Abstract: A multi-feature log anomaly detection method includes steps of: preliminarily processing a log data set to obtain a log entry word group corresponding to all semantics of a log sequence in the log data set, and using the log entry word group as a semantic feature of the log sequence; extracting a type feature, a time feature and a quantity feature of the log sequence, and encoding the semantic feature, the type feature, the time feature and the quantity feature into a log feature vector set of the log sequence; training a BiGRU neural network model with all log feature vector sets to obtain a trained BiGRU neural network mode; and inputting the log data set to be detected into the trained BiGRU neural network model for prediction, and determining whether the log sequence is a normal or abnormal log sequence according to a prediction result.

Abstract: A device and a method are provided to automatically generate test case for embedded software. This invention is in software test field, including symbolic execution kernel module, path selection module, solver, debugger, concrete execution kernel module and debugger agent module. The tested software and test cases are uploaded from the host system to the embedded system through debugger and debugger agent. The concrete execution kernel module starts the tested software. The symbolic execution kernel module captures the run-time information of the tested software through the debugger. When the tested software operates on the symbol source, the symbolic execution kernel module marks the symbol source, tracks the symbol propagation, generates path condition and sends the path condition to path selection module. This invention can automatically generate test cases for embedded software, which doesn't need the source code of the tested software and can be conveniently used for commercial software.

Abstract: A device and a method are provided to automatically generate test case for embedded software. This invention is in software test field, including symbolic execution kernel module, path selection module, solver, debugger, concrete execution kernel module and debugger agent module. The tested software and test cases are uploaded from the host system to the embedded system through debugger and debugger agent. The concrete execution kernel module starts the tested software. The symbolic execution kernel module captures the run-time information of the tested software through the debugger. When the tested software operates on the symbol source, the symbolic execution kernel module marks the symbol source, tracks the symbol propagation, generates path condition and sends the path condition to path selection module. This invention can automatically generate test cases for embedded software, which doesn't need the source code of the tested software and can be conveniently used for commercial software.