A Distance-Based Dynamic Random Testing with Test Case Clustering

Hanyu Pei; Beibei Yin; Kai-Yuan Cai; Min Xie

doi:10.1109/QRS.2019.00019

A Distance-Based Dynamic Random Testing with Test Case Clustering

Hanyu Pei, Beibei Yin, Kai-Yuan Cai, Min Xie

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

One goal of software testing strategies is to detect faults faster. Dynamic Random Testing (DRT) strategy uses the testing results to guide the selection of test cases, which have shown to be effective in the fault detection process. However, the effectiveness of DRT still can be improved. In this paper, a distance-based DRT (D-DRT) strategy is proposed. The vectorized test cases are partitioned with k-means clustering method to obtain better classification, and the distance information are used to guide the test case selection, then the test cases that are close to failure-causing test cases are more likely to be selected, thus the testing process can be optimized. In the case study, the performance of D-DRT and other testing strategies are compared. The experiment results show that the proposed D-DRT strategy has better fault detection effectiveness than the others without significant increase in computational cost.

Original language	English
Title of host publication	19^th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019
Subtitle of host publication	Proceedings
Publisher	IEEE
Pages	46-53
ISBN (Electronic)	978-1-7281-3927-2
ISBN (Print)	978-1-7281-3928-9
DOIs	https://doi.org/10.1109/QRS.2019.00019
Publication status	Published - Jul 2019
Event	19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019 - Sofia University, Sofia, Bulgaria Duration: 22 Jul 2019 → 26 Jul 2019 https://qrs19.techconf.org/

Publication series

Name	Proceedings - IEEE International Conference on Software Quality, Reliability and Security, QRS
Publisher	IEEE

Conference

Conference	19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019
Place	Bulgaria
City	Sofia
Period	22/07/19 → 26/07/19
Internet address	https://qrs19.techconf.org/

Research Keywords

dynamic random testing
k-means clustering
software cybernetics
test case distance
testing profile

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Pei, H., Yin, B., Cai, K.-Y., & Xie, M. (2019). A Distance-Based Dynamic Random Testing with Test Case Clustering. In 19^th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019: Proceedings (pp. 46-53). Article 8854733 (Proceedings - IEEE International Conference on Software Quality, Reliability and Security, QRS). IEEE. https://doi.org/10.1109/QRS.2019.00019

@inproceedings{ed9ccc33612a443fb284df58632acb37,

title = "A Distance-Based Dynamic Random Testing with Test Case Clustering",

abstract = "One goal of software testing strategies is to detect faults faster. Dynamic Random Testing (DRT) strategy uses the testing results to guide the selection of test cases, which have shown to be effective in the fault detection process. However, the effectiveness of DRT still can be improved. In this paper, a distance-based DRT (D-DRT) strategy is proposed. The vectorized test cases are partitioned with k-means clustering method to obtain better classification, and the distance information are used to guide the test case selection, then the test cases that are close to failure-causing test cases are more likely to be selected, thus the testing process can be optimized. In the case study, the performance of D-DRT and other testing strategies are compared. The experiment results show that the proposed D-DRT strategy has better fault detection effectiveness than the others without significant increase in computational cost.",

keywords = "dynamic random testing, k-means clustering, software cybernetics, test case distance, testing profile",

author = "Hanyu Pei and Beibei Yin and Kai-Yuan Cai and Min Xie",

year = "2019",

month = jul,

doi = "10.1109/QRS.2019.00019",

language = "English",

isbn = "978-1-7281-3928-9",

series = "Proceedings - IEEE International Conference on Software Quality, Reliability and Security, QRS",

publisher = "IEEE",

pages = "46--53",

booktitle = "19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019",

address = "United States",

note = "19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019 ; Conference date: 22-07-2019 Through 26-07-2019",

url = "https://qrs19.techconf.org/",

}

Pei, H, Yin, B, Cai, K-Y & Xie, M 2019, A Distance-Based Dynamic Random Testing with Test Case Clustering. in 19^th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019: Proceedings., 8854733, Proceedings - IEEE International Conference on Software Quality, Reliability and Security, QRS, IEEE, pp. 46-53, 19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019, Sofia, Bulgaria, 22/07/19. https://doi.org/10.1109/QRS.2019.00019

A Distance-Based Dynamic Random Testing with Test Case Clustering. / Pei, Hanyu; Yin, Beibei; Cai, Kai-Yuan et al.
19^th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019: Proceedings. IEEE, 2019. p. 46-53 8854733 (Proceedings - IEEE International Conference on Software Quality, Reliability and Security, QRS).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A Distance-Based Dynamic Random Testing with Test Case Clustering

AU - Pei, Hanyu

AU - Yin, Beibei

AU - Cai, Kai-Yuan

AU - Xie, Min

PY - 2019/7

Y1 - 2019/7

N2 - One goal of software testing strategies is to detect faults faster. Dynamic Random Testing (DRT) strategy uses the testing results to guide the selection of test cases, which have shown to be effective in the fault detection process. However, the effectiveness of DRT still can be improved. In this paper, a distance-based DRT (D-DRT) strategy is proposed. The vectorized test cases are partitioned with k-means clustering method to obtain better classification, and the distance information are used to guide the test case selection, then the test cases that are close to failure-causing test cases are more likely to be selected, thus the testing process can be optimized. In the case study, the performance of D-DRT and other testing strategies are compared. The experiment results show that the proposed D-DRT strategy has better fault detection effectiveness than the others without significant increase in computational cost.

AB - One goal of software testing strategies is to detect faults faster. Dynamic Random Testing (DRT) strategy uses the testing results to guide the selection of test cases, which have shown to be effective in the fault detection process. However, the effectiveness of DRT still can be improved. In this paper, a distance-based DRT (D-DRT) strategy is proposed. The vectorized test cases are partitioned with k-means clustering method to obtain better classification, and the distance information are used to guide the test case selection, then the test cases that are close to failure-causing test cases are more likely to be selected, thus the testing process can be optimized. In the case study, the performance of D-DRT and other testing strategies are compared. The experiment results show that the proposed D-DRT strategy has better fault detection effectiveness than the others without significant increase in computational cost.

KW - dynamic random testing

KW - k-means clustering

KW - software cybernetics

KW - test case distance

KW - testing profile

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U2 - 10.1109/QRS.2019.00019

DO - 10.1109/QRS.2019.00019

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-7281-3928-9

T3 - Proceedings - IEEE International Conference on Software Quality, Reliability and Security, QRS

SP - 46

EP - 53

BT - 19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019

PB - IEEE

T2 - 19th IEEE International Conference on Software Quality, Reliability and Security, QRS 2019

Y2 - 22 July 2019 through 26 July 2019

ER -

A Distance-Based Dynamic Random Testing with Test Case Clustering

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