Heterogeneous Cross-Project Software Defect Prediction Method Based on Kernel Mapping Migration Integration

A software defect prediction, cross-project technology, applied in the field of software defect prediction, can solve the problems of not considering the coverage of the common feature subspace, and the prediction performance of the prediction method is difficult to achieve the prediction effect.

Active Publication Date: 2020-09-08
BEIHANG UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] (3) No consideration of covering the optimal common feature subspace through multiple subspaces
[0007] Therefore, the above...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Heterogeneous Cross-Project Software Defect Prediction Method Based on Kernel Mapping Migration Integration
  • Heterogeneous Cross-Project Software Defect Prediction Method Based on Kernel Mapping Migration Integration
  • Heterogeneous Cross-Project Software Defect Prediction Method Based on Kernel Mapping Migration Integration

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0051] refer to figure 1 As shown, the heterogeneous cross-project software defect prediction method based on nuclear mapping migration integration provided by the embodiment of the present invention includes: S1-S4;

[0052] S1. Preprocessing the source data based on the over-sampling unbalanced learning process; the source data is the historical defect data of the software project;

[0053] S2. Construct an objective function ac...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a heterogeneous cross-project software defect prediction method based on nuclear spectrum mapping migration integration, which includes preprocessing source data based on an over-sampling unbalanced learning process; the source data is historical defect data of software projects; According to the difference information between the source data and the target data distribution, and the information loss caused by spectral mapping, the target function is constructed; the target data is the heterogeneous cross-project software to be predicted; the original space is mapped to multiple high-level by multi-core learning dimensional space, optimize the objective function on each high-dimensional space to find the optimal common subspace, train a classifier on each common subspace; use ensemble learning to comprehensively integrate all the classifiers , generate a prediction model; predict the label of the target data according to the prediction model. This method has a higher defect prediction accuracy and is beneficial to improve the work efficiency of software testing.

Description

technical field [0001] The invention relates to the technical field of software defect prediction, in particular to a heterogeneous cross-project software defect prediction method based on nuclear spectrum mapping migration integration. Background technique [0002] Software defect prediction refers to using the historical defect data of a given software project to find the mapping relationship between software module metrics and software defects through statistical or machine learning methods, and then predict the defect status of new modules of the project. If there is not enough historical defect data, it is necessary to utilize cross-project software defect prediction techniques. Cross-project software defect prediction refers to the use of historical defect data (source data) of other software projects to establish a prediction model, and then use it for new software projects (target data) to predict its defect status. Cross-project software defect prediction can be di...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F11/36G06K9/62
CPCG06F11/366G06F18/241
Inventor 王世海李成群何俊秀秦庆强童浩楠
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap