Abstract
Various programming languages allow the construction of structure-shy programs. Such programs are defined generically for many different datatypes and only specify specific behavior for a few relevant subtypes. Typical examples are XML query languages that allow selection of subdocuments without exhaustively specifying intermediate element tags. Other examples are languages and libraries for polytypic or strategic functional programming and for adaptive object-oriented programming. In this paper, we present an algebraic approach to transformation of declarative structure-shy programs, in particular for strategic functions and XML queries. We formulate a rich set of algebraic laws, not just for transformation of structure-shy programs, but also for their conversion into structure-sensitive programs and vice versa. We show how subsets of these laws can be used to construct effective rewrite systems for specialization, generalization, and optimization of structure-shy programs. We present a type-safe encoding of these rewrite systems in Haskell which itself uses strategic functional programming techniques. Copyright © 2007 ACM.

Abstract
Coupled transformations occur in software evolution when multiple artifacts must be modified in such a way that they remain consistent with each other. An important example involves the coupled transformation of a data type, its instances, and the programs that consume or produce it. Previously, we have provided a formal treatment of transformation of the first two: data types and instances. The treatment involved the construction of type-safe, type-changing strategic rewrite systems. In this paper, we extend our treatment to the transformation of corresponding data processing programs. The key insight underlying the extension is that both data migration functions and data processors can be represented type-safely by a generalized abstract data type (GADT). These representations are then subjected to program calculation rules, harnessed in type-safe, type-preserving strategic rewrite systems. For ease of calculation, we use point-free representations and corresponding calculation rules. Thus, coupled transformations are carried out in two steps. First, a type-changing rewrite system is applied to a source type to obtain a target type together with (representations of) migration functions between source and target. Then, a type-preserving rewrite system is applied to the composition of a migration function and a data processor on the source (or target) type to obtain a data processor on the target (or source) type. All rewrites are type-safe.

Abstract
A two-level data transformation consists of a type-level transformation of a data format coupled with value level transformations of data instances corresponding to that format. We have implemented a system for performing two-level transformations on XML schemas and their corresponding documents, and on SQL schemas and the databases that they describe. The core of the system consists of a combinator library for composing type-changing rewrite rules that preserve structural information and referential constraints. We discuss the implementation of the system's core library, and of its SQL and XML front-ends in the functional language Haskell. We show how the system can be used to tackle various two-level transformation scenarios, such as XML schema evolution coupled with document migration, and hierarchical-relational data mappings that convert between XML documents and SQL databases.

Abstract

Abstract
Multi-master update everywhere database replication, as achieved by protocols based on group communication such as DBSM and Postgres-R, addresses both performance and availability. By scaling it to wide area networks, one could save costly bandwidth and avoid large round-trips to a distant master server Also, by ensuring that updates are safely stored at a remote site within transaction boundaries, disaster recovery is guaranteed. Unfortunately, scaling existing cluster based replication protocols is troublesome. In this paper we present a database replication protocol based on group communication that targets interconnected clusters. In contrast with previous proposals, it uses a separate multicast group for each cluster and thus does not impose any additional requirements on group communication, easing implementation and deployment in a rea setting. Nonetheless, the protocol ensures one-copy equivalence while allowing all sites to execute update transactions. Experimental evaluation using the workload of the industry standard TPC-C benchmark confirms the advantages of the approach.

Abstract
Recently renewed interest in scalable database systems for shared nothing clusters has been supported by replication protocols based on group communication that are aimed at seamlessly extending the native consistency criteria of centralized database management systems. By using a read-one/write-all-available approach and avoiding the fine-grained synchronization associated with traditional distributed locking, one needs just a single distributed interaction step for each update transaction. Therefore the system can easily be scaled to a large number of replicas, especially, with read intensive loads typical of Web server support environments. In this paper we point out that 1-copy equivalence for causal consistency, which is subsumed by both serializability and snap-shot isolation criteria, depends on basic session guarantees that are costly to ensure in clusters, especially in a multi-tier environment. We then point out a simple solution that guarantees causal consistency in the Database State Machine protocol and evaluate its performance, thus highlighting the cost of seamlessly providing common consistency criteria of centralized databases in a clustered environment. Copyright 2006 ACM.