Software performance abnormal condition detection method and detection device
A software performance and detection method technology, applied in software testing/debugging, hardware monitoring, computer components, etc., can solve the problems of software performance failure features not prominent, data sets with too much noise, etc., to solve software performance failure features not prominent , solve the effect of excessive noise and improve accuracy
Pending Publication Date: 2022-04-12
BEIHANG UNIV
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[0006] The embodiment of the present application provides a related technical solution for improving the detection accuracy of software performance abnormalities, which is used to solve technical problems such as excessive noise in the data set of software performance failure characterization elements and software performance failure characteristics are not prominent.
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[0056]In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments of the present application and corresponding drawings. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.
[0057] Please refer to figure 1 , a method for detecting abnormalities in software performance provided by the present application, comprising the following specific steps:
[0058] S100: Collect data of attributes representing operating conditions when the target software is running, to obtain a first data set.
[0059] It is understandable that the...
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The invention discloses a method and a device for detecting abnormal conditions of software performance. The method for detecting the abnormal condition of the software performance comprises the following steps: collecting data representing attributes of a running condition when target software runs, so as to obtain a first data set; screening out elements which do not meet a preset colinearity condition in the first data set according to a multi-colinearity test standard to obtain a second data set; according to the waveform characteristics of the key performance elements, performing noise reduction processing on the second data set through an adaptive discrete wavelet decomposition method to obtain a third data set; training an anomaly detection model by using the third data set to obtain a software performance anomaly detection model; and detecting to-be-detected target software through the software performance anomaly detection model to obtain a detection result. According to the method, the problems that noise is too much and software performance failure characteristics are not prominent are effectively solved by combining and using a multi-collinearity inspection standard, a self-adaptive discrete wavelet decomposition method and an anomaly detection model, so that the accuracy of software detection is improved.
Description
technical field [0001] The present application relates to the technical field of software detection, and in particular to a detection method and detection device for abnormal software performance. Background technique [0002] At present, with the rapid development of computer technology and Internet technology, the functional requirements and performance requirements of software are gradually increasing, and the complexity of software is also increasing rapidly. How to ensure the reliability of complex software runtime is a hot research field. Because the software itself has defects that are not suitable for detection and new defects will be introduced continuously in version updates, these defects will be activated during the long-term running of the software. Activated flaws lead to cumulative software failures. At the same time, an unreasonable resource scheduling mechanism will also lead to continuous consumption or even exhaustion of system resources. Software will ...
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Login to View More IPC IPC(8): G06F11/30G06F11/36G06F17/14G06K9/62
Inventor 艾骏王曙光孔士溢陆民燕龚屹昂
Owner BEIHANG UNIV