The Venus Rule Language introduced a declarative basis for structured rule-based programming (as opposed to procedural encapsulation). The method is closely related to the nested transaction model for concurrency control and otherwise the language has been designed to serve as the basis of both main-memory and hard (or expert) activedatabase systems. We present a quantitative evaluation of the impact on development costs of the Venus language on rule-based programs. The basis of the study is a reimplementation of ALEXSYS, an active-database program originally developed in 0PS5 and currently in use in the financial securities industry. The measurements indicate substantially improved code, suggesting substantially reduced development and life-cycle costs.
We present the architecture and a performance assessment of an extensible query optimizer written in Venus. Venus is a generalpurpose active-database rule language embedded in C++. Following the developments in extensible database query optimizers, first in rule-based form, followed by optimizers written as object-oriented programs, the Venus-based optimizer avails to the advantages of both. Venus' modular structure allows us to go a step further and provide extensibility in search by defining parameterized search components in a declarative form that has the additional effect of integrating heuristic and cost-based optimization. We compare optimizers developed with Volcano, OPI++ and Venus. Venus' optimizing compiler yields code whose performance is comparable with Volcano and OPT++ on smaller queries. The ability to introduce additional pruning heuristics yields better scalability on larger queries. Evaluation of the system using quantitative software metrics supports a claim that the Venusbased optimizer is more easily maintained and extended than are its predecessors.
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