Abstract: Metadata associated with at least one field defined in a user interface is identified. The metadata associated with the field defined in the user interface is processed to identify at least one characteristic of the field defined in the user interface. Based on the characteristic(s), a test string is generated for use as an input into the field defined in the user interface to perform validation on the field.

Abstract: Metadata associated with at least one field defined in a user interface is identified. The metadata associated with the field defined in the user interface is processed to identify at least one characteristic of the field defined in the user interface. Based on the characteristic(s), a test string is generated for use as an input into the field defined in the user interface to perform validation on the field.

Abstract: Metadata associated with at least one field defined in a user interface is identified. The metadata associated with the field defined in the user interface is processed to identify at least one characteristic of the field defined in the user interface. Based on the characteristic(s), a test string is generated for use as an input into the field defined in the user interface to perform validation on the field.

Abstract: Metadata associated with at least one field defined in a user interface is identified. The metadata associated with the field defined in the user interface is processed to identify at least one characteristic of the field defined in the user interface. Based on the characteristic(s), a test string is generated for use as an input into the field defined in the user interface to perform validation on the field.

Abstract: Disclosed herein are techniques for determining a most relevant data measurement from among competing data points. Particular embodiments call for an evaluation engine to receive as input from an underlying database, a plurality of competing data points together with meta-data reflecting a provenance of those data points. The evaluation engine is configured to apply a precedence rule set to the input, and produce an output comprising a most relevant data measurement. Via application of the precedence rule set, the evaluation engine may consider expected reliability of the source of the data measurement. The precedence rule set may also reflect other factors, such as a number of alternative sources for the measurement, a freshness of the measurement, and/or a possibility of combining (e.g. averaging) a plurality of otherwise equally situated measurements. An example evaluates the statistics of pro football prospects (e.g. foot speed) available from different sources (e.g. scouting reports).