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        1 - Prediction of Deadlocks in Concurrent Programs Using Neural Network
        Elmira Hasanzad babamir babamir
        The dependability of concurrent programs is usually limited by concurrency errors like deadlocks and data races in allocation of resources. Deadlocks are difficult to find during the program testing because they happen under very specific thread or process scheduling an More
        The dependability of concurrent programs is usually limited by concurrency errors like deadlocks and data races in allocation of resources. Deadlocks are difficult to find during the program testing because they happen under very specific thread or process scheduling and environmental conditions. In this study, we extended our previous approach for online potential deadlock detection in resources allocated by multithread programs. Our approach is based on reasoning about deadlock possibility using the prediction of future behavior of threads. Due to the nondeterministic nature, future behavior of multithread programs, in most of cases, cannot be easily specified. Before the prediction, the behavior of threads should be translated into a predictable format. Time series is our choice to this conversion because many Statistical and Artificial Intelligence techniques can be developed to predict the future members of the time series. Among all the prediction techniques, artificial neural networks showed applicable performance and flexibility in predicting complex behavioral patterns which are the most usual cases in real world applications. Our model focuses on the multithread programs which use locks to allocate resources. The proposed model was used to deadlock prediction in resources allocated by multithread Java programs and the results were evaluated. Manuscript profile
      • Open Access Article

        2 - Enhancing Efficiency of Software Fault Tolerance Techniques in Satellite Motion System
        Hoda Banki babamir babamir Azam Farokh Mohammad Mehdi Morovati
        This research shows the influence of using multi-core architecture to reduce the execution time and thus increase performance of some software fault tolerance techniques. According to superiority of N-version Programming and Consensus Recovery Block techniques in compar More
        This research shows the influence of using multi-core architecture to reduce the execution time and thus increase performance of some software fault tolerance techniques. According to superiority of N-version Programming and Consensus Recovery Block techniques in comparison with other software fault tolerance techniques, implementations were performed based on these two methods. Finally, the comparison between the two methods listed above showed that the Consensus Recovery Block is more reliable. Therefore, in order to improve the performance of this technique, we propose a technique named Improved Consensus Recovery Block technique. In this research, satellite motion system which known as a scientific computing system is consider as a base for our experiments. Because of existing any error in calculation of system may result in defeat in system totally, it shouldn’t contains any error. Also the execution time of system must be acceptable. In our proposed technique, not only performance is higher than the performance of consensus recovery block technique, but also the reliability of our proposed technique is equal to the reliability of consensus recovery block technique. The improvement of performance is based on multi-core architecture where each version of software key units is executed by one core. As a result, by parallel execution of versions, execution time is reduced and performance is improved. Manuscript profile