Abstract: A system and method for optimized processing of requirements data in a software development life cycle is provided. The present invention provides for determining a first pre-defined parameter, a second pre-defined parameter, a third pre-defined parameter, a fourth pre-defined parameter, a fifth pre-defined parameter, a sixth pre-defined parameter, and a seventh pre-defined parameter associated with user story by applying pre-defined rules respectively. Further, an output is rendered as Requirement Completeness Index (RCI) for user story data, and corrective actions are automatically carried out on user story data based on the generated RCI.

Abstract: The present invention relates to a system and method for application debt management with zero maintenance strategy that make the applications “fit for use” and “fit for purpose”. The objective is to ensure that applications run at the lowest cost, deliver maximum performance and serve the purpose for which it was developed. The machine learning enabled debt engine of present system reads the unstructured ticket data or debts, eliminates noise, and classify the debts into one of predefined categories. This is followed by remediation of debt via either of automation or healing workbench based on predetermined priorities.

Abstract: The present invention relates to a system and method for application debt management with zero maintenance strategy that make the applications “fit for use” and “fit for purpose”. The objective is to ensure that applications run at the lowest cost, deliver maximum performance and serve the purpose for which it was developed. The machine learning enabled debt engine of present system reads the unstructured ticket data or debts, eliminates noise, and classify the debts into one of predefined categories. This is followed by remediation of debt via either of automation or healing workbench based on predetermined priorities.