Abstract-Regression testing assures changed programs against unintended amendments. Rearranging the execution order of test cases is a key idea to improve their effectiveness. Paradoxically, many test case prioritization techniques resolve tie cases using the random selection approach, and yet random ordering of test cases has been considered as ineffective. Existing unit testing research unveils that adaptive random testing (ART) is a promising candidate that may replace random testing (RT). In this paper, we not only propose a new family of coverage-based ART techniques, but also show empirically that they are statistically superior to the RT-based technique in detecting faults. Furthermore, one of the ART prioritization techniques is consistently comparable to some of the best coverage-based prioritization techniques (namely, the "additional" techniques) and yet involves much less time cost.

Random testing is not only a useful testing technique in itself, but also plays a core role in many other testing methods. Hence, any significant improvement to random testing has an impact throughout the software testing community. Recently, Adaptive Random Testing (ART) was proposed as an effective alternative to random testing. This paper presents a synthesis of the most important research results related to ART. In the course of our research and through further reflection, we have realised how the techniques and concepts of ART can be applied in a much broader context, which we present here. We believe such ideas can be applied in a variety of areas of software testing, and even beyond software testing. Amongst these ideas, we particularly note the fundamental role of diversity in test case selection strategies. We hope this paper serves to provoke further discussions and investigations of these ideas.

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Service-oriented applications use XPath extensively to integrate loosely-coupled workflow steps. A mismatch among components (e.g., extracting the wrong contents or failing to extract any content from a correct XML message) may cause an application to function incorrectly. XPath should be studied deeply to improve the quality of the applications. In the development of the web services, XPath play a crucial role to capture the messages. Sometimes, XPath can extract error messages, so if XPath can be combined with mutation analysis, the error messages can be avoided. The mutation analysis helps to develop effective tests or locate weaknesses in the test data used for the program or in sections of the code. The time taken to find the error messages and to remove them is critical in the context of XPath. Data flow testing will be done on the test cases generated by the XPath. The effectiveness of the application can be measured by using the fault detection rate. In this paper a technique called the mutation analysis with the use of finite state machine was used to find the mismatch among the components. This approach can be implemented for open source applications. The fault detection rate and the time taken to find the mismatches occured are used to evaluate the approach. We will evaluate this approach by performing the dataflow testing on the open source applications until all the errors in the XML messages are found.

There are two fundamental limitations in software testing, known as the reliable test set problem and the oracle problem. Fault-based testing is an attempt by Morell to alleviate the reliable test set problem. In this paper, we propose to enhance fault-based testing to alleviate the oracle problem as well. We present an integrated method that combines metamorphic testing with fault-based testing using real and symbolic inputs.

Regression testing assures the quality of modified service-oriented business applications against unintended changes. However, a typical regression test suite is large in size. Earlier execution of those test cases that may detect failures is attractive. Many existing prioritization techniques order test cases according to their respective coverage of program statements in a previous version of the application. On the other hand, industrial service-oriented business applications are typically written in orchestration languages such as WS-BPEL and integrated with workflow steps and web services via XPath and WSDL. Faults in these artifacts may cause the application to extract wrong data from messages, leading to failures in service compositions. Surprisingly, current regression testing research hardly considers these artifacts. We propose a multilevel coverage model to capture the business process, XPath, and WSDL from the perspective of regression testing. We develop a family of test case prioritization techniques atop the model. Empirical results show that our techniques can achieve significantly higher rates of fault detection than existing techniques.

Coverage-based fault-localization techniques find the fault-related positions in programs by comparing the execution statistics of passed executions and failed executions. They assess the fault suspiciousness of individual program entities and rank the statements in descending order of their suspiciousness scores to help identify faults in programs. However, many such techniques focus on assessing the suspiciousness of individual program entities but ignore the propagation of infected program states among them. In this paper, we use edge profiles to represent passed executions and failed executions, contrast them to model how each basic block contributes to failures by abstractly propagating infected program states to its adjacent basic blocks through control flow edges. We assess the suspiciousness of the infected program states propagated through each edge, associate basic blocks with edges via such propagation of infected program states, calculate suspiciousness scores for each basic block, and finally synthesize a ranked list of statements to facilitate the identification of program faults. We conduct a controlled experiment to compare the effectiveness of existing representative techniques with ours using standard benchmarks. The results are promising.

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