2955672
Grammatically Interpreting Feature Compositions
Abstract : Feature modeling is a popular domain analysis method for describing the commonality and variability among the domain products. The current formalisms of feature modeling do not have enough support for automated domain product configuration and validation. We have developed a theory of feature modeling: a feature model is analogous to a definition of a language; a particular feature composition instance (domain product) is analogous to a program written in that language; and the way the features can be assembled to form a product is analogous to the way various tokens can be assembled to form a program. To apply this theory, we have developed a meta-language Two-Level Grammar++ to specify feature models. The interpreter derived from the feature model specification performs automated product configuration and product quality validation.
17507277
Transforming business process models: enabling programming at a higher level
Two practical paradigms are presented, which facilitate domain concepts to be directly used to model business operations: the first paradigm is based on the business artifacts and their life cycle; the second paradigm is based on the business tasks and their sequencing. Transformation is an effective way to bridge the gap between business level analysis and IT solutions. We present algorithms that transform business process models based on these two paradigms into IT solutions of Web service platform. The specific problems we addressed in this transformation are: 1) how to generate the implementation code of an optimal size; 2) how to preserve the natural structure of business process models in the generated code.
47079351
A language based formalism for domain driven development
The evolution of programming languages (e.g. machine languages, assembly languages and high level languages) has been the driving force for the evolution of software development from the machine-centric to the application-centric. The 4th generation languages (4GLs), languages defined directly by the composition of domain features, serve as the language-based formalism for the emerging Domain Driven Development paradigm. The 4GLs are defined in Two-Level Grammar++ and can be compiled into 3GLs using the 4GL compiler framework.
15389203
Analyzing and enhancing the resilience of structured peer-to-peer systems
In this paper, we propose an approach to analyze the resilience of structured peer-to-peer (P2P) systems under failures. The approach is Markov-chain based, and can be applied to systems with relatively stable size and uniform distribution of nodes. We apply our approach to several well-known structured P2P systems. We find that different system features (types of neighbors of nodes) in P2P systems have different impacts on their resilience against failures. Following this observation, we propose to add some extra neighbor(s) to CAN using small-world model principles to form a so-called CAN-SW system. We then apply the proposed approach to analyze its resilience. We find that the performance is improved significantly, particularly, in terms of the average path length.
9772845
Performance Measurements for Privacy Preserving Data Mining
This paper establishes the foundation for the performance measurements of privacy preserving data mining techniques. The performance is measured in terms of the accuracy of data mining results and the privacy protection of sensitive data. On the accuracy side, we address the problem of previous measures and propose a new measure, named “effective sample size”, to solve this problem. We show that our new measure can be bounded without any knowledge of the data being mined, and discuss when the bound can be met. On the privacy protection side, we identify a tacit assumption made by previous measures and show that the assumption is unrealistic in many situations. To solve the problem, we introduce a game theoretic framework for the measurement of privacy.
5322268
Fault-tolerant real-time communication in FDDI-based networks
FDDI-Based Reconfigurable Networks have an architecture that is suitable for delivering messages that have hard real-time constraints as well as certain fault-tolerance requirements. This architecture uses multiple FDDI networks to connect hosts and provides for automatic reconfiguration to maintain high network bandwidth in spite of faults. An important open problem is how resources in such networks should be managed in order to guarantee that the fault-tolerant real-time requirements of messages are met. This paper presents an efficient and practical solution to this problem. Our solution consists of off-line and on-line components. On-line management deals with run-time manipulation of messages and network resources. A message grouping approach simplifies on-line management. Off-line management deals with message grouping, bandwidth allocation and schedulability verification. Three approaches are investigated: spatial redundancy, temporal redundancy and an integrated approach. It is shown that the integrated approach has the best performance. Our solution is compatible with the FDDI and SAFENET standards.
205343629
A network flow approach to the Minimum Common Integer Partition Problem
In the k-Minimum Common Integer Partition Problem, abbreviated as k-MCIE we are given k multisets X1,...,Xk of positive integers, the goal is to find an integer multiset T of the minimum size such that for every i, we can partition each of the integers in Xi so that the disjoint (multiset) union of their partitions equals T. This problem has applications in computational molecular biology, in particular, ortholog assignment and DNA hybridization fingerprint assembly. The problem is known to be NP-hard for any k ≥ 2. In this article, we improve the approximation ratio for k-MCIP by viewing this problem as a flow decomposition problem in some flow network. We show an efficient 0.5625k-approximation algorithm, improving upon the previously best known 0.6139k-approximation algorithm for this problem.
13980635
A Note on Dynamic Data Driven Wildfire Modeling
A proposed system for real-time modeling of wildfires is described. The system involves numerical weather and fire prediction, automated data acquisition from Internet sources, and input from aerial photographs and sensors. The system will be controlled by a non-Gaussian ensemble filter capable of assimilating out-of-order data. The computational model will run on remote supercomputers, with visualization on PDAs in the field connected to the Internet via a satellite.