along multiple dimensions of data. Each dimension of data represents criteria to be evaluated and the stratification of a dimension is based on a distribution of the discrete sets of data along such a dimension. Once divided into the multidimensional strata, one or more discrete sets of data are randomly selected from each stratum and are provided to human judges to generate corresponding classifications of such a discrete set of data. Such human-generated classifications are compared with computer-generated classifications associated with the same discrete sets of data for purposes of evaluating the computer-implemented functionality generating such classifications. Such human-generated classifications are also associated with the corresponding discrete sets of data for purposes of training, and thereby improving, computer-implemented functionality.

Abstract: One particular technique includes storing logic expressions in a data file. This particular technique also includes executing application code. The executing provided by this particular technique includes receiving a query, reading an individual logic expression from the data file, processing the query using the individual logic expression to determine a query result, and providing the query result in response to the query.

Abstract: The described implementations relate to computer programming. One implementation provides a technique that can include storing logic expressions in a data file. The technique can also include executing application code. The executing can include receiving a query, reading an individual logic expression from the data file, processing the query using the individual logic expression to determine a query result, and providing the query result in response to the query.