Michael Lyu - Academia.edu (original) (raw)
Papers by Michael Lyu
2014 International Joint Conference on Neural Networks (IJCNN), 2014
Social information between users has been widely used to improve the traditional Recommender Syst... more Social information between users has been widely used to improve the traditional Recommender System in many previous works. However, in many websites such as Amazon and eBay, there is no explicit social graph that can be used to improve the recommendation performance. Hence in this work, in order to make it possible to employ social recommendation methods in those non-social information websites, we propose a general framework to construct a homophilybased implicit social network by utilizing both the rating and comments of items given by the users. Our scalable framework can be easily extended to enhance the performance of any recommender systems without social network by replacing the homophily-based implicit social relation definition. We propose four methods to extract and analyze the implicit social links between users, and then conduct the experiments on Amazon dataset. Experimental results show that our proposed methods work better than traditional recommendation methods without social information.
Proceedings Ninth International Symposium on Software Reliability Engineering (Cat. No.98TB100257)
Prevalent Markovian and semi-Markovian methods to predict the reliability and performance of comp... more Prevalent Markovian and semi-Markovian methods to predict the reliability and performance of component-based heterogeneous systems suffer from several limitations: they are subject to an intractably large state-space for more involved scenarios, and they cannot take into account the influence of various parameters such as reliability growth of the individual components, dependencies among the components, etc., in a single model. Discrete-event simulation on the other hand offers an attractive alternative to analytical models as it can capture a detailed system structure, and can be used to study the influence of different factors separately as well as in a combined fashion on dependability measures. In this paper we demonstrate the flexibility offered by discrete-event simulation to analyze such complex systems through two case studies, one of a terminating application, and the other of a real-time application with feedback control. We simulate the failure behavior of the terminating application with instantaneous as well as explicit repair. We also study the effect of having fault-tolerant configurations for some of the components on the failure behavior of the application. In the second case of the realtime application, we initially simulate the failure behavior of a single version taking into account its reliability growth. Later we study the failure behavior of three fault tolerant systems, viz., DRB, NVP and NSCP, which are built from the individual versions of the real-time application. Results demonstrate the flexibility offered by simulation to study the influence of various factors on the failure behavior of the applications for single as well as fault-tolerant configura-This work was done when the author was a graduate student at Duke University y Supported by the Direct Grant from the Chinese University of Hong Kong z Supported by a contract from Charles Stark Draper Laboratory and in part by Bellcore as a core project in the Center for Advanced Computing and Communication tions.
ACM Transactions on Software Engineering and Methodology, 2013
Service Oriented Architecture (SOA) is a business-centric IT architectural approach for building ... more Service Oriented Architecture (SOA) is a business-centric IT architectural approach for building distributed systems. Reliability of service-oriented systems heavily depends on the remote Web services as well as the unpredictable Internet connections. Designing efficient and effective reliability prediction approaches of Web services has become an important research issue. In this article, we propose two personalized reliability prediction approaches of Web services, that is, neighborhood-based approach and model-based approach. The neighborhood-based approach employs past failure data of similar neighbors (either service users or Web services) to predict the Web service reliability. On the other hand, the model-based approach fits a factor model based on the available Web service failure data and use this factor model to make further reliability prediction. Extensive experiments are conducted with our real-world Web service datasets, which include about 23 millions invocation resul...
& Conclusions-Existing software reliability-growth models often overestimate the reliability of a... more & Conclusions-Existing software reliability-growth models often overestimate the reliability of a given program. Empirical studies suggest that the over-estimations exist because the models do not account for the nature of the testing. Every testing technique has a limit to its ability to reveal faults in a given system. Thus, as testing continues in its region of saturation, no more faults are discovered and inaccurate reliability-growth phenomena are predicted from the models. This paper presents a technique intended to solve this Problem, using both time & code coverage measures for the prediction of software failures in operation. Coverage information collected during testing is used only to consider the effective portion of the test data. Execution time between test cases, which neither increases code coverage nor causes a failure, is reduced by a parameterized factor. Experiments were conducted to evaluate this technique, on a program created in a simulated environment with simulated faults, and on two industrial systems that contained tenths of ordinary faults. Two well-known reliability models, Goel-Okumoto and Musa-Okumoto, were applied to both the raw data and to the data adjusted using this technique. Results show that overestimation of reliability is properly corrected in the cases studied. This new approach has potential, not only to achieve more accurate applications of software reliability models, but to reveal effective ways of conducting software testing.
International Symposium on Software Reliability Engineering, 1998
Prevalent Markovian and semi Markovian methods to predict the reliability and performance of comp... more Prevalent Markovian and semi Markovian methods to predict the reliability and performance of component based heterogeneous systems suffer from several limitations: they are subject to an intractably large state space for more complex scenarios, and they cannot take into account the influence of various parameters such as reliability growth of individual components, dependencies among components, etc., in a single model.
