Coverage criteria for test case generation using UML state chart diagram

Salman, Yasir Dawood; Hashim, Nor Laily; Rejab, Mawarny Md.; Romli, Rohaida; Mohd, Haslina

doi:10.1063/1.5005458

Cited by 7 publications

(2 citation statements)

References 26 publications

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“…These unimportant features are usually redundant and can add noise to the classifier's design. As a result, it's important to select data with useful characteristics that will help classifier performance improve [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

An Efficient Hybrid Filter-Wrapper Feature Selection Approach for Network Intrusion Detection System

2023

IJIES

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The detection rate of network intrusion detection systems mainly depends on relevant features; however, the selection of attributes or features is considered an issue in NP-hard problems. It is an important step in machine learning and pattern recognition. The major aim of feature selection is to determine the feature subset from the current/existing features that will enhance the learning performance of the algorithms, in terms of accuracy and learning time. This paper proposes a new hybrid filter-wrapper feature selection method that can be used in classification problems. The information gain ratio algorithm (GR) represents the filter feature selection approach, and the black hole algorithm (BHA) represents the wrapper feature selection approach. The comparative analysis of network intrusion detection methods focuses on accuracy and false positive rate. GBA shines with exceptional results: achieving 96.96% accuracy and a mere 0.89% false positive rate. This success can be traced to GBA's improved initialization via the GR technique, which effectively removes irrelevant features. By assigning these features almost zero weights, GBA hones its ability to accurately spot intrusions while drastically reducing false alarms. These standout outcomes underline GBA's superiority over other methods, showcasing its potential as a reliable solution for bolstering network security.

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Section: Introductionmentioning

confidence: 99%

An Efficient Hybrid Filter-Wrapper Feature Selection Approach for Network Intrusion Detection System

2023

IJIES

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“…In software testing, genetic algorithms (GAs) have successfully achieved the maximum coverage criterion in object-oriented classes [1][2][3][4]. The coverage criterion is a definition for which parts of the program are to be executed and whether the set of test cases can be executed as defined [5,6]. There are a variety of coverage criteria for testing (e.g., branch, line, mutation).…”

Section: Introductionmentioning

confidence: 99%

Multiple-Searching Genetic Algorithm for Whole Test Suites

et al. 2021

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A test suite is a set of test cases that evaluate the quality of software. The aim of whole test suite generation is to create test cases with the highest coverage scores possible. This study investigated the efficiency of a multiple-searching genetic algorithm (MSGA) for whole test suite generation. In previous works, the MSGA has been effectively used in multicast routing of a network system and in the generation of test cases on individual coverage criteria for small- to medium-sized programs. The performance of the algorithms varies depending on the problem instances. In this experiment were generated whole test suites for complex programs. The MSGA was expanded in the EvoSuite test generation tool and compared with the available algorithms on EvoSuite in terms of the number of test cases, the number of statements, mutation score, and coverage score. All algorithms were evaluated on 14 problem instances with different corpus to satisfy multiple coverage criteria. The problem instances were Java open-source projects. Findings demonstrate that the MSGA generated test cases reached greater coverage scores and detected a larger number of faults in the test class when compared with the others.

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DFS-KeyLevel: A Two-Layer Test Scenario Generation Approach for UML Activity Diagram

Zhang

Chen

et al. 2023

J Electron Test

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Coverage criteria for test case generation using UML state chart diagram

Cited by 7 publications

References 26 publications

An Efficient Hybrid Filter-Wrapper Feature Selection Approach for Network Intrusion Detection System

An Efficient Hybrid Filter-Wrapper Feature Selection Approach for Network Intrusion Detection System

Multiple-Searching Genetic Algorithm for Whole Test Suites

DFS-KeyLevel: A Two-Layer Test Scenario Generation Approach for UML Activity Diagram

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