A software aging prediction method and device based on multi-model comparison

An aging prediction and software aging technology, applied in software testing/debugging, kernel methods, biological neural network models, etc., can solve problems affecting decision-making, reduce performance degradation or crash, alleviate impact, and improve reliability

Active Publication Date: 2022-05-06
WUHAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the above defects or improvement needs of the prior art, the present invention proposes a software aging prediction method and device based on multi-model comparison, which solves the problem that the prediction result of a single model may affect decision-making, and can be based on aging data characteristics and prediction The error automatically selects the appropriate model, avoiding the early or late execution of proactive maintenance measures, and reducing the impact on software reliability

Method used

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  • A software aging prediction method and device based on multi-model comparison
  • A software aging prediction method and device based on multi-model comparison
  • A software aging prediction method and device based on multi-model comparison

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Embodiment 1

[0041] A software aging prediction method based on multi-model comparison of the present invention includes three parts: a data collection process, a prediction process and a verification process;

[0042] The data collection process collects aging index data from the target system to form a data set with a time index;

[0043] The prediction process includes a series of machine learning and neural network models, and candidate models are selected according to the data characteristics and prediction error results of the data in the data set;

[0044] The validation process uses non-parametric testing methods to test the candidate model and other models to determine the final aging prediction model.

[0045] Such as figure 1Shown is a schematic flowchart of a software aging prediction method based on multi-model comparison provided by an embodiment of the present invention, including the following steps:

[0046] S1: Collect the original data of aging indicators of the target...

Embodiment 2

[0081] Such as Figure 7 Shown is a schematic structural diagram of a device provided by an embodiment of the present invention, including: a data acquisition module 701, a prediction module 702, and a verification module 703;

[0082] The data acquisition module 701 is used to collect the original data of the aging index from the target software system, and process the original data of the aging index into time series data to form a data set;

[0083] The prediction module 702 is used to design several aging prediction models for the scale of aging data, use the data set as the input of each aging prediction model, and calculate the prediction error of each aging prediction model, and select the smallest prediction error and the best fitting effect. A good aging prediction model is used as a candidate aging prediction model;

[0084] The verification module 703 is used to calculate whether there is a significant difference between the candidate aging prediction model and oth...

Embodiment 3

[0092] The present application also provides a computer-readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Programmable Read-Only Memory (PROM), Magnetic Storage, Magnetic Disk, Optical Disk, Server, App Store, etc., on which computer programs, program When executed by the processor, the software aging prediction method based on multi-model comparison in the method embodiment is implemented.

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Abstract

The invention discloses a software aging prediction method and device based on multi-model comparison, belonging to the field of software aging, collecting aging indicators from target software systems, processing them into time series data as pre-input of models; aiming at aging data scale, designing Including the aging prediction model of machine learning and neural network, calculate the prediction error of each model, select the model with the smallest error as the candidate model; calculate whether there is a significant difference between the model and other models, if the difference is obvious, select the model for the final aging prediction model. The invention solves the problem that the prediction result of a single model may affect the decision-making, and the user can automatically select a suitable model according to the characteristics of aging data and prediction errors, avoiding the early or late implementation of proactive maintenance measures and reducing the reliability of the software. sexual influence. More models can be expanded, and the optimal prediction model can be selected for different aging data scales to help system operation and maintenance.

Description

technical field [0001] The invention belongs to the field of software aging, and more specifically relates to a software aging prediction method and device based on multi-model comparison. Background technique [0002] For various system software, such as Linux operating system, Apache server, middleware, J2EE application server, software system under the Internet of Things environment and various mobile devices, during the long-term running process, due to the accumulation of errors and the consumption of resources The resulting degradation in performance and eventually crashes is known as software aging. Software aging prediction is widely used as a proactive maintenance technique for software regeneration. This predictive approach can extrapolate and predict future states based on the current or past states of the system. Estimate next-state system resource usage by using techniques such as machine learning or time-series methods. This predictive mode estimates when sy...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/36G06N20/10G06N3/04
CPCG06F11/3668G06N20/10G06N3/044G06N3/045
Inventor 向剑文贾凯李滴萌赵冬冬
Owner WUHAN UNIV OF TECH
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