Recent advances in computing technologies are increasing the expectations of high accuracy and reliability from sophisticated arithmetic programs. Multi Precision Arithmetic (MPA) plays a vital role in majority of scientific applications, where the accuracy levels are more considerable and even a small mistake may misguide the downstream experimental results. Normal testing strategies rely on test oracles to predict the expected output to compare with target output. Testing of MPA programs is a crucial work with normal testing strategies, due to the complexity of generating oracles to verify the correctness of test outputs. In this paper we propose a novel software testing technique called Metamorphic Testing (MT), to test the nontestable MPA programs with the help of Metamorphic Relations (MRs) to alleviate the oracle problem.MT uses the data diversity technique to generate the follow-up test cases based on the existed successful test cases, which are low cost, scalable, efficient and leads to 'N-Version Programming'. Experimental results are showing that our approach is identifying the hidden errors and improving the testing accuracy by finding more mutants.
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