During software development, engineers often reuse a code fragment via copy-and-paste with or without modifications or adaptations. Such practices lead to a number of the same or similar code fragments spreading within one or many large codebases. Detecting code clones has been shown to be useful towards security such as detection of similar security bugs and, more generally, quality improvement such as refactoring of code clones. A large number of academic research projects have been carried out on empirical studies or tool supports for detecting code clones. In this paper, we report our experiences of carrying out successful technology transfer of our new approach of code-clone detection, called XIAO. XIAO has been integrated into Microsoft Visual Studio 2012, to be benefiting a huge number of developers in industry. The main success factors of XIAO include its high tunability, scalability, compatibility, and explorability. Based on substantial industrial experiences, we present the XIAO approach with emphasis on these success factors of XIAO. We also present empirical results on applying XIAO on real scenarios within Microsoft for the tasks of security-bug detection and refactoring.

Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness at meeting some performance goal. Various goals are possible; one involves rate of fault detection, a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test and let software engineers begin correcting faults earlier than might otherwise be possible. One application of prioritization techniques involves regression testing, the retesting of software following modifications; in this context, prioritization techniques can take advantage of information gathered about the previous execution of test cases to obtain test case orderings. We describe several techniques for using test execution information to prioritize test cases for regression testing, including: 1) techniques that order test cases based on their total coverage of code components; 2) techniques that order test cases based on their coverage of code components not previously covered; and 3) techniques that order test cases based on their estimated ability to reveal faults in the code components that they cover. We report the results of several experiments in which we applied these techniques to various test suites for various programs and measured the rates of fault detection achieved by the prioritized test suites, comparing those rates to the rates achieved by untreated, randomly ordered, and optimally ordered suites.

Test case prioritization techniques schedule test cases for execution in an order that attempts to maximize some objective function. A variety of objective functions are applicable; one such function involves rate of fault detection-a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during regression testing can provide faster feedback on a system under regression test and let debuggers begin their work earlier than might otherwise be possible. In this paper we describe several techniques for prioritizing test cases and report our empirical results measuring the effectiveness of these techniques for improving rate of fault detection. The results provide insights into the tradeoffs among various techniques for test case prioritization.