Postdoc: Data-Flow Testing for Difficult-To-Find Bugs

9704703 Ryder，Barbara G. 罗格斯大学 CISE博士后研究员在实验CS：数据流测试难以找到的错误 数据流覆盖准则是判断软件测试集质量和确定何时完成足够测试的一种方法。对诸如C语言的程序进行数据流测试所需的分析目前在大型程序上是不切实际的。 实现覆盖需求的接近100%的满足构成了数据流测试的真实的开销。然而，这与测试的真实的开销没有必然的联系，测试的开销是寻找那些难以发现的bug。 通过假设难以发现的错误与语句风险水平相关，引入语句风险来度量程序语句执行的意外影响。 初步实验表明，一小部分程序语句是高度危险的。副作用危险定义为程控仪未预期到的副作用程度。因此，实验来确定危险的语句和错误检测之间的关系进行了描述。这些实验建立在分析数据流测试有效性的其他成功实验的基础上，但另外要特别注意那些难以发现的错误。确定危险语句和难以发现的错误之间的相关性将提高数据流测试的有效性并降低其成本，使数据流测试在工业环境中可行。

9704703 Ryder, Barbara G. Rutgers University CISE Postdoctoral Research Associates in Experimental CS :Data-Flow Testing for Difficult-to-Find Bugs Data-flow coverage criteria are heuristics for judging the quality of software test suites and determining when enough testing has been done. The analysis required for data-flow testing of programs in languages such as C is currently impractical on large programs. Achieving near 100% satisfaction of the coverage requirements constitutes the real expense of data-flow testing. However, this is not necessarily related to the real expense of testing, which is looking for the difficult-to-find bugs. With the hypothesis that difficult-to-find bugs are correlated with statement hazard level, statement hazard is introduced to measure the unexpected effects of executing a program statement. Preliminary experiments indicate that a small proportion of program statements are highly hazardous. Hazard of a side-effect is defined as the degree to which its side-effects are unexpected by the programmer. Thus, experiments to determine the relation between hazardous statements and bug detection are described. These experiments build on other successful experiments in analyzing data-flow testing effectiveness, but additionally pay special attention to those bugs that are difficult to find. Determining the correlation between hazardous statements and difficult-to-find bugs will improve the effectiveness of data-flow testing and reduce its cost, making data-flow testing feasible in an industrial environment.