R. Casallas, M. Vela, Catalina Acero, Nicolás López
We propose an approach to create application-cooperation executable UML models by performing transformations on high-level business rule models. Business rules are defined, using activity diagrams, then, they are transformed to an annotated PIM to, finally, be transformed into an executable UML (xUML) model. The xUML model along side with a set of test cases enables us to validate that applications, whose cooperation is described in the rules, maintain consistency and integrity. Because this validation is based on a non-distributed, platform-independent simulation the cost and effort of its development and testing is reduced; early detection of flaws can help avoid expensive modifications on a concrete platform specific implementation.
{"title":"xEAI-rules: executable models to simulate enterprise application cooperation","authors":"R. Casallas, M. Vela, Catalina Acero, Nicolás López","doi":"10.1145/1141277.1141581","DOIUrl":"https://doi.org/10.1145/1141277.1141581","url":null,"abstract":"We propose an approach to create application-cooperation executable UML models by performing transformations on high-level business rule models. Business rules are defined, using activity diagrams, then, they are transformed to an annotated PIM to, finally, be transformed into an executable UML (xUML) model. The xUML model along side with a set of test cases enables us to validate that applications, whose cooperation is described in the rules, maintain consistency and integrity. Because this validation is based on a non-distributed, platform-independent simulation the cost and effort of its development and testing is reduced; early detection of flaws can help avoid expensive modifications on a concrete platform specific implementation.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121212772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a clustering algorithm for categorical datasets, called CLUC (CLUstering with Cohesion), which uses a novel similarity measure, called cohesion, to determine the degree with which items/objects stick to clusters. We have implemented CLUC and carried out extensive experiments on real-life and synthetic datasets. The results of experiments and their analyses indicate that CLUC generates high quality clusters in that they conform to expert's opinion. Our experiments on large synthetic data confirm that CLUC is scalable when the dataset grows in the number of objects and/or dimensions. We also repeated the experiments with different orders of the items in the datasets. The results show that the proposed algorithm is order insensitive
{"title":"CLUC: a natural clustering algorithm for categorical datasets based on cohesion","authors":"Aida Nemalhabib, Nematollaah Shiri","doi":"10.1145/1141277.1141422","DOIUrl":"https://doi.org/10.1145/1141277.1141422","url":null,"abstract":"We propose a clustering algorithm for categorical datasets, called CLUC (CLUstering with Cohesion), which uses a novel similarity measure, called cohesion, to determine the degree with which items/objects stick to clusters. We have implemented CLUC and carried out extensive experiments on real-life and synthetic datasets. The results of experiments and their analyses indicate that CLUC generates high quality clusters in that they conform to expert's opinion. Our experiments on large synthetic data confirm that CLUC is scalable when the dataset grows in the number of objects and/or dimensions. We also repeated the experiments with different orders of the items in the datasets. The results show that the proposed algorithm is order insensitive","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121331065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Complex environmental modeling often involves a large number of unknown physical and ecological parameters. Parameter estimation is one of the most difficult steps in many modeling activities. In this paper we present a service-oriented framework, named GGPE-G (Grid-enabled Global optimization for General Parameter Estimation), for efficient parameter estimation in heterogeneous, distributed systems. Being presented as services, the optimization algorithms, the physical and ecological process models and clients can interact with each other by XML message interactions. The proposed approach supports a generic parameter estimation procedure and can be easily applied to different modeling environment. In this paper, we explain the design, architecture, and implementation of GGPE-G in details. We also apply GGPE-G to a complex soil-water-atmosphere-plant modeling system to demonstrate its utility and efficiency.
{"title":"Service-oriented grid computation for large-scale parameter estimation in complex environmental modeling","authors":"Kejing He, Shoubin Dong, Li-Ping Zheng","doi":"10.1145/1141277.1141449","DOIUrl":"https://doi.org/10.1145/1141277.1141449","url":null,"abstract":"Complex environmental modeling often involves a large number of unknown physical and ecological parameters. Parameter estimation is one of the most difficult steps in many modeling activities. In this paper we present a service-oriented framework, named GGPE-G (Grid-enabled Global optimization for General Parameter Estimation), for efficient parameter estimation in heterogeneous, distributed systems. Being presented as services, the optimization algorithms, the physical and ecological process models and clients can interact with each other by XML message interactions. The proposed approach supports a generic parameter estimation procedure and can be easily applied to different modeling environment. In this paper, we explain the design, architecture, and implementation of GGPE-G in details. We also apply GGPE-G to a complex soil-water-atmosphere-plant modeling system to demonstrate its utility and efficiency.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121487803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we discuss how to create and update diagrams after the execution of a model transformation. This is achieved by creating an independent diagram reconciliation tool component that is based on a mapping language from the abstract syntax to the concrete syntax of a modeling language. This approach allows us to decouple model transformation from diagram handling in model transformation languages and tools.
