(untitled) (Informatica, 2024)
With the maturity of software development models and methods, large-scale software is born. However, the current problem is the lack of a software test data management model that integrates basic data management and advanced knowledge reasoning. To solve this problem, we constructed a software test data management model based on knowledge graph, so as to realize the intelligent management and reasoning of software test data. The model adopts the entity extraction model based on feed-forward neural network, the knowledge graph integration method based on graph database, and the knowledge reasoning submodule based on deep learning. In order to validate the model effect, we evaluated the functions of the three modules separately. Specifically, the knowledge graph construction accuracy, knowledge query response time, and knowledge inference accuracy are higher than the currently existing methods.