Abstract: An embodiment of the present invention is directed to a code audit tool that intelligently analyzes and profiles code, such as Python code, based on a variety of previously unmeasured factors and metrics including a set of software dimensions, such as Algorithmic Complexities; Software Sizing Metrics; Anti-Pattern Implementations; Maintainability Metrics; Dependency Mappings; Runtime Metrics; Testing Metrics; and Security Metrics. Once this analysis is complete, a standardized report card or other scoring interface may be generated. This may include analytical findings as well as suggestions and recommend steps so that developers can make informed decisions, enhance their code bases and improve the score assigned to their code.

Abstract: Various methods, apparatuses/systems, and media for intelligent tracking of data are disclosed.

Abstract: Various methods, apparatuses/systems, and media for generating an architecture weighted scoring model are disclosed. A receiver receives a request from a user computing device to develop an application. A GUI displays a set of questions that are designed to gather meaningful information about the application to be developed by the user. A processor receives user input data on each answer to the set of questions; selects an architecture type by utilizing a first decision tree running on backend of a GUI; generates a second decision tree to select architecture layers; and generates a third decision tree to select product offerings; calculates a score for the selected architecture type based on analyzing aggregated information collected from data generated in response to user's answers and corresponding user's selection of each decision tree; checks that the architecture works; and generates an architecture weighted scoring model (AWSM) based on the calculated score.

Abstract: An embodiment of the present invention is directed to a code audit tool that intelligently analyzes and profiles code, such as Python code, based on a variety of previously unmeasured factors and metrics including a set of software dimensions, such as Algorithmic Complexities; Software Sizing Metrics; Anti-Pattern Implementations; Maintainability Metrics; Dependency Mappings; Runtime Metrics; Testing Metrics; and Security Metrics. Once this analysis is complete, a standardized report card or other scoring interface may be generated. This may include analytical findings as well as suggestions and recommend steps so that developers can make informed decisions, enhance their code bases and improve the score assigned to their code.