{"title":"Reconciling diagrams after executing model transformations","authors":"Marcus Alanen, Torbjörn Lundkvist, Ivan Porres","doi":"10.1145/1141277.1141573","DOIUrl":"https://doi.org/10.1145/1141277.1141573","url":null,"abstract":"In this paper we discuss how to create and update diagrams after the execution of a model transformation. This is achieved by creating an independent diagram reconciliation tool component that is based on a mapping language from the abstract syntax to the concrete syntax of a modeling language. This approach allows us to decouple model transformation from diagram handling in model transformation languages and tools.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122059692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We show how to extend MOF 2.0 to include an action semantics to support behavioural modelling. We explain why such an extension is useful, particularly for model transformation and consistency checking.
{"title":"An action semantics for MOF 2.0","authors":"R. Paige, D. Kolovos, F. Polack","doi":"10.1145/1141277.1141579","DOIUrl":"https://doi.org/10.1145/1141277.1141579","url":null,"abstract":"We show how to extend MOF 2.0 to include an action semantics to support behavioural modelling. We explain why such an extension is useful, particularly for model transformation and consistency checking.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123509024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Labeled graphs provide a natural way of representing objects and the way they are connected. They have various applications in different fields, such as for example in computational chemistry. They can be represented by relational structures and thus stored in relational databases. Acyclic conjunctive queries form a practically relevant fragment of database queries that can be evaluated in polynomial time. We propose a top-down induction algorithm for learning acyclic conjunctive queries from labeled graphs represented by relational structures. The algorithm allows the use of building blocks which depend on the particular application considered. To compensate for the reduced expressive power of the hypothesis language and thus the potential loss in predictive performance, we combine acyclic conjunctive queries with confidence-rated boosting. In the empirical evaluation of the method we show that it leads to excellent prediction accuracy on the domain of mutagenicity.
{"title":"Effective rule induction from labeled graphs","authors":"T. Horváth, S. Hoche, S. Wrobel","doi":"10.1145/1141277.1141416","DOIUrl":"https://doi.org/10.1145/1141277.1141416","url":null,"abstract":"Labeled graphs provide a natural way of representing objects and the way they are connected. They have various applications in different fields, such as for example in computational chemistry. They can be represented by relational structures and thus stored in relational databases. Acyclic conjunctive queries form a practically relevant fragment of database queries that can be evaluated in polynomial time. We propose a top-down induction algorithm for learning acyclic conjunctive queries from labeled graphs represented by relational structures. The algorithm allows the use of building blocks which depend on the particular application considered. To compensate for the reduced expressive power of the hypothesis language and thus the potential loss in predictive performance, we combine acyclic conjunctive queries with confidence-rated boosting. In the empirical evaluation of the method we show that it leads to excellent prediction accuracy on the domain of mutagenicity.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124939106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Interactive configuration guides a user searching through a large combinatorial space of solutions to a system of constraints. We investigate a class of very expressive underlying constraint satisfaction problems: modular recursive constraint systems of unbounded size. A precomputation step is used to obtain a configuration algorithm for such systems that supports the user efficiently with bounded response time. This precomputation step determines all solutions for each module, which are computed and stored in compact data structures such as Binary Decision Diagrams (BDDs), in order to eliminate run-time search. The precomputation step also detects ill-behaved module collections that have no finite solutions. The runtime interaction algorithm scales well as its response time only depends on the amount of the information passed locally between the modules, and not on the size of the entire configured structure. Our algorithm was implemented and tested on an industrial example, and gives good response times. We believe this is the first known sound and complete algorithm for solving unbounded interactive configuration problems, with bounded response time per interaction.
