Reify Your Collection Queries for Modularity and Speed!

Modularity and efficiency are often contradicting requirements, such that programers have to trade one for the other. We analyze this dilemma in the context of programs operating on collections. Performance-critical code using collections need often to be hand-optimized, leading to non-modular, brittle, and redundant code. In principle, this dilemma could be avoided by automatic collection-specific optimizations, such as fusion of collection traversals, usage of indexing, or reordering of filters. Unfortunately, it is not obvious how to encode such optimizations in terms of ordinary collection APIs, because the program operating on the collections is not reified and hence cannot be analyzed. We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala collections API that allows such analyses and optimizations to be defined and executed within Scala, without relying on external tools or compiler extensions. SQuOpt provides the same "look and feel" (syntax and static typing guarantees) as the standard collections API. We evaluate SQuOpt by re-implementing several code analyses of the Findbugs tool using SQuOpt, show average speedups of 12x with a maximum of 12800x and hence demonstrate that SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page

Scala Server Faces

Progress in the Java language has been slow over the last few years. Scala is emerging as one of the probable successors for Java with features such as type inference, higher order functions, closure support and sequence comprehensions. This allows object-oriented yet concise code to be written using Scala. While Java based MVC frameworks are still prevalent, Scala based frameworks along with Ruby on Rails, Django and PHP are emerging as competitors. Scala has a web framework called Lift which has made an attempt to borrow the advantages of other frameworks while keeping code concise. Since Sun’s MVC framework, Java Server Faces 2.0 and its future versions seem to be heading in a reasonably progressive direction; I have developed a framework which attempts to overcome its limitations. I call such a framework ―Scala Server Faces‖. This framework provides a way of writing Java EE applications in Scala yet borrow from the concept of ―convention over configuration‖ followed by rival web frameworks. Again, an Eclipse tool is provided to make the programmer\u27s task of writing code on the popular Eclipse platform. Scala Server Faces, the framework and the tool allows the programmer to write enterprise web applications in Scala by providing features such as templating support, CRUD screen generation for database model objects, an Ant script to help deployment and integration with the Glassfish Application Server

Using schema transformation pathways for data lineage tracing

With the increasing amount and diversity of information available on the Internet, there has been a huge growth in information systems that need to integrate data from distributed, heterogeneous data sources. Tracing the lineage of the integrated data is one of the problems being addressed in data warehousing research. This paper presents a data lineage tracing approach based on schema transformation pathways. Our approach is not limited to one specific data model or query language, and would be useful in any data transformation/integration framework based on sequences of primitive schema transformations

RAM: array processing over a relational DBMS

Developing multimedia applications in relational databases is hindered by a mismatch in computational frameworks. Efficient manipulation of multimedia data calls for array-based processing, which at best is available as a database add-on, not supported by the query optimizer. As a result, array-based processing ends up in dedicated programs outside the DBMS: non-reusable black boxes. The goal of our research is to reduce this gap between user-needs and system functionality by developing a seemless integration of array processing in a relational algebra engine. The paper introduces a declarative language for array-expressions based on the array comprehension, and its mapping to a relational kernel in a prototype implementation. The layered architecture of the resulting array database management system allows the use of structural knowledge available in the array data type. This additional source of information can be exploited for query optimization, which is demonstrated with a case study. The experiments show how the performance of a standard tool for matrix computations can be achieved without sacrificing data independence, highlighting however a critical aspect in the DBMS architecture proposed

A computer scientist's reconstruction of quantum theory

The rather unintuitive nature of quantum theory has led numerous people to develop sets of (physically motivated) principles that can be used to derive quantum mechanics from the ground up, in order to better understand where the structure of quantum systems comes from. From a computer scientist's perspective we would like to study quantum theory in a way that allows interesting transformations and compositions of systems and that also includes infinite-dimensional datatypes. Here we present such a compositional reconstruction of quantum theory that includes infinite-dimensional systems. This reconstruction is noteworthy for three reasons: it is only one of a few that includes no restrictions on the dimension of a system; it allows for both classical, quantum, and mixed systems; and it makes no a priori reference to the structure of the real (or complex) numbers. This last point is possible because we frame our results in the language of category theory, specifically the categorical framework of effectus theory.Comment: 42 page