Abstract: A method implements input validation using mathematical expressions. The method includes receiving an input string, scanning the input string to locate a hit string matching a hit expression from a validation package, and converting the hit string to a list of values corresponding to characters from the hit string. The method further includes validating the hit string by evaluating a validation expression from the validation package using the list of values to generate a validation result and returning the validation result.

Abstract: A method includes receiving event strings from source code repositories, creating, for the source code repositories, digests of keywords, receiving log strings, and aggregating the log strings into a log group. The method further includes comparing the digests to the log group to generate scores, whereby the scores correlate the digests to the log group. The method further includes selecting a source code repository from the source code repositories according to the scores, and associating the log group to a service corresponding to the source code repository, where the source code repository corresponds to the digest with a highest score.

Abstract: A method includes receiving event strings from source code repositories, creating, for the source code repositories, digests of keywords, receiving log strings, and aggregating the log strings into a log group. The method further includes comparing the digests to the log group to generate scores, whereby the scores correlate the digests to the log group. The method further includes selecting a source code repository from the source code repositories according to the scores, and associating the log group to a service corresponding to the source code repository, where the source code repository corresponds to the digest with a highest score.

Abstract: A computing device including a processor and memory may receive input from a user to define one or more sequence types, each sequence type based on a time frame. A distributed computing system may receive interaction data on a plurality of computing nodes and describing an interaction event between a customer and an agent. The one or more computing nodes may associate the received interaction event with the customer's identifier in a customer history table, wherein the customer history table stores historical interaction events for the customer. Further, the computing nodes may assign the received interaction event to a sequence, based on the defined one or more sequence types.

Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.

Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.

Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.

Abstract: A computing device including a processor and memory may receive input from a user to define one or more sequence types, each sequence type based on a time frame. A distributed computing system may receive interaction data on a plurality of computing nodes and describing an interaction event between a customer and an agent. The one or more computing nodes may associate the received interaction event with the customer's identifier in a customer history table, wherein the customer history table stores historical interaction events for the customer. Further, the computing nodes may assign the received interaction event to a sequence, based on the defined one or more sequence types.

Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.