Field-exhaustive testing

Pablo Ponzio, Nazareno Aguirre, M. Frias, W. Visser
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引用次数: 24

Abstract

We present a testing approach for object oriented programs, which encompasses a testing criterion and an automated test generation technique. The criterion, that we call field-exhaustive testing, requires a user-provided limit n on the size of data domains, and is based on the idea of considering enough inputs so as to exhaustively cover the extension of class fields, within the limit n. Intuitively, the extension of a field f is the binary relation established between objects and their corresponding values for field f, in valid instances. Thus, a suite S is field-exhaustive if whenever a field f relates an object o with a value v (i.e., o.f = v) within a valid instance I of size bounded by n, then S contains at least one input I' covering such relationship, i.e., o must also be part of I', and o.f = v must hold in I'. Our test generation technique uses incremental SAT solving to produce small field-exhaustive suites: field-exhaustiveness can be achieved with a suite containing at most # F x n2 inputs, where # F is the number of fields in the class under test. We perform an experimental evaluation on two different testing domains drawn from the literature: implementations of data structures, and of a refactoring engine. The experiments show that field-exhaustive suites can be computed efficiently, and retain similar levels of code coverage and mutation killing as significantly larger bounded exhaustive and random suites, thus consuming a fraction of the cost of test execution compared to these automated testing approaches.
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Field-exhaustive测试
我们提出了一种面向对象程序的测试方法,它包括一个测试标准和一个自动测试生成技术。我们称之为字段穷举测试的标准,要求用户提供数据域大小的限制n,并且基于考虑足够的输入,以便在限制n内详尽地覆盖类字段的扩展的想法。直观地说,字段f的扩展是在有效实例中对象及其对应字段f的值之间建立的二元关系。因此,一个集合S是域穷举的,如果当一个域f将一个对象o与一个值v(即,o.f = v)关联在一个有效的实例I中,且该实例I的大小为n,那么S至少包含一个覆盖这种关系的输入I',即,o也必须是I'的一部分,并且o.f = v必须包含在I'中。我们的测试生成技术使用增量SAT求解来生成小的字段穷举套件:字段穷举可以通过包含最多# F x n2个输入的套件来实现,其中# F是被测试类中的字段数。我们从文献中提取了两个不同的测试领域:数据结构的实现和重构引擎的实现,并对它们进行了实验评估。实验表明,字段穷举套件可以被有效地计算,并且保留了与更大的有界穷举套件和随机套件相似的代码覆盖率和突变消除水平,因此与这些自动化测试方法相比,消耗了测试执行成本的一小部分。
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