We explore the automatic generation of test data that respect constraints expressed in the Object-Role Modeling(ORM) language. ORM is a popular conceptual modelinglanguage, primarily targeting database applications, withsignificant uses in practice. The general problem of evenchecking whether an ORM diagram is satisfiable is quitehard: restricted forms are easily NP-hard and the problemis undecidable for some expressive formulations of ORM.Brute-force mapping to input for constraint and SAT solversdoes not scale: state-of-the-art solvers fail to find data to satisfy uniqueness and mandatory constraints in realistic time even for small examples. We instead define a restricted subset of ORM that allows efficient reasoning yet contains most constraints overwhelmingly used in practice. We show that the problem of deciding whether these constraints are consistent (i.e., whether we can generate appropriate test data) is solvable in polynomial time, and we produce a highly efficient (interactive speed) checker. Additionally, we analyze over 160 ORM diagrams that capture data models from industrial practice and demonstrate that our subset of ORM is expressive enough to handle their vast majority

We present and evaluate the idea of adaptive processor cache management. Specifically, we describe a novel and general scheme by which we can combine any two cache management algorithms (e.g., LRU, LFU, FIFO, Random) and adaptively switch between them, closely tracking the locality characteristics of a given program. The scheme is inspired by recent work in virtual memory management at the operating system level, which has shown that it is possible to adapt over two replacement policies to provide an aggregate policy that always performs within a constant factor of the better component policy. A hardware implementation of adaptivity requires very simple logic but duplicate tag structures. To reduce the overhead, we use partial tags, which achieve good performance with a small hardware cost. In particular, adapting between LRU and LFU replacement policies on an 8-way 512KB L2 cache yields a 12.7% improvement in average CPI on applications that exhibit a non-negligible L2 miss ratio. Our approach increases total cache storage by 4.0%, but it still provides slightly better performance than a conventional 10-way set-associative 640KB cache which requires 25% more storage