Wang, Miao

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Wang, Miao
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Wang, Miao

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  • Publication
    Towards an automated approach to use expert systems in the performance testing of distributed systems
    (IEEE, 2014-07-21)
    Portillo Dominguez, Andres Omar 
    ;
    Wang, Miao 
    ;
    Murphy, John 
    ;
    et al. 
    Performance testing in distributed environments is challenging. Specifically, the identification of performance issues and their root causes are time-consuming and complex tasks which heavily rely on expertise. To simplify these tasks, many researchers have been developing tools with built-in expertise. However limitations exist in these tools, such as managing huge volumes of distributed data, that prevent their efficient usage for performance testing of highly distributed environments. To address these limitations, this paper presents an adaptive framework to automate the usage of expert systems in performance testing. Our validation assessed the accuracy of the framework and the time savings that it brings to testers. The results proved the benefits of the framework by achieving a significant decrease in the time invested in performance analysis and testing
      429Scopus© Citations 5
  • Publication
    Automated WAIT for Cloud-Based Application Testing
    (IEEE, 2014-04-04)
    Portillo Dominguez, Andres Omar 
    ;
    Wang, Miao 
    ;
    Murpy, John 
    ;
    Magoni, Damien 
    Cloud computing is causing a paradigm shift in the provision and use of software. This has changed the way of obtaining, managing and delivering computing services and solutions. Similarly, it has brought new challenges to software testing. A particular area of concern is the performance of cloud-based applications. This is because the increased complexity of the applications has exposed new areas of potential failure points, complicating all performance-related activities. This situation makes the performance testing of cloud environments very challenging. Similarly, the identification of performance issues and the diagnosis of their root causes are time-consuming and complex, usually require multiple tools and heavily rely on expertise. To simplify these tasks, hence increasing the productivity and reducing the dependency on human experts, this paper presents a lightweight approach to automate the usage of expert tools in the performance testing of cloud-based applications. In this paper, we use a tool named Whole-system Analysis of Idle Time to demonstrate how our research work solves this problem. The validation involved two experiments, which assessed the overhead of the approach and the time savings that it can bring to the analysis of performance issues. The results proved the benefits of the approach by achieving a significant decrease in the time invested in performance analysis while introducing a low overhead in the tested system.
      458Scopus© Citations 11