We conducted an eye-tracking study of mechanical problem solving from cross-sectional diagrams of devices. Response time, accuracy and eye movement data were collected and analyzed for 72 problem-solving episodes (9 s...
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In this paper, we consider a new atomicity model, write all with collision (WAC), and compare it with existing models considered in the literature. This model captures the computations in sensor networks. We show that...
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The behavior and performance of MPI non-blocking message passing operations are sensitive to implementation specifics as they are heavily dependant on available system level buffers. In this paper we investigate the b...
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Program slicing is widely used in applications such as program comprehension, software testing, debugging, measurement, and re-engineering. This paper proposes a new approach for program slicing, called modular monadi...
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The object constraint language (OCL) was introduced as part of the Unified Modeling Language (UML). Its main purpose is to make UML models more precise by providing a constraint language. For example, operation contra...
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The object constraint language (OCL) was introduced as part of the Unified Modeling Language (UML). Its main purpose is to make UML models more precise by providing a constraint language. For example, operation contracts and statechart guard conditions can be precisely defined using OCL. There has been an ongoing debate on the usefulness of using OCL in UML-based development, questioning whether the additional effort and formality were worth the benefit. This work presents the results of a controlled experiment that investigates the impact of using OCL on model comprehension and maintainability. Current results show that, once past an initial learning curve, significant benefits can be obtained by using OCL in combination with UML diagrams.
Peer-to-Peer (P2P) computing is said to be the next wave of computing after client-server and web-based computing. It provides an opportunity to harness a lot of idle peer-resources such as desktop computers across th...
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This paper describes TRAP/J, a software tool that enables new adaptable behavior to be added to existing Java applications transparently (that is, without modifying the application source code and without extending th...
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UML is a good tool to represent ontologies. When using UML for Ontology development, one of the principal goals is to assure the quality of ontologies. UML class diagrams provide a static modeling capability that is w...
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ISBN:
(纸本)0769521185
UML is a good tool to represent ontologies. When using UML for Ontology development, one of the principal goals is to assure the quality of ontologies. UML class diagrams provide a static modeling capability that is well suited for representing ontologies, so the structural complexity of a UML class diagram is one of the most important measures to evaluate the quality of the ontologies. This paper uses weighted class dependence graphs to represent a given class diagrams, and then presents a structure complexity measure for the UML class diagrams based on entropy distance. It considers complexity of both classes and relationships between the classes, and presents rules for transforming complexity value of classes and different lands of relations into a weighted class dependence graphs. This method can measure the structure complexity of class diagrams objectively.
We concentrate on automated synthesis of multitolerant programs, i.e., programs that tolerate multiple classes of faults and provide a (possibly) different level of fault-tolerance to each class. We consider three lev...
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We concentrate on automated synthesis of multitolerant programs, i.e., programs that tolerate multiple classes of faults and provide a (possibly) different level of fault-tolerance to each class. We consider three levels of fault-tolerance: (1) failsafe, where in the presence of faults, the synthesized program guarantees safety, (2) nonmasking, where in the presence of faults, the synthesized program recovers to states from where its safety and liveness are satisfied, and (3) masking where in the presence of faults the synthesized program satisfies safety and recovers to states from where its safety and liveness are satisfied. We focus on the automated synthesis of finite-state multitolerant programs in high atomicity model where the program can read and write all its variables in an atomic step. We show that if one needs to add failsafe (respectively, nonmasking) fault-tolerance to one class of faults and masking fault-tolerance to another class of faults then such addition can be done in polynomial time in the state space of the fault-intolerant program. However, if one needs to add failsafe fault-tolerance to one class of faults and nonmasking fault-tolerance to another class of faults then the resulting problem is NP-complete. We find this result to be counterintuitive since adding failsafe and nonmasking fault-tolerance to the same class of faults (which is equivalent to adding masking fault-tolerance to that class of faults) can be done in polynomial time, whereas adding failsafe fault-tolerance to one class of faults and nonmasking fault-tolerance to a different class of faults is NP-complete.
Path probing is essential to maintain an efficient overlay network topology. However, the cost of complete probing can be as high as O(n/sup 2/), which is prohibitive in large-scale overlay networks. Recently we propo...
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Path probing is essential to maintain an efficient overlay network topology. However, the cost of complete probing can be as high as O(n/sup 2/), which is prohibitive in large-scale overlay networks. Recently we proposed a method that trades probing overhead for inference accuracy in sparse networks such as the Internet. The method uses physical path information to infer path quality for all of the n/spl times/(n-1) overlay paths, while actually probing only a subset of the paths. We propose and evaluate a distributed approach to implement this method. We describe a minimum diameter, link-stress bounded overlay spanning tree, which is used to collect and disseminate path quality information. All nodes in the tree collaborate to infer the quality of all paths. Simulation results show this approach can achieve a high-level of inference accuracy while reducing probing overhead and balancing link stress on the spanning tree.
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