Database Programming Environment Research Articles

Interactive Correction and Recommendation for Computer Language Learning and Training

Active learning and training is a particularly effective form of education. In various domains, skills are equally important to knowledge. We present an automated learning and skills training system for a database programming environment that promotes procedural knowledge acquisition and skills training. The system provides meaningful knowledge-level feedback such as correction of student solutions and personalized guidance through recommendations. Specifically, we address automated synchronous feedback and recommendations based on personalized performance assessment. At the core of the tutoring system is a pattern-based error classification and correction component that analyzes student input in order to provide immediate feedback and in order to diagnose student weaknesses and suggest further study material. A syntax-driven approach based on grammars and syntax trees provides the solution for a semantic analysis technique. Syntax tree abstractions and comparison techniques based on equivalence rules and pattern matching are specific approaches.

Personalised correction, feedback and guidance in an automated tutoring system for skills training

In addition to knowledge, in various domains skills are equally important. Active learning and training are effective forms of education. We present an automated skills training system for a database programming environment that promotes procedural knowledge acquisition and skills training. The system provides support features such as correction of solutions, feedback and personalised guidance, similar to interactions with a human tutor. Specifically, we address synchronous feedback and guidance based on personalised assessment. Each of these features is automated and includes a level of personalisation and adaptation. At the core of the system is a pattern-based error classification and correction component that analyses student input.

Evaluation and optimization of query programs in an object-oriented and symbolic information system

OASIS, a database programming environment that extends UNIX with the concept of persistent objects, is discussed. The OASIS query languages extend conventional database query languages with procedural methods and general control statements. As the complexity of the languages makes it difficult to device a query optimizer based on a universally applicable algorithm, each query in OASIS is optimized based on a collection of basic patterns for which each pattern is associated with a separation query optimization algorithm. The optimization techniques for a set of basic patterns consisting of iterative statements and a set of nested statements is described. The optimization techniques discussed include an extended decomposition algorithm, evaluation of multiple conditions, data dependence analysis, and optimization of queries with arbitrary nesting. >

An approach to embed knowledge in database systems

Most tools for developing knowledge-based systems do not integrate well with databases. This lack of integration is hampered by slow database queries or by overly limited database interfaces. This paper describes a novel approach to the knowledge-data integration problem by embedding knowledge directly into the database systems. This approach entails the simple but powerful extension of a database system to increase its ability to represent and manipulate knowledge. A description is given of KBase, an environment for embedding knowledge in databases using facilities and extended constructs of the familiar dBase database programming environment. At the end, the applicability of the approach is illustrated with a developmental prototype, CICONSA, for scheduling construction projects.