基于镜像测试用例多样性和改进的测试用例选择策略的自适应随机测试方法研究

发布时间：2021-08-31 05:09

　　软件测试已经被认为是软件工程学科中最重要的研究领域之一,并且仍然是软件质量评估和改进中最被广泛实践和研究的方法之一。通过复杂的抽象,软件工程师已经将测试集成到软件开发价值链的每个层次。但是不管怎么努力,“缺陷”还是会在不经意间“潜入”软件,导致软件最终失效。因此,大量的测试技术被提出用来增强开发人员的信心,高质量的软件具有满足相关人群各种愿望的特定功能。大多数这类技术都关注于选择测试用例的策略。如何生成高效的测试用例已经成为学术界和工业界关注的主题。在对这一主题的众多贡献中,随机测试（RT,Random Testing）是最成功的,并且由于其简单、灵活、高效、易于自动化等优点而受到人们的青睐。最近,越来越多的研究人员开始关注RT的有效性,他们批评RT未能利用任何程序信息来指导测试过程。RT的机制建立在软件使用和行为不能被预测的前提下,因此评估软件质量的测试输入也应该以不可预测（随机）的方式进行选择。尽管这一论断仍然正确,但各种经验观察表明,程序员更容易犯某些类型的错误,从而造成大多数程序失效的输入聚集化。这些引起输入失效的几何形状和分布被称为失效模式。根据这些额外信息,这些研究人员试图... 

【文章来源】：江苏大学江苏省

【文章页数】：213 页

【学位级别】：博士

【文章目录】：
ABSTRACT
摘要
Chapter 1 Introduction
    1.1 Software testing
    1.2 Software testing resource and expectations management
    1.3 Closely related Software testing terminologies:Mistake,Fault,Error,and Failure
    1.4 Test case selection and exhaustive testing
    1.5 Automated testing and the test oracle problem
    1.6 Testing techniques:black-box vs.white-box testing
        1.6.1 Black-box testing
        1.6.2 White-box testing
    1.7 Aims and organization of this thesis
    1.8 Contributions of this thesis:
    1.9 Outline of the presentation of this thesis
Chapter 2 Literature Review of Adaptive Random Testing Methods
    2.1 Introduction
    2.2 Random testing(RT)
    2.3 Geometric shapes of failure causing inputs-motivation for ART
    2.4 Adaptive Random Testing(ART)
    2.5 Classifications of ART algorithms
        2.5.1 The exclusion approaches/restrictions
        2.5.2 Partitioning methods
        2.5.3 Restriction-based methods
    2.6 Categories based on effectiveness
    2.7 Based on solving the high dimensionality problems of ART
    2.8 Based on reducing the overhead cost of ART
    2.9 Based on applications of ART to OOP
    2.10 Fault-seeded programs tested using ART
    2.11 Criticisms and open issues on ART
    2.12 An in-depth look at mirror adaptive random testing(MART)
        2.12.1 Characteristics of MART
        2.12.2 Effects of partitioning scheme on the distribution failure causing inputs
        2.12.3 Test case diversity:Implications for the effectiveness of MART
        2.12.4 The problem with the mapping functions of MART
    2.13 Discussions and conclusions
Chapter 3 Metrics,Simulations and Experiment Design Setup
    3.1 Introduction
    3.2 Effectiveness and efficiency metrics
    3.3 Data collection method
    3.4 Error seeding and fault injection strategy
    3.5 Simulations and object programs
        3.5.1 Simulated programs
        3.5.2 Object programs
    3.6 System environment of the simulation and experimental studies:
    3.7 Conclusion
Chapter 4 A Proactive Approach to Test Case Selection-An Efficient Implementation of Adaptive Random Testing
    4.1 Introduction
    4.2 Description of FSCS-ART algorithm
    4.3 The overhead problem of FSCS-ART
    4.4 Overlapping rule
        4.4.1 Contextual underpinning
        4.4.2 FSCS test case distribution
        4.4.3 Predicting the maximin values
        4.4.4 Analysis of candidate test case selection and the impact of overlapping rule
        4.4.5 Determination of efficiency ratio
        4.4.6 Complexity of FSCS-O
    4.5 Research questions
    4.6 Simulations and experimental studies
        4.6.1 Results of simulations
        4.6.2 Results of empirical studies
    4.7 Conclusions
Chapter 5 A Relational Memory Selection:An implementation of Adaptive Random Sequence to Enhance Effectiveness and Efficiency of Adaptive random testing
    5.1 Introduction
    5.2 Background
    5.3 Adaptive random sequence
    5.4 A relational memory selection
        5.4.1 Potential threat to effectiveness of RMS
        5.4.2 Test case generation using RMS
    5.5 Time complexity analysis
    5.6 Research questions
    5.7 Simulations and experimental studies
        5.7.1 Parameter setting
        5.7.2 Results of simulation studies
        5.7.3 Results of experimental studies
    5.8 Conclusion
Chapter 6 Elimination by Linear Association:An Effective and Efficient Static Mirror Adaptive Random Testing
    6.1 Introduction
    6.2 Dynamic partitioning mirror adaptive random testing(DMART)
    6.3 Eliminating the linear association among partitions
        6.3.1 Eliminating failure unrelated challenge of MART
        6.3.2 ELA partitioning schemes
        6.3.3 Selection of source domain
        6.3.4 Generation of test cases from source domain
        6.3.5 Definition of neighboring partition
        6.3.6 Identifying Neighboring partitions
        6.3.7 Generating Mirror test cases
        6.3.8 Demonstrating of test case generation
    6.4 Complexity of EMART
    6.5 Research questions
    6.6 Simulations and experiments
        6.6.1 Setting of parameters
        6.6.2 Simulations
        6.6.3 Experiment with object programs
    6.7 Conclusions
Chapter 7 Random Border Mirror Transform:A Diversity Based Approach to an Effective and Efficient Mirror Adaptive Random Testing
    7.1 Introduction
    7.2 Diversity of mirror mapping function
    7.3 Random border mirror transforms(RBMT)
        7.3.1 Creation of virtual mirror partition
        7.3.2 Random boarder displacement vector
        7.3.3 Schematic diversity transform vector
        7.3.4 Virtual mirror transform and transform discriminant(T~d)
        7.3.5 Mirror transforms
        7.3.6 Addressing the problems of MART
        7.3.7 Test case generation using RBMT-ART
        7.3.8 The algorithm of RBMT
        7.3.9 Complexity analysis of RBMT-ART
    7.4 Research Questions
    7.5 Simulations and Empirical Studies
        7.5.1 Parameter setting
        7.5.2 Simulations Results and Analysis
        7.5.3 Empirical Analysis
    7.6 Discussion and conclusion
Chapter 8 General Conclusion
    8.1 General conclusion
    8.2 Contributions of this thesis
    8.3 Future research directions
REFERENCES
AKNOWLEDGEMENT
PUBLICATIONS


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