Abstract: A test case identification system that may tokenize natural language input and correlate the resultant set of tokens to a plurality of test cases for identification of a test case from the plurality of test cases. The identified test cases may be scored based upon historical information, quantification metrics and number of search token matches in order to identify a test case to a user. The results of the tokenization, correlation and identification may be stored in a master library for utilization in future identification efforts.

Abstract: Systems and methods of generating a computer program using artificial intelligence module include generating logic programming by analyzing natural language in sample input data received from an external source, the sample input data resulting in a known output. Select input data, which includes select natural language or a coding instruction including the select natural language, is received. Context data is generated by processing the select natural language. The logic programming based on the context data is selected. A computing instruction is determined for the select input data using the logic programming, and the computer program including the computing instruction is generated.

Abstract: A computerized system converts a webpage built on a legacy framework to a target framework. The system allows a user to identify and download one or more webpages for conversion. The system converts the webpage to XML and outputs in a data store, such as an XML file. The system parses and converts the XML file into big object file. The system, through conversion logic, converts the big object file into a target component market. The system then reports the conversion, including any processing logs and error files, to a user. The system report include highlighted errors from any step of the conversion along with automatically generated recommendations for error corrections.