Testing an Open Source Suite for Open Queuing Network Modelling Using Metamorphic Testing Technique

Author(s):  
T.Y. Chen ◽  
F.-C. Kuo ◽  
R. Merkel ◽  
W.K. Tam
2011 ◽  
Vol 121-126 ◽  
pp. 1961-1965 ◽  
Author(s):  
Song Huang ◽  
Meng Yu Ji ◽  
Zhan Wei Hui ◽  
Yi Ting Duanmu

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.


2011 ◽  
Vol 09 (06) ◽  
pp. 729-747 ◽  
Author(s):  
MD. SHAIK SADI ◽  
FEI-CHING KUO ◽  
JOSHUA W. K. HO ◽  
MICHAEL A. CHARLESTON ◽  
T. Y. CHEN

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.


2015 ◽  
Vol 24 (3) ◽  
pp. 356 ◽  
Author(s):  
Sunderesh S. Heragu ◽  
Aman Gupta

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 392
Author(s):  
Zhenglong Xiang ◽  
Hongrun Wu ◽  
Fei Yu

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.


2020 ◽  
Vol 16 (4) ◽  
pp. 364
Author(s):  
Chang ai Sun ◽  
An Fu ◽  
Yiqiang Liu ◽  
Qing Wen ◽  
Zuoyi Wang ◽  
...  

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