15449712
Maintaining Database Consistency in the Presence of Schema Evolution
With rapid advances in computer network technology and the increasing interest in global information sharing, grows the need for facilities that can effectively maintain the database consistency and program compatibility as the schema evolves. In this paper, we present a general framework based on versions of schema for supporting seamless schema evolution in large-scale object-oriented software systems. We argue that the effectiveness of using the schema version model to materialize schema evolution relies not only on the management of version derivation of schema, but also on the ability to maintain consistency of the database instances with the new schema versions, and the flexibility of sharing instances among versions of schema. Semantics of schema versioning is studied with the objective to facilitate instance adaptation and program compatibility in the presence of schema updates. A number of options for sharing of instances among versions of a schema is developed. Applications may derive versions of schema upon requests for schema updates, and define the instance access scope (the set of objects that are accessible under a given schema version) for each new version of schema by either creating their own instance access scope or inheriting the instance access scope of its ancestor schema versions in terms of a selection of options. The significance of our approach is 
 
 
the abilities for maintaining database consistency, in the presence of schema modification, without irreversibly changing the objects that exist before the schema modification, and 
 
 
the facilities that allow multi-users and applications to create and manipulate different collections of objects under different versions of schema. 
 
 
 
As a consequence, many organizational investments of the existing customer set, such as application design and development, can remain operational in the presence of schema changes.
12589406
VISTA: Validating and Refining Clusters Via Visualization
Clustering is an important technique for understanding of large multidimensional datasets. Most of clustering research to date has been focused on developing automatic clustering algorithms and cluster validation methods. The automatic algorithms are known to work well in dealing with clusters of regular shapes, for example, compact spherical shapes, but may incur higher error rates when dealing with arbitrarily shaped clusters. Although some efforts have been devoted to addressing the problem of skewed datasets, the problem of handling clusters with irregular shapes is still in its infancy, especially in terms of dimensionality of the datasets and the precision of the clustering results considered. Not surprisingly, the statistical indices works ineffective in validating clusters of irregular shapes, too. In this paper, we address the problem of clustering and validating arbitrarily shaped clusters with a visual framework (VISTA). The main idea of the VISTA approach is to capitalize on the power of visualization and interactive feedbacks to encourage domain experts to participate in the clustering revision and clustering validation process. The VISTA system has two unique features. First, it implements a linear and reliable visualization model to interactively visualize multi-dimensional datasets in a 2D star-coordinate space. Second, it provides a rich set of user-friendly interactive rendering operations, allowing users to validate and refine the cluster structure based on their visual experience as well as their domain knowledge.
9143242
Update Monitoring: The CQ Project
In rapidly growing open environments such as the Internet, users experience information starvation in the midst of data overload, due to difficulties similar to finding the needle in a haystack. Update monitoring is a promising area of research where we bring the right information to the user at the right time, instead of forcing the user through manual browsing or repeated submission of queries. As an example of update monitoring research, we outline our work in the Continual Queries (CQ) project, including its basic concepts, software architecture, and current implementation status.
599285
Differential evaluation of continual queries
We define continual queries as a useful tool for monitoring of updated information. Continual queries are standing queries that monitor the source data and notify the users whenever new data matches the query. In addition to periodic refresh, continual queries include Epsilon Transaction concepts to allow users to specify query refresh based on the magnitude of updates. To support efficient processing of continual queries, we propose a differential re-evaluation algorithm (DRA), which exploits the structure and information contained in both the query expressions and the database update operations. The DRA design can be seen as a synthesis of previous research on differential files, incremental view maintenance, and active databases.
13182282
InfoFilter: Supporting quality of service for fresh information delivery
With the explosive growth of the Internet and World Wide Web comes a dramatic increase in the number of users that compete for the shared resources of distributed system environments. Most implementations of application servers and distributed search software do not distinguish among requests to different web pages. This has the implication that the behavior of application servers is quite unpredictable. Applications that require timely delivery of fresh information consequently suffer the most in such competitive environments. This paper presents a model of quality of service (QoS) and the design of a QoS-enabled information delivery system that implements such a QoS model. The goal of this development is two-fold. On one hand, we want to enable users or applications to specify the desired quality of service requirements for their requests so that application-aware QoS adaptation is supported throughout the Web query and search processing. On the other hand, we want to enable an application server to customize how it should respond to external requests by setting priorities among query requests and allocating server resources using adaptive QoS control mechanisms. We introduce the Infopipe approach as the systems support architecture and underlying technology for building a QoS-enabled distributed system for fresh information delivery.
33902172
An Object-Centered Approach for Manipulating Hierarchically Complex Objects
We present an object-centered approach for manipulating hierarchically complex objects, which covers an extended object model and an object-centered query algebra. Extensions of the object model are mainly based on a separation of structural and semantic elements in modeling complex objects, including a general distinction between aggregation reference and association reference, an introduction of type inheritance into aggregation hierarchies and a support for combination of aggregation inheritance with subtype inheritance. Based on the extensions, we develop a query algebra as an integral part of the model. Unlike most of existing algebra-based query languages, our object algebra takes complex object collectively as a unit of high level queries and allows complex objects to be accessed at all levels of aggregation hierarchies without having resort to any kind of path expressions. Features of aggregation hierarchies, such as acyclicity and aggregation inheritance, have played important roles in such a development. We have also formally described the output type of each operator in order for dynamic classification of query results in the IsA type/class lattice. Although the design is based on the chosen object-oriented model, other object-oriented databases are possible. We feel that the proposal largely covers the query requirements for complex objects, and meanwhile provides users with an opportunity to remain within the framework of the model of complex objects while querying database. As a consequence, the flexibility and adaptability of the object-oriented model against schema changes are increased.