{"title":"Efficient interactive configuration of unbounded modular systems","authors":"E. Meer, A. Wąsowski, H. Andersen","doi":"10.1145/1141277.1141370","DOIUrl":"https://doi.org/10.1145/1141277.1141370","url":null,"abstract":"Interactive configuration guides a user searching through a large combinatorial space of solutions to a system of constraints. We investigate a class of very expressive underlying constraint satisfaction problems: modular recursive constraint systems of unbounded size. A precomputation step is used to obtain a configuration algorithm for such systems that supports the user efficiently with bounded response time. This precomputation step determines all solutions for each module, which are computed and stored in compact data structures such as Binary Decision Diagrams (BDDs), in order to eliminate run-time search. The precomputation step also detects ill-behaved module collections that have no finite solutions. The runtime interaction algorithm scales well as its response time only depends on the amount of the information passed locally between the modules, and not on the size of the entire configured structure. Our algorithm was implemented and tested on an industrial example, and gives good response times. We believe this is the first known sound and complete algorithm for solving unbounded interactive configuration problems, with bounded response time per interaction.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125089902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Engineering requires tradeoffs [23]. When engineering computer applications, software engineers should consider the costs and benefits to humans as an integral part of the software development process. In this paper we focus on reliability, a central aspect of software quality, and the influence of relationships and various software development contexts on the software developer.
{"title":"Good/fast/cheap: contexts, relationships and professional responsibility during software development","authors":"Marty J. Wolf, F. Grodzinsky","doi":"10.1145/1141277.1141339","DOIUrl":"https://doi.org/10.1145/1141277.1141339","url":null,"abstract":"Engineering requires tradeoffs [23]. When engineering computer applications, software engineers should consider the costs and benefits to humans as an integral part of the software development process. In this paper we focus on reliability, a central aspect of software quality, and the influence of relationships and various software development contexts on the software developer.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125391408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security concerns restrict this access, thus derailing data mining projects. What we need is distributed knowledge discovery that is sensitive to this problem. The key is to obtain valid results, while providing guarantees on the non-disclosure of data. Support vector machine classification is one of the most widely used classification methodologies in data mining and machine learning. It is based on solid theoretical foundations and has wide practical application. This paper proposes a privacy-preserving solution for support vector machine (SVM) classification, PP-SVM for short. Our solution constructs the global SVM classification model from the data distributed at multiple parties, without disclosing the data of each party to others. We assume that data is horizontally partitioned -- each party collects the same features of information for different data objects. We quantify the security and efficiency of the proposed method, and highlight future challenges.
{"title":"Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data","authors":"Hwanjo Yu, Xiaoqian Jiang, Jaideep Vaidya","doi":"10.1145/1141277.1141415","DOIUrl":"https://doi.org/10.1145/1141277.1141415","url":null,"abstract":"Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security concerns restrict this access, thus derailing data mining projects. What we need is distributed knowledge discovery that is sensitive to this problem. The key is to obtain valid results, while providing guarantees on the non-disclosure of data. Support vector machine classification is one of the most widely used classification methodologies in data mining and machine learning. It is based on solid theoretical foundations and has wide practical application. This paper proposes a privacy-preserving solution for support vector machine (SVM) classification, PP-SVM for short. Our solution constructs the global SVM classification model from the data distributed at multiple parties, without disclosing the data of each party to others. We assume that data is horizontally partitioned -- each party collects the same features of information for different data objects. We quantify the security and efficiency of the proposed method, and highlight future challenges.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121786124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Automatic verification techniques, which analyze all processes at once, typically do not scale well for large, complex concurrent software systems because of the theoretic barrier - PSPACE complexity in worst case. In this paper, we present our tool named ARCATS (Architecture Refactoring and Compositional Analysis Tool Suite). ARCATS consists a set of tools to combat state explosion in a divide-and-conquer, hierarchical manner, which is also known as compositional analysis. We build these tools to seek out best combinations to scale the verification to larger software systems.
{"title":"ARCATS: a scalable compositional analysis tool suite","authors":"Yung-Pin Cheng, Yu-Ru Cheng, Hong-Yi Wang","doi":"10.1145/1141277.1141713","DOIUrl":"https://doi.org/10.1145/1141277.1141713","url":null,"abstract":"Automatic verification techniques, which analyze all processes at once, typically do not scale well for large, complex concurrent software systems because of the theoretic barrier - PSPACE complexity in worst case. In this paper, we present our tool named ARCATS (Architecture Refactoring and Compositional Analysis Tool Suite). ARCATS consists a set of tools to combat state explosion in a divide-and-conquer, hierarchical manner, which is also known as compositional analysis. We build these tools to seek out best combinations to scale the verification to larger software systems.","PeriodicalId":269830,"journal":{"name":"Proceedings of the 2006 ACM symposium on Applied computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124384740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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