System for understanding navigational semantics via hypothesis generation and contextual analysis

Abstract

A system for understanding navigational semantics via hypothesis generation and contextual analysis is disclosed. The system may, such as when examining and testing a software application, address the handling and resolution of constraint hypotheses in an uncertain environment, where potentially overlapping or conflicting suggestions are generated with various confidences. The system may utilize algorithmic and/or machine learning tools to identify consistent constraints for the software application with the highest levels of confidence. During operation, the system may continuously perform hypothesis testing on constraints generated by the system, which may result in the creation of new hypotheses yielding improved confidences. Feedback from the hypothesis testing may be provided to knowledge sources to improve the processing of information subsequently processed by the system. The system may construct complex constraints on multiple fields or functional transitions with associated confidences. A constraint optimizer of the system may simplify constraints or reduce their quantities.