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A Cross-Project Software Aging Defect Prediction Method

A software aging and prediction method technology, applied in software testing/debugging, computer components, error detection/correction, etc., can solve problems such as overfitting, large difference in prediction effect, and reduce migration effect, so as to avoid loss, The effect of improving prediction accuracy and strong robustness

Active Publication Date: 2022-06-03
WUHAN UNIV OF TECH
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Problems solved by technology

However, in the traditional method, only the difference of marginal distribution is considered, and the difference of conditional distribution is not considered, which reduces the transfer effect
And only using the oversampling method to deal with the class imbalance problem can easily lead to overfitting, which is not robust enough for different machine learning classifiers, that is, the prediction effect is quite different

Method used

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  • A Cross-Project Software Aging Defect Prediction Method
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  • A Cross-Project Software Aging Defect Prediction Method

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Embodiment Construction

[0018] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0021] Step 1, data preprocessing is carried out to the data of the source item and the target item.

[0022] Data preprocessing mainly refers to the standardization of data. This method is often used to assign all features with the same weight

[0023]

[0025] Step 2, using Joint Distribution Domain Adaptation (JDA) to reduce data distribution differences.

[0028] Maximum Mean Difference (MMD) is used to represent this distance. Our goal is to find the transform A such that the transformed edge

[0030]

[0032]

[0034]

[0036]

[0038]

[0039] s.t.A

[0040] Wherein represents the regular term, H represents the center matrix, and I represents the identity matrix. By using Laplace's square

[0041]

[0042] where φ represents the Laplacian kernel. Transform A is calculated.

[0046]

[0048]

[0050]

[0052] Step 4, using machine learning method to ...

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Abstract

The invention discloses a cross-project software aging prediction method. First, the data in the source project and the target project are preprocessed, and then the joint distribution domain is used to adapt to reduce the difference between the marginal distribution and the conditional distribution, and then the undersampling method and the improved The subclass discriminant analysis method alleviates the class imbalance problem, and finally uses a machine learning classifier (logistic regression, etc.) to make predictions. The invention considers the conditional distribution difference between the source item and the target item of the software aging defect data set, and further adopts an improved subclass discriminant analysis method to alleviate the extremely serious class imbalance problem. It solves the problem of low accuracy and robustness of traditional cross-project software aging defect prediction methods, and helps developers find and remove software aging-related defects during the development and testing phase, avoiding losses caused by software aging problems. The feasibility of the invention has been verified on real software, and can be extended to other software to predict defects related to software aging.

Description

A cross-project software aging defect prediction method technical field [0001] The invention belongs to the technical field of software processing, and in particular relates to a cross-project software aging defect prediction method. Background technique In long-running operating systems, software aging is the main cause of system performance degradation or software crashes. because. It is caused by software Aging-Related Bugs (ARBs) such as memory leaks, unreleased files locks, storage issues, etc. And it has been found to exist in various systems, such as Android, Linux, Windows, etc. software aging Its complexity and time characteristics make its detection very difficult. Therefore, predict and remove software during the development and testing phase (code level) Aging-related defects are one of the important ways to reduce the loss caused by software aging. [0003] In recent years, aging defect prediction has gradually attracted the attention of scholars in ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/36G06K9/62G06N20/00
CPCG06F11/3672G06N20/00G06F18/24G06F18/214
Inventor 向剑文徐斌贾凯赵冬冬
Owner WUHAN UNIV OF TECH
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