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Two factors contribute to the difficulty of testing scientific software. One is the lack of testing oracles - a means of comparing software output to expected and correct results. The second is the large number of tests required when following any standard testing technique described in the software engineering literature. Due to the lack of oracles, scientists use judgment based on experience to assess trustworthiness, rather than correctness, of their software. This is an approach well established for assessing scientific models. However, the problem of assessing software is more complex, exacerbated by the problem of code faults. This highlights the need for effective and efficient testing for code faults in scientific software. Our current research suggests that a small number of well chosen tests may reveal a high percentage of code faults in scientific software and allow scientists to increase their trust.