2014 International Joint Conference on Neural Networks (IJCNN), 2014
Social information between users has been widely used to improve the traditional Recommender Syst... more Social information between users has been widely used to improve the traditional Recommender System in many previous works. However, in many websites such as Amazon and eBay, there is no explicit social graph that can be used to improve the recommendation performance. Hence in this work, in order to make it possible to employ social recommendation methods in those non-social information websites, we propose a general framework to construct a homophilybased implicit social network by utilizing both the rating and comments of items given by the users. Our scalable framework can be easily extended to enhance the performance of any recommender systems without social network by replacing the homophily-based implicit social relation definition. We propose four methods to extract and analyze the implicit social links between users, and then conduct the experiments on Amazon dataset. Experimental results show that our proposed methods work better than traditional recommendation methods without social information.
Proceedings Ninth International Symposium on Software Reliability Engineering (Cat. No.98TB100257)
Prevalent Markovian and semi-Markovian methods to predict the reliability and performance of comp... more Prevalent Markovian and semi-Markovian methods to predict the reliability and performance of component-based heterogeneous systems suffer from several limitations: they are subject to an intractably large state-space for more involved scenarios, and they cannot take into account the influence of various parameters such as reliability growth of the individual components, dependencies among the components, etc., in a single model. Discrete-event simulation on the other hand offers an attractive alternative to analytical models as it can capture a detailed system structure, and can be used to study the influence of different factors separately as well as in a combined fashion on dependability measures. In this paper we demonstrate the flexibility offered by discrete-event simulation to analyze such complex systems through two case studies, one of a terminating application, and the other of a real-time application with feedback control. We simulate the failure behavior of the terminating application with instantaneous as well as explicit repair. We also study the effect of having fault-tolerant configurations for some of the components on the failure behavior of the application. In the second case of the realtime application, we initially simulate the failure behavior of a single version taking into account its reliability growth. Later we study the failure behavior of three fault tolerant systems, viz., DRB, NVP and NSCP, which are built from the individual versions of the real-time application. Results demonstrate the flexibility offered by simulation to study the influence of various factors on the failure behavior of the applications for single as well as fault-tolerant configura-This work was done when the author was a graduate student at Duke University y Supported by the Direct Grant from the Chinese University of Hong Kong z Supported by a contract from Charles Stark Draper Laboratory and in part by Bellcore as a core project in the Center for Advanced Computing and Communication tions.
ACM Transactions on Software Engineering and Methodology, 2013
Service Oriented Architecture (SOA) is a business-centric IT architectural approach for building ... more Service Oriented Architecture (SOA) is a business-centric IT architectural approach for building distributed systems. Reliability of service-oriented systems heavily depends on the remote Web services as well as the unpredictable Internet connections. Designing efficient and effective reliability prediction approaches of Web services has become an important research issue. In this article, we propose two personalized reliability prediction approaches of Web services, that is, neighborhood-based approach and model-based approach. The neighborhood-based approach employs past failure data of similar neighbors (either service users or Web services) to predict the Web service reliability. On the other hand, the model-based approach fits a factor model based on the available Web service failure data and use this factor model to make further reliability prediction. Extensive experiments are conducted with our real-world Web service datasets, which include about 23 millions invocation resul...
& Conclusions-Existing software reliability-growth models often overestimate the reliability of a... more & Conclusions-Existing software reliability-growth models often overestimate the reliability of a given program. Empirical studies suggest that the over-estimations exist because the models do not account for the nature of the testing. Every testing technique has a limit to its ability to reveal faults in a given system. Thus, as testing continues in its region of saturation, no more faults are discovered and inaccurate reliability-growth phenomena are predicted from the models. This paper presents a technique intended to solve this Problem, using both time & code coverage measures for the prediction of software failures in operation. Coverage information collected during testing is used only to consider the effective portion of the test data. Execution time between test cases, which neither increases code coverage nor causes a failure, is reduced by a parameterized factor. Experiments were conducted to evaluate this technique, on a program created in a simulated environment with simulated faults, and on two industrial systems that contained tenths of ordinary faults. Two well-known reliability models, Goel-Okumoto and Musa-Okumoto, were applied to both the raw data and to the data adjusted using this technique. Results show that overestimation of reliability is properly corrected in the cases studied. This new approach has potential, not only to achieve more accurate applications of software reliability models, but to reveal effective ways of conducting software testing.
International Symposium on Software Reliability Engineering, 1998
Prevalent Markovian and semi Markovian methods to predict the reliability and performance of comp... more Prevalent Markovian and semi Markovian methods to predict the reliability and performance of component based heterogeneous systems suffer from several limitations: they are subject to an intractably large state space for more complex scenarios, and they cannot take into account the influence of various parameters such as reliability growth of individual components, dependencies among components, etc., in a single model.