Abstract: A method for reducing the carbon footprint of a software application during a test phase including calculating a unitary carbon footprint of each application scenario of a determined set of application scenarios, estimating the number of executions of the each application scenario of the determined set of application scenarios over a predetermined period of time, calculating a total carbon footprint of the each application scenario over the predetermined period of time using the unitary carbon footprint that is calculated and the number of executions that is estimated of the each application scenario. The method also includes determining a subset of the set of application scenarios using at least the total carbon footprint of the each application scenario, and modifying or removing from the software application at least one application scenario of the subset to reduce the carbon footprint of the software application.

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: 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.