Automatic Test Case Generation Using Many-Objective Search and Principal Component Analysis

Li, Dongcheng; Wong, W. Eric; Pan, Sean; Koh, Liang-Seng; Li, Shenglong; Chau, Matthew

doi:10.1109/access.2022.3198694

Cited by 8 publications

(4 citation statements)

References 17 publications

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“…The effectiveness of automated test suite implementation strategies for the Python project Atomic Simulation Environment used in the material sciences is examined by Trubenbach et al [1]. The Principal Component Analysis approach by Li et al [2] is suggested in this study for implementing multi-criteria test suites. It delivers better test suite implementation performance and achieves higher or equal coverage.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Software testing is necessary to ensure that the software complies with its specifications, but if carried out improperly, it may result in even more problems. Putting test suites into place aids in locating the software's testing procedures that need improvement [2]. The test suites are necessary for software testers to use while they evaluate the application or software.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of Test Suites using Enhanced State Chart Diagrams: A Case Study

Gupta,

Goyal

2023

J. Sci. Res.

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An essential part of software engineering is testing. A series of pre-testing tasks should be completed before performing testing tasks. Implementing test suites is one of the pre-testing phases. In this work, a case study has been used to implement the suggested method for implementing test suites. The strategy is based on an analysis of UML (Unified Modelling Language) enhanced state chart diagrams (SCDs). UML state chart diagram analysis, AD (activity diagram) conversion into a graph, AG (activity graph) simplification, and test suite implementation are all steps in the generating process.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Implementation of Test Suites using Enhanced State Chart Diagrams: A Case Study

Gupta,

Goyal

2023

J. Sci. Res.

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“…The performance of MOO methods used to separate mixed signals is often vital. Especially in biomedical signals, the accuracy of the signals separated using MOO methods is confirmed by at least two objective functions [8,9]. Many optimization algorithms have been proposed to separate the mixed signals with the BSS method.…”

Section: Introductionmentioning

confidence: 99%

Blind Source Separation with Strength Pareto Evolutionary Algorithm 2 (SPEA2) Using Discrete Wavelet Transform

Celik,

Karaboga

2023

Electronics

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This paper presents a new method for separating the mixed audio signals of simultaneous speakers using Blind Source Separation (BSS). The separation of mixed signals is an important issue today. In order to obtain more efficient and superior source estimation performance, a new algorithm that solves the BSS problem with Multi-Objective Optimization (MOO) methods was developed in this study. In this direction, we tested the application of two methods. Firstly, the Discrete Wavelet Transform (DWT) was used to eliminate the limited aspects of the traditional methods used in BSS and the small coefficients in the signals. Afterwards, the BSS process was optimized with the multi-purpose Strength Pareto Evolutionary Algorithm 2 (SPEA2). Secondly, the Minkowski distance method was proposed for distance measurement by using density information in the discrimination of individuals with raw fitness values for the concept of Pareto dominance. With this proposed method, the originals (original source signals) were estimated by separating the randomly mixed male and two female speech signals. Simulation and experimental results proved that the efficiency and performance of the proposed method can effectively solve BSS problems. In addition, the Pareto front approximation performance of this method also confirmed that it is superior in the Inverted Generational Distance (IGD) indicator.

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“…According to the defect report library of large commercial software, such as Eclipse and Firefox, 20%-40% of test reports are marked as duplicates [2]. In many cases, the judgment of the truth or falsity of defects is highly dependent on practitioners or developers in the relevant field of the unit under test [3], and sometimes even requires the help of professional testing tools [4]. Anvik et al [5] found that less than 50% of the reports submitted in the first round of traditional software testing contained true defects.…”

Section: Introductionmentioning

confidence: 99%

Estimate the Precision of Defects Based on Reports Duplication in Crowdsourced Testing

Huang

Shi

et al. 2022

IEEE Access

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When analyzing the defects of crowdsourced testing, the testing reports need to be preprocessed, including removing duplicate and false positives. At present, most crowdsourced testing research focuses on duplication of the reports, which has achieved high accuracy. However, studies on reducing false positives of defects have rarely been conducted. Starting from the duplication of defects in the reports, this paper discusses the relationship between the duplication and the accuracy of defects and proposes an estimation approach based on the defect distribution in historical crowdsourced testing projects. Experiments have shown that our approach can provide a priori knowledge of defects and exhibits good stability. We applied this approach to the defect population estimation of crowdsourced testing. With better experimental results, our improved model is more accurate than the original model. We attempt to apply it to the estimation of the defect population of crowdsourced testing, which is more accurate than the original model.INDEX TERMS Precision of defect duplication; crowdsourced testing; a priori distribution of defect precision.

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Automatic Test Case Generation Using Many-Objective Search and Principal Component Analysis

Cited by 8 publications

References 17 publications

Implementation of Test Suites using Enhanced State Chart Diagrams: A Case Study

Implementation of Test Suites using Enhanced State Chart Diagrams: A Case Study

Blind Source Separation with Strength Pareto Evolutionary Algorithm 2 (SPEA2) Using Discrete Wavelet Transform

Estimate the Precision of Defects Based on Reports Duplication in Crowdsourced Testing

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