Browsing by Author "Hill, James H. (James Haswell)"

Now showing 1 - 4 of 4
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    Auto-Generating Models From Their Semantics and Constraints
    (2013-08-20) Pati, Tanumoy; Hill, James H. (James Haswell); Raje, Rajeev; Al Hasan, Mohammad
    Domain-specific models powered using domain-specific modeling languages are traditionally created manually by modelers. There exist model intelligence techniques, such as constraint solvers and model guidance, which alleviate challenges associated with manually creating models, however parts of the modeling process are still manual. Moreover, state-of-the-art model intelligence techniques are---in essence---reactive (i.e., invoked by the modeler). This thesis therefore provides two contributions to model-driven engineering research using domain-specific modeling language (DSML). First, it discusses how DSML semantic and constraint can enable proactive modeling, which is a form of model intelligence that foresees model transformations, automatically executes these model transformations, and prompts the modeler for assistance when necessary. Secondly, this thesis shows how we integrated proactive modeling into the Generic Modeling environment (GME). Our experience using proactive modeling shows that it can reduce modeling effort by both automatically generating required model elements, and by guiding modelers to select what actions should be executed on the model.
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    Characterizing software components using evolutionary testing and path-guided analysis
    (2013-12-16) McNeany, Scott Edward; Hill, James H. (James Haswell); Raje, Rajeev; Al Hasan, Mohammad; Fang, Shiaofen
    Evolutionary testing (ET) techniques (e.g., mutation, crossover, and natural selection) have been applied successfully to many areas of software engineering, such as error/fault identification, data mining, and software cost estimation. Previous research has also applied ET techniques to performance testing. Its application to performance testing, however, only goes as far as finding the best and worst case, execution times. Although such performance testing is beneficial, it provides little insight into performance characteristics of complex functions with multiple branches. This thesis therefore provides two contributions towards performance testing of software systems. First, this thesis demonstrates how ET and genetic algorithms (GAs), which are search heuristic mechanisms for solving optimization problems using mutation, crossover, and natural selection, can be combined with a constraint solver to target specific paths in the software. Secondly, this thesis demonstrates how such an approach can identify local minima and maxima execution times, which can provide a more detailed characterization of software performance. The results from applying our approach to example software applications show that it is able to characterize different execution paths in relatively short amounts of time. This thesis also examines a modified exhaustive approach which can be plugged in when the constraint solver cannot properly provide the information needed to target specific paths.
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    Design, development and experimentation of a discovery service with multi-level matching
    (2013-11-20) Pileththuwasan Gallege, Lahiru Sandakith; Raje, Rajeev; Hill, James H. (James Haswell); Tuceryan, Mihran
    The contribution of this thesis focuses on addressing the challenges of improving and integrating the UniFrame Discovery Service (URDS) and Multi-level Matching (MLM) concepts. The objective was to find enhancements for both URDS and MLM and address the need of a comprehensive discovery service which goes beyond simple attribute based matching. It presents a detailed discussion on developing an enhanced version of URDS with MLM (proURDS). After implementing proURDS, the thesis includes details of experiments with different deployments of URDS components and different configurations of MLM. The experiments and analysis were carried out using proURDS produced MLM contracts. The proURDS referred to a public dataset called QWS dataset. This dataset includes actual information of software components (i.e., web services), which were harvested from the Internet. The proURDS implements the different matching operations as independent operators at each level of matching (i.e., General, Syntactic, Semantic, Synchronization, and QoS). Finally, a case study was carried out with the deployed proURDS. The case study addresses real world component discovery requirements from the earth science domain. It uses the contracts collected from public portals which provide geographical and weather related data.
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    Real-time monitoring of distributed real-time and embedded systems using Web
    (2014-01-03) Puranik, Darshan Gajanan; Hill, James H. (James Haswell); Raje, Rajeev; Durresi, Arjan; Fang, Shiaofen
    Asynchronous JavaScript and XML (AJAX) is the primary method for enabling asynchronous communication over the Web. Although AJAX is providing warranted real-time capabilities to the Web, it requires unconventional programming methods at the expense of extensive resource usage. WebSockets, which is an emerging protocol, has the potential to address many challenges with implementing asynchronous communication over the Web. There, however, has been no in-depth study that quantitatively compares AJAX and WebSockets. This thesis therefore provides two contributions to Web development. First, it provides an experience report for adding real-time monitoring support over the Web to the Open-source Architecture of Software Instrumentation of Systems(OASIS), which is open-source real-time instrumentation middleware for distributed real-time and embedded (DRE) systems. Secondly, it quantitatively compares using AJAX and WebSockets to stream collected instrumentation data over the Web in real-time. Results from quantitative comparison between WebSockets and AJAX show that a WebSockets server consumes 50% less network bandwidth than an AJAX server; a WebSockets client consumes memory at constant rate, not at an increasing rate; and WebSockets can send up to 215.44% more data samples when consuming the same amount network bandwidth as AJAX.