In highly dynamic IoT environments, the connection statuses of IoT resources and the availability of IoT-based services change frequently. Therefore, to successfully build distributed service registries for managing and finding the information about available services in an effective manner, it is crucial to minimize the overhead of message exchanges between registries and to reduce the time overhead for identifying the capabilities of available IoT resources and the services that can be provided by utilizing these capabilities. In this paper, we propose a lightweight messaging approach that uses hierarchical Bloom filters to efficiently represent service information to be exchanged and managed by distributed service registries for IoT environments with high mobility. We also propose a method for serializing the dimensions of a Bloom-filter-encoded search space. We conducted experiments to demonstrate the improvement in the service discovery performance, the reduction in message traffic among service registries, and the decrease in the latency when synchronizing distributed service registries.

The functions, capabilities, and effects produced by the application services of cyber physical systems (CPS) are usually consumed by users performing their daily activities in a variety of environmental conditions. Thus, it is critical to ensure that those systems neither interfere with human activities nor harm the users involved. In this paper, we propose a framework for testing and verifying the safety and reliability of CPS services from the perspectives of CPS environments and users. The framework provides an environmentaware testing method by which the efficiency of testing CPS services can be improved by prioritizing CPS environments and by applying machinelearning techniques. The framework also includes a metric by which we can automate the test of the most effective services that deliver effects from physical devices to users. Additionally, the framework provides a computational model that assesses mental workloads to test whether a CPS service can cause cognitive depletion or contention problems for users. We conducted a series of experiments to show the effectiveness of the proposed approaches for ensuring the safety and reliability of CPS application services during the development and operation phases.

When testing client-side web applications, it is important to consider different web-browser environments. Different properties of these environments such as web-browser types and underlying platforms may cause a web application to exhibit different types of failures. As web applications evolve, they must be regression tested across these different environments. Because there are many environments to consider this process can be expensive, resulting in delayed feedback about failures in applications. In this work, we propose six techniques for providing a developer with faster feedback on failures when regression testing web applications across different web-browser environments. Our techniques draw on methods used in test case prioritization; however, in our case we prioritize web-browser environments, based on information on recent and frequent failures. We evaluated our approach using four non-trivial and popular open-source web applications. Our results show that our techniques outperform two baseline methods, namely, no ordering and random ordering, in terms of the cost-effectiveness. The improvement rates ranged from −12.24% to 39.05% for no ordering, and from −0.04% to 45.85% for random ordering.

Regression testing in continuous integration development environments must be cost-effective and should provide fast feedback on test suite failures to the developers. In order to provide faster feedback on failures to developers while using computing resources efficiently, two types of regression testing techniques have been developed: Regression Testing Selection (RTS) and Test Case Prioritization (TCP). One of the factors that reduces the effectiveness of the RTS and TCP techniques is the inclusion of test suites that fail only once over a period. We propose an approach based on Bloom filtering to exclude such test suites during the RTS process, and to assign such test suites with a lower priority during the TCP process. We experimentally evaluate our approach using a Google dataset, and demonstrate that cost-effectiveness of the proposed RTS and TCP techniques outperforms the state-of-the-art techniques.

An emerging issue in urban computing environments is the seamless selection, composition, and delivery of user-centric services that run over what is known as the Internet of Things (IoT). This challenge is about enabling services actuated by IoT devices to be delivered spontaneously from the perspective of users. To accomplish this goal, we propose the Service-Oriented Internet of Things (SoIoT), a user-centric IoT-based service framework, which integrates services that utilize IoT resources in an urban computing environment. This framework provides a task-oriented computing approach that enables the composition of IoT-based services in a spontaneous manner to accomplish a user task. Tasks can also be recommended to users based on the available IoT resources in an environment and on the contextual knowledge that is represented and managed in social, spatial, and temporal aspects. These tasks are then bound to a set of service instances and performed in a distributed manner. This final composition ensures the Quality of Service (QoS) requirements of the tasks and is assigned to multiple client devices for the efficient utilization of IoT resources. We prove the practicality of our approach by showing a real-case service scenario implemented in our IoT-based test-bed as well as experimental results.

In regression testing, running all a system's test cases can require a great deal of time and resources. Test case prioritization (TCP) attempts to schedule test cases to achieve goals such as higher coverage or faster fault detection. While code coverage-based approaches are typical in TCP, recent work has explored the use of additional information to improve effectiveness. In this work, we explore the use of Information Retrieval (IR) techniques to improve the effectiveness of TCP, particularly for testing infrequently tested code. Our approach considers the frequency at which elements have been tested, in additional to traditional coverage information, balancing these factors using linear regression modeling. Our empirical study demonstrates that our approach is generally more effective than both random and traditional code coverage-based approaches, with improvements in rate of fault detection of up to 4.7%.