Design patterns for database pedagogy: a proposal
Proceedings of the 36th SIGCSE technical symposium on Computer science education
Using predicate fields in a highly flexible industrial control system
OOPSLA '05 Companion to the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Towards automatic integration of the business-data layers in enterprise-systems
Journal of Computational Methods in Sciences and Engineering
Separating data access crosscutting concerns using AspectJ: a quantitative assessment
SE '08 Proceedings of the IASTED International Conference on Software Engineering
Research on performance optimization and implementation of oracle database
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
A pattern language for metadata-based frameworks
Proceedings of the 16th Conference on Pattern Languages of Programs
Towards a theory of genericity based on government and binding
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
NGITS'06 Proceedings of the 6th international conference on Next Generation Information Technologies and Systems
A single semester web programming course model
Journal of Computing Sciences in Colleges
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From the Publisher:25 proven patterns for improving data access and application performance Efficient, high-quality data access code is crucial to the performance and usability of virtually any enterprise application--and there's no better way to improve an existing system than to optimize its data access code. Regardless of database engine, platform, language, orapplication, developers repeatedly encounter the same relational database access challenges. In Data Access Patterns, Clifton Nock identifies 25 proven solutions, presenting each one in the form of a clear, easy-to-use pattern. These patterns solve an exceptionally wide range of problems including creating efficient database-independent applications, hiding obscure database semantics from users, speeding database resource initialization, simplifying development and maintenance, improving support for concurrency and transactions, and eliminating data access bottlenecks. Every pattern is illustrated with fully commented Java/JDBC code examples, as well as UML diagrams representing interfaces, classes, and relationships. The patterns are organized into five categories: Decoupling Patterns: Build cleaner, more reliable systems by decoupling data access code from other application logic Resource Patterns: Manage relational database resources more efficiently Input/Output Patterns: Simplify I/O operations by translating consistently between "physical" relational data and domain object representations of that data Cache Patterns: Use caching strategically, to optimize the tradeoffs between data access optimization and cache overhead Concurrency Patterns: Implement concurrencyand transactions more effectively and reliably Data Access Patterns demystifies techniques that have traditionally been used only in the most robust data access solutions--making those techniques practical for every software developer, architect, and designer.