Unsupervised software aging detection method based on data flow local outlier factor

An outlier factor and software aging technology, applied in software testing/debugging, electrical digital data processing, error detection/correction, etc.

Active Publication Date: 2021-04-27
GUANGXI NORMAL UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0005] What the present invention aims to solve is the problem that the existing software aging detection method ignores the external influence on aging detection and easily produces aging false alarms, and provides an unsupervised software aging detection method based on the local outlier factor of the data stream

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  • Unsupervised software aging detection method based on data flow local outlier factor
  • Unsupervised software aging detection method based on data flow local outlier factor
  • Unsupervised software aging detection method based on data flow local outlier factor

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Embodiment Construction

[0029] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific examples.

[0030] An unsupervised software aging detection method based on data flow local outlier factors, which specifically includes the following steps:

[0031] Step 1. Continuously collect the attribute parameters of the software system at various moments, wherein the attribute parameters include inherent attributes and environmental attributes; treat the attribute parameters at each moment as a data object, and thus obtain the data object flow.

[0032]In this embodiment, the collected attribute parameters include load rate, response time, existence time and space distance, wherein the load rate and response time are selected as inherent attributes, and the existence time and space distance are selected as environmental attributes.

[0033] In order to prevent the magnitude i...

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Abstract

The invention discloses an unsupervised software aging detection method based on a data flow local outlier factor, which abandons the unlike binary attribute of the detection result of the existing algorithm, and utilizes the local outlier factor of the flow data to represent the aging degree of a software system at each moment. Therefore, the aging degree of the software system at each moment can be visually displayed through a specific numerical value. Meanwhile, the influence of external environment factors of the software system on aging state detection of the software system is also considered. Therefore, when the local outlier coefficient of the streaming data is calculated, the attributes of the monitoring data are divided into inherent attributes and environment attributes. Secondly, performing nearest neighbor search on the tested data by using the environmental parameters, and calculating a local outlier coefficient of the tested data by using the intrinsic attribute parameters; compared with a supervised detection algorithm, the method has the advantages that rules are directly searched in the data set without marking the training data set, and the method belongs to the category of unsupervised learning.

Description

technical field [0001] The invention relates to the technical field of software aging detection, in particular to an unsupervised software aging detection method based on local outlier factors of data streams. Background technique [0002] Aging is a ubiquitous and inevitable phenomenon in nature, and computer software, as a product of human thinking, also has aging phenomena. Software Aging (Software Aging) refers to the degradation of performance, degradation of service quality, and even system hang-ups caused by the continuous increase of running time, system resource consumption, or accumulation of runtime errors in a software system in an open environment. Phenomenon. Software aging is not a sudden event. Through the monitoring and analysis of system performance parameters, it can be found that their performance parameters will change with a certain trend during the operation of the system with software aging, and thus gradually deviate from the normal state. track. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/36
CPCG06F11/3668Y02D10/00
Inventor 钟子力梁媛苏书宾李先贤
Owner GUANGXI NORMAL UNIV
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