MIXIN COMPOSITION SYNTHESIS BASED ON INTERSECTION TYPES

We present a method for synthesizing compositions of mixins using type inhabitation in intersection types. First, recursively defined classes and mixins, which are functions over classes, are expressed as terms in a lambda calculus with records. Intersection types with records and record-merge are used to assign meaningful types to these terms without resorting to recursive types. Second, typed terms are translated to a repository of typed combinators. We show a relation between record types with record-merge and intersection types with constructors. This relation is used to prove soundness and partial completeness of the translation with respect to mixin composition synthesis. Furthermore, we demonstrate how a translated repository and goal type can be used as input to an existing framework for composition synthesis in bounded combinatory logic via type inhabitation. The computed result is a class typed by the goal type and generated by a mixin composition applied to an existing class

A Long and Winding Road Towards Modular Synthesis

This paper offers a personal reflection on a number of attempts over the past decade to apply a variety of approaches to construct a product line for solitaire card games implemented in Java. A product line shares a common set of features developed from a common set of software artifacts. A feature is a unit of functionality within a system that is visible to an end-user and can be used to differentiate members of the product line. The ultimate research goal is to assemble a product line by selecting a configuration of a set of pre-designed modular units and developing new units as necessary for individual members; in short, incorporating configuration into routine development. A secondary goal was to develop a suitable tool chain that could be integrated with existing IDEs to achieve widespread acceptance of the approach. We compare progress against by-hand development in Java. During this period we investigated a number of approaches from the research literature, including components, aspects, and layers; these efforts led to a productive collaboration supported by type theory

Combinatory synthesis of classes using feature grammars

We describe a method for automatically transforming feature grammars into type-specifications which are subsequently used to synthesize a code-generator for a product of a given feature selection. Feature models are assumed to be given in the form of feature grammars with constraints, and we present a generic type-theoretic representation of such grammars. Our synthesis method is based on an extension of previous work in combinatory logic synthesis, where semantic types can be superimposed onto native APIs to specify a repository of components as well as synthesis goals. In our case, semantic types correspond to feature selections. We use an encoding of boolean logic in intersection types, which allows us to directly represent logical formulas expressing complex feature selection constraints. The novelty of our approach is the possibility to perform retrieval, selection and composition of products in a unified form, without sacrificing modularity. In contrast to constraint based methods, multiple selections of a single feature can coexist

Search and Aggregation in XML Documents

International audienceInformation retrieval encounters a migration from the traditional paradigm (returning an ordered list of responses) to the aggregate search paradigm (grouping the most comprehensive and relevant answers into one final aggregated document). Nowadays extensible markup language (XML) is an important standard of information exchange and representation. Usually the tree representation of documents and queries is used to process them. It allows to consider the XML documents retrieval as a tree matching problem between the document trees and the query tree. Several paradigms for retrieving XML documents have been proposed in the literature but only a few of them try to aggregate a set of XML documents in order to provide more significant answers for a given query. In this paper, we propose and evaluate an aggregated search method to obtain the most accurate and richest answers in XML fragment search. Our search method is based on the Top-k Approximate Subtree Matching (TASM) algorithm and a new similarity function is proposed to improve the returned fragments. Then an aggregation process is presented to generate a single aggregate response containing the most relevant, exhaustive and non-redundant information given by the fragments. The method is evaluated on two real world datasets. Experimentations show that it generates good results in terms of relevance and quality