Detecting Integer Bugs without Oracle Based on Metamorphic Testing Technique

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.121-126.1961 ◽

2011 ◽

Vol 121-126 ◽

pp. 1961-1965 ◽

Cited By ~ 1

Author(s):

Song Huang ◽

Meng Yu Ji ◽

Zhan Wei Hui ◽

Yi Ting Duanmu

Keyword(s):

Formal Method ◽

General Procedure ◽

Testing Technique ◽

Metamorphic Testing ◽

Software Failures ◽

Mission Critical

Integer bugs are considered to be the rising threat to mission-critical software. For the oracle problem, testers always ignore integer bugs unless program throws an exception obviously. In this paper, we propose a general procedure based on metamorphic testing to detect integer bugs without oracle and a strategy of the metamorphic relation selection as the complement to T.Y.Chen’ one. The experiment result shows that our approach can detect some invisible mission-critical software failures caused by integer bugs, which are difficult to be found in conventional formal method.

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An Efficient Metamorphic Testing Technique Using Genetic Algorithm

Information Intelligence, Systems, Technology and Management - Communications in Computer and Information Science ◽

10.1007/978-3-642-19423-8_19 ◽

2011 ◽

pp. 180-188 ◽

Cited By ~ 3

Author(s):

Gagandeep Batra ◽

Jyotsna Sengupta

Keyword(s):

Genetic Algorithm ◽

Testing Technique ◽

Metamorphic Testing

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

Mathematical Problems in Engineering ◽

10.1155/2013/381389 ◽

2013 ◽

Vol 2013 ◽

pp. 1-6 ◽

Cited By ~ 7

Author(s):

Zhanwei Hui ◽

Song Huang ◽

Zhengping Ren ◽

Yi Yao

Keyword(s):

Collision Avoidance ◽

Traditional Method ◽

Property Testing ◽

Testing Methods ◽

Metamorphic Testing ◽

Testing Method ◽

Safety Property ◽

Mission Critical ◽

Collision Avoidance System

For mission critical programs, integer overflow is one of the most dangerous faults. Different testing methods provide several effective ways to detect the defect. However, it is hard to validate the testing outputs, because the oracle of testing is not always available or too expensive to get, unless the program throws an exception obviously. In the present study, the authors conduct a case study, where the authors apply a metamorphic testing (MT) method to detect the integer overflow defect and alleviate the oracle problem in testing critical program of Traffic Collision Avoidance System (TCAS). Experimental results show that, in revealing typical integer mutations, compared with traditional safety property testing method, MT with a novel symbolic metamorphic relation is more effective than the traditional method in some cases.

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VERIFICATION OF PHYLOGENETIC INFERENCE PROGRAMS USING METAMORPHIC TESTING

Journal of Bioinformatics and Computational Biology ◽

10.1142/s021972001100563x ◽

2011 ◽

Vol 09 (06) ◽

pp. 729-747 ◽

Cited By ~ 8

Author(s):

MD. SHAIK SADI ◽

FEI-CHING KUO ◽

JOSHUA W. K. HO ◽

MICHAEL A. CHARLESTON ◽

T. Y. CHEN

Keyword(s):

Amino Acids ◽

Software Testing ◽

Evolutionary History ◽

Phylogenetic Inference ◽

Evolutionary Relationships ◽

Testing Technique ◽

Metamorphic Testing ◽

History Of ◽

Scoring Algorithms

Many phylogenetic inference programs are available to infer evolutionary relationships among taxa using aligned sequences of characters, typically DNA or amino acids. These programs are often used to infer the evolutionary history of species. However, in most cases it is impossible to systematically verify the correctness of the tree returned by these programs, as the correct evolutionary history is generally unknown and unknowable. In addition, it is nearly impossible to verify whether any non-trivial tree is correct in accordance to the specification of the often complicated search and scoring algorithms. This difficulty is known as the oracle problem of software testing: there is no oracle that we can use to verify the correctness of the returned tree. This makes it very challenging to test the correctness of any phylogenetic inference programs. Here, we demonstrate how to apply a simple software testing technique, called Metamorphic Testing, to alleviate the oracle problem in testing phylogenetic inference programs. We have used both real and randomly generated test inputs to evaluate the effectiveness of metamorphic testing, and found that metamorphic testing can detect failures effectively in faulty phylogenetic inference programs with both types of test inputs.

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A Genetic Algorithm-Based Approach for Composite Metamorphic Relations Construction

Information ◽

10.3390/info10120392 ◽

2019 ◽

Vol 10 (12) ◽

pp. 392

Author(s):

Zhenglong Xiang ◽

Hongrun Wu ◽

Fei Yu

Keyword(s):

Genetic Algorithm ◽

Empirical Studies ◽

High Quality ◽

Testing Technique ◽

Metamorphic Testing ◽

The Core ◽

Test Oracle ◽

Detection Capabilities ◽

Optimal Set ◽

Core Problem

The test oracle problem exists widely in modern complex software testing, and metamorphic testing (MT) has become a promising testing technique to alleviate this problem. The inference of efficient metamorphic relations (MRs) is the core problem of metamorphic testing. Studies have proven that the combination of simple metamorphic relations can construct more efficient metamorphic relations. In most previous studies, metamorphic relations have been mainly manually inferred by experts with professional knowledge, which is an inefficient technique and hinders the application. In this paper, a genetic algorithm-based approach is proposed to construct composite metamorphic relations automatically for the program to be tested. We use a set of relation sequences to represent a particular class of MRs and turn the problem of inferring composite MRs into a problem of searching for suitable sequences. We then dynamically implement multiple executions of the program and use a genetic algorithm to search for the optimal set of relation sequences. We conducted empirical studies to evaluate our approach using scientific functions in the GNU scientific library (abbreviated as GSL). From the empirical results, our approach can automatically infer high-quality composite MRs, on average, five times more than basic MRs. More importantly, the inferred composite MRs can increase the fault detection capabilities by at least 30 % more than the original metamorphic relations.

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