The design of efJicient storage hierorchies generally involves the repeated running of "typical" program address traces through a simulated storage system while various hierarchy design parameters are djusted. This paper describes a new and eficient method of determining, in one pass of an address trace, performance measures for a large class of demand-paged, multilevel storage systems utilizing a variety of mapping schemes and replacement algorithms. The technique depends on an algorithm classification, called "stack algorithms," examples of which are "least frequently used," "least recently used," "optimal," and "random replacement" algorithms. The techniques yield the exact access frequent-v to each storage device, which can be used to estimate the overall performance of actual storage hierarchies.

System R, an experimental database system, was constructed to demonstrate that the usability advantages of the relational data model can be realized in a system with the complete function and high performance required for everyday production use. This paper describes the three principal phases of the System R project and discusses some of the lessons learned from System R about the design of relational systems and database systems in general.

System R supports a high-level relational user language called SQL which may be used by ad hoc users at terminals or as an embedded data sublanguage in PL/I or COBOL. Host-language programs with embedded SQL statements are processed by the System R precompiler which replaces the SQL statements by calls to a machine-language access module. The precompilation approach removes much of the work of parsing, name binding, and access path selection from the path of a running program, enabling highly efficient support for repetitive transactions. Ad hoc queries are processed by a similar approach of name binding and access path selection which takes place on-line when the query is specified. By providing a flexible spectrum of binding times, System R permits transaction-oriented programs and ad hoc query users to share a database without loss of efficiency. System R is an experimental database management system designed and built by members of the IBM San Jose Research Laboratory as part of a research program on the relational model of data. This paper describes the architecture of System R, and gives some preliminary measurements of system performance in both the ad hoc query and the “canned program” environments.

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Finite-length reference string of arbitrary structure are considered, and an exact expression for average working set size in terms of "corrected" interreference interval statistics is derived. An example is discussed; upper and lower bounds are obtained; and the average working set size function is shown to be efficiently ohtained for a set of page sizes, in a single pass of the reference string.This work follows the developments of a paper by Denning and Schwartz, who consider infinite-length reference strings which satisfy certain statistical properties and who derive an expression relating the asymptotic average working set size to the asymptotic missing page rate function under working set replacement.