Mulr4FL: Effective Fault Localization of Evolution Software Based on Multivariate Logistic Regression Model

Ju, Xiaolin; Qian, Jie; Chen, Zhihua; Zhao, Chunyu; Qian, Junyan

doi:10.1109/access.2020.3037235

Cited by 4 publications

(3 citation statements)

References 57 publications

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“…Later in 2020, Peng [9] wrote an article on the Internet financial platform based on 5G network. Ju et al [10] explained the effective fault localization of evolution software which is based on the multivariate logistic regression model, Wang et al [11] adopted the forward local push with its parallelization for accurate and fast SimRank computation, Chang et al [12] worked for the person reidentification and proposed a transductive semisupervised metric learning. Deng et al [13,14] proposed some enhanced and evolutionary algorithms for optimization problems.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Relevant Customer Identification Algorithm Based on the Internet Financial Platform

Yangyudongnanxin

2021

Journal of Mathematics

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In order to improve the intelligent search capabilities of Internet financial customers, this paper proposes a search algorithm for Internet financial data. The proposed algorithm calculates the customers corresponding to the two selected financial platforms based on the candidate customer set selected from the seed dataset and combined with the restored social relationship. Moreover, it also calculates the similarity of each field between the pairs. Furthermore, this article proposes an entity customer classification model based on logistic regression. Through the SNC model, threshold propagation, and random propagation, the model is transformed into an algorithm that identifies the associated customers, eliminates redundant customers, and realizes associated user identification. Experimental results verify that pruning increases the accuracy of identifying related customers by 8.44%. The average sampling accuracy of the entire customer association model is 79%, the lowest accuracy is 40%, and the highest is 1. From the sampling results, the overall recognition effect of the model reaches the expected goal.

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Section: Literature Reviewmentioning

confidence: 99%

“…When conducting customer confirmation, the confirmation classification is considered to be a two-point issue; that is, it is confirmed that the same entity customers are a two-point issue. e logistic regression (LR) [10]…”

Section: Logic Regressionmentioning

confidence: 99%

A Relevant Customer Identification Algorithm Based on the Internet Financial Platform

Yangyudongnanxin

2021

Journal of Mathematics

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“…To improve the effectiveness of fault localization, Wang, Wu & Liu (2021) used a clustering-based technique to identify coincidentally correct test cases from passed test suites and empirically quantified the accuracy of identifying coincidentally correct test cases to assess its effectiveness. A framework for fault localization using a multivariate logistic regression model that combines static and dynamic features collected from the program being debugged by Ju et al (2020) . Ghosh & Singh (2021b) proposed an automated framework using chaos-based genetic algorithm for multi-fault localization based on SBFL technique.…”

Section: Related Workmentioning

confidence: 99%

The improved dynamic slicing for spectrum-based fault localization

Cao

Wang

Deng

et al. 2022

PeerJ Computer Science

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Background Spectrum-based Fault localization have proven to be useful in the process of software testing and debugging. However, how to improve the effectiveness of software fault localization has always been a research hot spot in the field of software engineering. Dynamic slicing can extract program dependencies under certain conditions. Thus, this technology is expected to benefit for locating fault. Methods We propose an improved dynamic slicing for spectrum-based fault localization under a general framework. We first obtain the dynamic slice of program execution. Secondly, we construct a mixed slice spectrum matrix from the dynamic slice of each test case and the corresponding test results. Finally, we compute the suspiciousness value of each statement in the mixed-slice spectram matrix. Results To verify the performance of our method, we conduct an empirical study on 15 widely used open-source programs. Experimental results show that our approach achieves significant improvement than the compared techniques. Conclusions Our approach can reduce approximately 1% to 17.79% of the average cost of code examined significantly.

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A fault diagnosis method with multi-source data fusion based on hierarchical attention for AUV

et al. 2022

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Mulr4FL: Effective Fault Localization of Evolution Software Based on Multivariate Logistic Regression Model

Cited by 4 publications

References 57 publications

A Relevant Customer Identification Algorithm Based on the Internet Financial Platform

A Relevant Customer Identification Algorithm Based on the Internet Financial Platform

The improved dynamic slicing for spectrum-based fault localization

A fault diagnosis method with multi-source data fusion based on hierarchical attention for AUV

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