45869693
Inter-Departure Times in Base-Stock Inventory-Queues
An inventory-queue is an inventory system controlled by a processing station with queueing. They are natural building blocks for supply chain models. An important and largely open issue for inventory queues is the characterization of their departure processes. In an inventory-queue, departures are triggered either by a job arrival when the output buffer is not empty or otherwise by a service completion. Such departures are more difficult to analyze than departures from a standard queue. The main results in this study are expressions for the probability distributions and squared coefficient of variations of inter-departure times for base-stock inventory-queues with birth–death production processes.
35610063
A Specification-Based Approach to Testing Polymorphic Attributes
The object-oriented features, such as aggregation, inheritance and polymorphism, facilitate software reuse and improve software quality. But those features also cause new problems that traditional testing techniques cannot resolve effectively. Existing researches on object-oriented software testing are mainly based on some graph representations and seldom consider the combinational effect of aggregation, inheritance and polymorphism. For some model-based specifications that do not include graph representations, it is difficult to use the graph based testing techniques to derive test cases. This paper provides an approach to deriving test cases for testing the combinational effect of aggregation, inheritance and polymorphism from a model-based class specification. This approach contains two techniques at intra-class and inter-class testing levels and is mechanized using the algorithms presented in this paper. Finally, through the experimental analysis, we present the effectiveness and applicability of our testing approach.
10661094
Designing information systems in social context: a goal and scenario modelling approach
In order to design a better information system, a designer would like to have notations to visualize how design experts' know-how can be applied according to one's specific social and technology situation. We propose the combined use of a goal-oriented requirements language (GRL) and a scenario-oriented notation Use Case Maps (UCM) for representing design knowledge of information systems. Goal-oriented modelling is used throughout the requirements and design process. In GRL, goals are used to depict business objectives and system requirements, both functional and non-functional. Tasks are used to represent different ways for achieving goals. Means-ends reasoning is used to explore alternative solutions and their operationalizations into implementable system constructs. Social context is modelled in terms of dependency relationships among agents and roles. Scenarios expressed in UCM are used to describe elaborated business processes or workflow. The complementary use of goal-oriented modelling with GRL and scenario modelling with UCM is illustrated with an example of designing a web-based training system.
2115447
Security and privacy requirements analysis within a social setting
Security issues for software systems ultimately concern relationships among social actors stakeholders, system users, potential attackers - and the software acting on their behalf. We propose a methodological framework for dealing with security and privacy requirements based on i*, an agent-oriented requirements modeling language. The framework supports a set of analysis techniques. In particular, attacker analysis helps identify potential system abusers and their malicious intents. Dependency vulnerability analysis helps detect vulnerabilities in terms of organizational relationships among stakeholders. Countermeasure analysis supports the dynamic decision-making process of defensive system players in addressing vulnerabilities and threats. Finally, access control analysis bridges the gap between security requirement models and security implementation models. The framework is illustrated with an example involving security and privacy concerns in the design of agent-based health information systems. In addition, we discuss model evaluation techniques, including qualitative goal model analysis and property verification techniques based on model checking.
10550445
Fuzzy Bayesian Networks - A General Formalism for Representation, Inference and Learning with Hybrid Bayesian Networks
This paper proposes a general formalism for representation, inference and learning with general hybrid Bayesian networks in which continuous and discrete variables may appear anywhere in a directed acyclic graph. The formalism fuzzifies a hybrid Bayesian network into two alternative forms: the first form replaces each continuous variable in the given directed acyclic graph (DAG) by a partner discrete variable and adds a directed link from the partner discrete variable to the continuous one. The mapping between two variables is not crisp quantization but is approximated (fuzzified) by a conditional Gaussian (CG) distribution. The CG model is equivalent to a fuzzy set but no fuzzy logic formalism is employed. The conditional distribution of a discrete variable given its discrete parents is still assumed to be multinomial as in discrete Bayesian networks. The second form only replaces each continuous variable whose descendants include discrete variables by a partner discrete variable and adds a directed link from that partner discrete variable to the continuous one. The dependence between the partner discrete variable and the original continuous variable is approximated by a CG distribution, but the dependence between a continuous variable and its continuous and discrete parents is approximated by a conditional Gaussian regression (CGR) distribution. Obviously, the second form is a finer approximation, but restricted to CGR models, and requires more complicated inference and learning algorithms. This results in two general approximate representations of a general hybrid Bayesian networks, which are called here the fuzzy Bayesian network (FBN) form-I and form-II. For the two forms of FBN, general exact inference algorithms exists, which are extensions of the junction tree inference algorithm for discrete Bayesian networks. Learning fuzzy Bayesian networks from data is different from learning purely discrete Bayesian networks because not only all the newly converted discrete variables are latent in the data, but also the number of discrete states for each of these variables and the CG or CGR distribution of each continuous variable given its partner discrete parents or both continuous and discrete parents have to be determined.