声明
Chapter 1 Introduction
1.1 Software Testing
1.2SoftwareTesting Resource and Expectations Management
1.3Closely related Software testing terminologies:Mistake, Fault, Error,and Failure
1.4Test Case Selection and Exhaustive Testing
1.5Automated Testing andthe Test Oracle Problem
1.6Testing Techniques: Black-Box Vs. White-Box Testing
1.6.1Black-Box Testing
1.6.2White-Box Testing
1.7Aims and organization of this thesis
1.8Contributions of this thesis
1.9Outline of the presentation of this thesis
Chapter 2Literature Review of Adaptive Random Testing Methods
2.1 Introduction
2.2 Random Testing (RT)
2.3Geometric shapes of failure causing inputs-motivation for ART
2.4Adaptive Random Testing (ART)
2.5Classifications of ART Algorithms
2.5.1The Exclusion Approaches/Restrictions
2.5.2 Partitioning Methods
2.5.3 Restriction-based Methods
2.6 Categories based on Effectiveness
2.7Based on solving the high dimensionality problems of ART
2.8Based on reducing the overhead cost of ART
2.9Based on applications of ART to OOP
2.10Fault-seeded programs tested using ART
2.11Criticisms and open issues on ART
2.12An in-depth look at mirror adaptive random testing (MART)
2.12.1Characteristics of MART
2.12.2Effects of partitioning scheme on the distribution failure causing inputs
2.12.3Test casediversity: Implications for the effectiveness of MART
2.12.4The problem with the mapping functions of MART
2.13Discussions and conclusions
Chapter 3Metrics, Simulations and Experiment Design Setup
3.1 Introduction
3.2Effectiveness and efficiency metrics
3.3Data collection method
3.4Error seeding and fault injection strategy
3.5Simulations and object programs
3.5.1Simulated programs
3.5.2Object programs
3.6System environment of the simulation and experimental studies
3.7 Conclusion
Chapter4A Proactive Approach to Test Case Selection-An Efficient Implementation of Adaptive Random Testing
4.1 Introduction
4.2Description of FSCS-ART algorithm
4.3The overhead problem of FSCS-ART
4.4Overlapping rule
4.4.1Contextual underpinning
4.4.2FSCS test case distribution
4.4.3Predicting the maximin values
4.4.4Analysis of candidate test case selection and the impact of overlapping rule
4.4.5Determination of efficiency ratio
4.4.6Complexity of FSCS-O
4.5Research questions
4.6Simulations and experimental studies
4.6.1Results of simulations
4.6.2Results of empirical studies
4.7 Conclusions
Chapter 5A Relational Memory Selection: An implementation of Adaptive Random Sequence to Enhance Effectiveness and Efficiency of Adaptive random testing
5.1 Introduction
5.2 Background
5.3Adaptive random sequence
5.4A relational memory selection
5.4.1Potential threat to effectiveness of RMS
5.4.2Test case generation using RMS
5.5Time complexity analysis
5.6Research questions
5.7Simulations and experimental studies
5.7.1Parameter setting
5.7.2Results of simulation studies
5.7.3Results of experimental studies
5.8 Conclusion
Chapter6Elimination by Linear Association: An Effective and Efficient Static Mirror Adaptive Random Testing
6.1 Introduction
6.2Dynamic partitioning mirror adaptive random testing (DMART)
6.3Eliminating the linear association among partitions
6.3.1Eliminating failure unrelated challenge of MART
6.3.2ELA partitioning schemes
6.3.3Selection of source domain
6.3.4Generation of test cases from source domain
6.3.5Definition of neighboring partition
6.3.6Identifying Neighboring partitions
6.3.7Generating Mirror test cases
6.3.8Demonstrating of test case generation
6.4Complexity of EMART
6.5 Research questions
6.6Simulations and experiments
6.6.1Setting of parameters
6.6.2 Simulations
6.6.3Experiment with object programs
6.7 Conclusions
Chapter7Random Border Mirror Transform: A Diversity Based Approach to an Effective and Efficient Mirror Adaptive Random Testing
7.1 Introduction
7.2Diversity of mirror mapping function
7.3Random border mirrortransforms(RBMT)
7.3.1Creation of virtual mirror partition
7.3.2Random boarder displacement vector
7.3.3Schematic diversity transform vector
7.3.4VirtualMirror Transform and Transform Discriminant(Td)
7.3.5 Mirror Transforms
7.3.6Addressing the problems of MART
7.3.7Test case generation using RBMT-ART
7.3.8The algorithm of RBMT
7.3.9Complexity analysis of RBMT-ART
7.4Research Questions
7.5Simulations and Empirical Studies
7.5.1Parameter setting
7.5.2Simulations Results and Analysis
7.5.3Empirical Analysis
7.6Discussion and conclusion
Chapter8General Conclusion
8.1General conclusion
8.2Contributions of this thesis
8.3Future research directions
参考文献
致谢
PUBLICATIONS
江苏大学;
