Models for persistence in lazy functional programming systems

Research into providing support for long term data in lazy functional programming systems is presented in this thesis. The motivation for this work has been to reap the benefits of integrating lazy functional programming languages and persistence. The benefits are: the programmer need not write code to support long term data since this is provided as part of the programming system; persistent data can be used in a type safe way since the programming language type system applies to data with the whole range of persistence; the benefits of lazy evaluation are extended to the full lifetime of a data value. Whilst data is reachable, any evaluation performed on the data persists. A data value changes monotonically from an unevaluated state towards a completely evaluated state over time. Interactive data intensive applications such as functional databases can be developed. These benefits are realised by the development of models for persistence in lazy functional programming systems. Two models are proposed which make persistence available to the functional programmer. The first, persistent modules, allows values named in modules to be stored in persistent storage for later reuse. The second model, stream persistence allows dynamic, interactive access to persistent storage. These models are supported by a system architecture which incorporates a persistent abstract machine, PCASE, integrated with a persistent object store. The resulting persistent lazy functional programming system, Staple, is used in prototyping and functional database modelling experiments

P-Pascal : a data-oriented persistent programming language

Bibliography: pages 187-199.Persistence is measured by the length of time an object is retained and is usable in a system. Persistent languages extend general purpose languages by providing the full range of persistence for data of any type. Moreover, data which remains on disk after program termination, is manipulated in the same way as transient data. As these languages are based on general purpose programming languages, they tend to be program-centred rather than data-centred. This thesis investigates the inclusion of data-oriented features in a persistent programming language. P-Pascal, a Persistent Pascal, has been designed and implemented to develop techniques for data clustering, metadata maintenance, security enforcement and bulk data management. It introduces type completeness to Pascal and in particular shows how a type-complete set constructor can be provided. This type is shown to be a practical and versatile mechanism for handling bulk data collections in a persistent environment. Relational algebra operators are provided and the automatic optimisation of set expressions is performed by the compiler and the runtime system. The P-Pascal Abstract Machine incorporates two complementary data placement strategies, automatic updating of type information, and metadata query facilities. The protection of data types, primary (named) objects and their individual components is supported. The challenges and opportunities presented by the persistent store organisation are discussed, and techniques for efficiently exploiting these properties are proposed. We also describe the effects on a data-oriented system of treating persistent and transient data alike, so that they cannot be distinguished statically. We conclude that object clustering, metadata maintenance and security enforcement can and should be incorporated in persistent programming languages. The provision of a built-in, type-complete bulk data constructor and its non-procedural operators is demonstrated. We argue that this approach is preferable to engineering such objects on top of a language, because of greater ease of use and considerable opportunity for automatic optimisation. The existence of such a type does not preclude programmers from constructing their own bulk objects using other types - this is but one advantage of a persistent language over a database system