Object-oriented database systems (OODBS), which aim at meeting the data modeling, performance, cooperative design, and version management requirements of next-generation applications, such as CAD, CAM, CASE, hypermedia, and expert systems, are discussed. Key features of OODBS are presented, a taxonomy of approaches is provided, and architectural and implementation issues, design alternatives, and tradeoffs are examined. A variety of OODB systems, both research prototypes and commercial systems, are summarized. Industry efforts to accelerate a consensus that can lead to standards in the OODB are discussed.>

The goal of this paper is to develop test generation procedures for testing microprocessors in a user environment. Classical fault detection methods based on the gate and flip-flop level or on the state diagram level description of microprocessors are not suitable for test generation. The problem is further compounded by the availability of a large variety of microprocessors which differ widely in their organization, instruction repertoire, addressing modes, data storage, and manipulation facilities, etc. In this paper, a general graph-theoretic model is developed at the register transfer level. Any microprocessor can be easily modeled using information only about its instruction set and the functions performed. This information is readily available in the user's manual. A fault model is developed on a functional level quite independent of the implementation details. The effects of faults in the fault model are investigated at the level of the graph-theoretic model. Test generation procedures are proposed which take the microprocessor organization and the instruction set as parameters and generate tests to detect all the faults in the fault model. The complexity of the test sequences measured in terms of the number of instructions is given. Our effort in generating tests for a real microprocessor and evaluating their fault coverage is described.

A fault model which views faults in semiconductor random-access memories at a functional level instead of at a basic gate level is presented. An efficient 0(n) algorithm to detect all faults in the fault model is described. The fault model is then extended to incorporate more complex faults. An 0(n · log2 n) algorithm is presented for one such extended fault model.