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In recent years many methods and tools for software clone detection have been proposed. While some work has been done on assessing and comparing performance of these tools, very little empirical evaluation has been done. In particular, accuracy measures such as precision and recall have only been roughly estimated, due both to problems in creating a validated clone benchmark against which toolscan be compared, and to the manual effort required to hand check large numbers of candidate clones. In this paper we propose an automated method for empirically evaluating clone detection tools that leverages mutation-based techniques to overcome these limitations by automatically synthesizing large numbers of known clones based on an editing theory of clone creation. Our framework is effective in measuring recall and precision of clone detection tools for various types of fine-grained clones in real systems without manual intervention.

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Developing correct concurrent code is more difficult than developing correct sequential code. This difficulty is due in part to the many different, possibly unexpected, executions of the program, and leads to the need for special quality assurance techniques for concurrent programs such as randomized testing and state space exploration. In this paper an approach is used that assesses testing and formal analysis tools using metrics to measure the effectiveness and efficiency of each technique at finding concurrency bugs. Using program mutation, the assessment method creates a range of faulty versions of a program and then evaluates the ability of various testing and formal analysis tools to detect these faults. The approach is implemented and automated in an experimental mutation analysis framework (ExMAn) which allows results to be more easily reproducible. To demonstrate the approach, we present the results of a comparison of testing using the IBM tool ConTest and model checking using the NASA tool Java PathFinder (JPF).

The current version of Java (J2SE 5.0) provides a high level of support for concurreny in comparison to previous versions. For example, programmers using J2SE 5.0 can now achieve synchronization between concurrent threads using explicit locks, semaphores, barriers, latches, or exchangers. Furthermore, built-in concurrent data structures such as hash maps and queues, built-in thread pools, and atomic variables are all at the programmer's disposal. We are interested in using mutation analysis to evaluate, compare and improve quality assurance techniques for concurrent Java programs. Furthermore, we believe that the current set of method mutation operators and class operators proposed in the literature are insufficient to evaluate concurrent Java source code because the majority of operators do not directly mutate the portions of code responsible for synchronization. In this paper we will provide an overview of concurrency constructs in J2SE 5.0 and a new set of concurrent mutation operators. We will justify the operators by categorizing them with an existing bug pattern taxonomy for concurrency. Most of the bug patterns in the taxonomy have been used to classify real bugs in a benchmark of concurrent Java applications.

Current mutation analysis tools are primarily used to compare different test suites and are tied to a particular programming language. In this paper we present the ExMAn experimental mutation analysis framework - ExMAn is automated, general and flexible and allows for the comparison of different quality assurance techniques such as testing, model checking, and static analysis. The goal of ExMAn is to allow for automatic mutation analysis that can be reproduced by other researchers. After describing ExMAn, we present a scenario of using ExMAn to compare testing with static analysis of temporal logic properties. We also provide both the benefits and the current limitations of using our framework.