Metamorphic Testing Integer Overflow Faults of Mission Critical Program: A Case Study

Hui, Zhanwei; Huang, Song; Ren, Zeyu; Yao, Yi

doi:10.1155/2013/381389

Cited by 10 publications

(5 citation statements)

References 9 publications

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“…Metamorphic testing has also been applied to optimisation programs using both stochastic [123] and heuristic algorithms [32]. Yao et al [124], [125], [126] presented preliminary results on the use of metamorphic testing to detect integer overflows. Batra and Singh [127] proposed using UML diagrams to guide the selection of metamorphic relations and presented a small case study using a banking application.…”

Section: Other Domainsmentioning

confidence: 99%

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A Survey on Metamorphic Testing

Segura

Fraser

Sánchez

et al. 2016

IIEEE Trans. Software Eng.

432

230

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Abstract-A test oracle determines whether a test execution reveals a fault, often by comparing the observed program output to the expected output. This is not always practical, for example when a program's input-output relation is complex and difficult to capture formally. Metamorphic testing provides an alternative, where correctness is not determined by checking an individual concrete output, but by applying a transformation to a test input and observing how the program output "morphs" into a different one as a result. Since the introduction of such metamorphic relations in 1998, many contributions on metamorphic testing have been made, and the technique has seen successful applications in a variety of domains, ranging from web services to computer graphics. This article provides a comprehensive survey on metamorphic testing: It summarises the research results and application areas, and analyses common practice in empirical studies of metamorphic testing as well as the main open challenges.

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Section: Other Domainsmentioning

confidence: 99%

“…This metric calculates the ratio of test cases that detect a given fault [41], [55], [68], [70], [71], [101], [124], [126]. The Fault Detection Ratio (FDR) of a metamorphic test suite t and a fault f is calculated as follows:…”

Section: Fault Detection Ratiomentioning

confidence: 99%

A Survey on Metamorphic Testing

Segura

Fraser

Sánchez

et al. 2016

IIEEE Trans. Software Eng.

432

230

View full text Add to dashboard Cite

show abstract

“…However, according to the analysis [42], even if the testing meets specific coverage criteria, some undetected faults still exist in programmes. Researches show that MRs have a strong ability to detect faults [30][31][32]. Therefore, when applying the IRs of MRs to generate test cases, we can use the ORs of MRs to improve the ability of test cases to detect faults.…”

Section: Discussionmentioning

confidence: 99%

“…(r, r f ) is called the MR [29]. The relation r is called the input relation (IR) and the relation r f is called the output relation (OR) [30]. If P is correct, then it must satisfy the following formula:…”

Section: Metamorphic Testing and Mrmentioning

confidence: 99%

“…If there is a relation r between

x_{1}, x_{2}, \dots, x_{n}

, and there is a relation

r_{f}

between

f false(x_{1} false), f false(x_{2} false), \dots, f false(x_{n} false)

, then

r false(x_{1}, x_{2}, \dots, x_{n} false) false\Rightarrow r_{f} false(f false(x_{1} false), f false(x_{2} false), \dots, f false(x_{n} false) false)

false(r, r_{f} false)

is called the MR [29]. The relation r is called the input relation (IR) and the relation

r_{f}

is called the output relation (OR) [30]. If P is correct, then it must satisfy the following formula:

r false(I_{1}, I_{2}, \dots, I_{n} false) false\Rightarrow r_{f} false(P false(I_{1} false), P false(I_{2} false), \dots, P false(I_{n} false) false)

I_{1}, I_{2}, \dots, I_{n}

are actual inputs of P corresponding with

x_{1}, x_{2}, \dots, x_{n}

;

…”

Section: Introductionmentioning

confidence: 99%

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Test cases generation for multiple paths based on PSO algorithm with metamorphic relations

Huang

Hui

et al. 2018

IET softw.

Self Cite

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The generation of multiple-path test cases can greatly enhance the efficiency of path-wise testing. Various methods adopting meta-heuristic algorithm to generate multiple-path test cases have been proposed, but existing methods focus on improving the meta-heuristic algorithm to get better test case generation efficiency, and test cases covering each path needs to be generated by meta-heuristic algorithm searching. To improve efficiency, a test case generation method for multiple-path coverage is proposed in this study, which combines a particle swarm optimisation (PSO) algorithm with metamorphic relations (MRs). The method first generates a test case using the PSO algorithm, and then generates new test cases by repeatedly using MRs between test cases. This method reduces evolving numbers of PSO algorithm. The experimental results show that the proposed method can significantly enhance the efficiency in terms of fitness evaluations and time consumption.

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A mapping study on testing non-testable systems

Patel

Hierons

2017

Software Qual J

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The terms "Oracle Problem" and "Non-testable system" interchangeably refer to programs in which the application of test oracles is infeasible. Test oracles are an integral part of conventional testing techniques; thus, such techniques are inoperable in these programs. The prevalence of the oracle problem has inspired the research community to develop several automated testing techniques that can detect functional software faults in such programs. These techniques include N-Version testing, Metamorphic Testing, Assertions, Machine Learning Oracles, and Statistical Hypothesis Testing. This paper presents a Mapping Study that covers these techniques. The Mapping Study presents a series of discussions about each technique, from different perspectives, e.g. effectiveness, efficiency, and usability. It also presents a comparative analysis of these techniques in terms of these perspectives. Finally, potential research opportunities within the non-testable systems problem domain are highlighted within the Mapping Study. We believe that the aforementioned discussions and comparative analysis will be invaluable for new researchers that are attempting to familiarise themselves with the field, and be a useful resource for practitioners that are in the process of selecting an appropriate technique for their context, or deciding how to apply their selected technique. We also believe that our own insights, which are embedded throughout these discussions and the comparative analysis, will be useful for researchers that are already accustomed to the field. It is our hope that the potential research opportunities that have been highlighted by the Mapping Study will steer the direction of future research endeavours.

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Metamorphic Testing Integer Overflow Faults of Mission Critical Program: A Case Study

Cited by 10 publications

References 9 publications

A Survey on Metamorphic Testing

A Survey on Metamorphic Testing

Test cases generation for multiple paths based on PSO algorithm with metamorphic relations

A mapping study on testing non-testable systems

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