Software anomaly detection method and device and electronic equipment

Abstract

The invention provides a software anomaly detection method and device and electronic equipment. The method comprises the following steps: waking up a target thread every preset time unit; determining a timeout event of a to-be-tested function in the software based on the time wheel through the target thread; executing the event processing function corresponding to the to-be-tested function. In the mode, the function anomaly detection is realized based on the time wheel algorithm, the software anomaly detection performance can be improved, the software anomaly detection time precision can be increased, the detected performance loss is irrelevant to the number of tasks to be detected, and the detection of a large number of to-be-tested functions can be supported.

Description

technical field [0001] The invention relates to the technical field of software processing, in particular to a software anomaly detection method, device and electronic equipment. Background technique [0002] When the software is running, it essentially opens up threads in the process, and realizes related functions through function loops and nested operations. Generally speaking, for software anomaly detection, it is mainly to detect the timeout and deadlock of the function operation of the software. [0003] In terms of function, the above method only mentions timeout detection and deadlock detection (in fact, it is also a function that does not return after timeout), and the detection content is less. [0004] In terms of implementation, the above method maintains the running time of a function inside each function, traverses all monitoring function data structures at regular intervals, and adds 1 to its counters in turn. If there are n If the monitored function is used...

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Problems solved by technology

[0004] In terms of implementation, the above method maintains the running time of a function inside each function, traverses all monitoring function data structures at regular intervals, and adds 1 to its counters in turn. If there are n The monitoring function, the time complexity is O(n), and there may be hundreds or thousands of functions that need to be monitored during the actual software running process, the computer performance loss of the above method is relatively large

[0005] In terms of time accuracy, because the traversal itself consumes CPU (Central Processing Unit, central processing unit) and is also very time-consuming, the time accuracy of the above method is generally 1 second, which cannot achieve millisecond-level time accuracy, and the performance of the algorithm is low. poor time precision

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