this paper explores the leverage determinants across firms’ sizesbased on the two main theories behind the capital structure, the trade-offand the pecking order theories. a panel data is sued to find therelationship between capital structure and the variables that proxy forbenefits and costs of debt during 1990 to 2006. our findings show thatboth principles help to explain the capital structure...

We tackle the problem of data-structure rewriting including pointer redirections. We propose two basic rewrite steps: (i) Local Redirection and Replacement steps the aim of which is redirecting speciic pointers determined by means of a pattern, as well as adding new information to an existing data ; and (ii) Global Redirection steps which are aimed to redirect all pointers targeting a node towa...

This paper describes the application of machine learning algorithms to the discovery of knowledge in a protein structure database. The problem addressed is the determination of the solvent exposure of each amino acid residue, using different levels of exposed surface to define exposure. First we introduce the baseline classifier which achieves good prediction results despite only taking into ac...

Data structure synthesis is the task of generating data structure implementations from high-level specifications. Recent work in this area has shown potential to save programmer time and reduce the risk of defects. Existing techniques focus on data structures for manipulating subsets of a single collection, but real-world programs often track multiple related collections and aggregate propertie...

We consider the problem of specifying data structures with complex sharing in a manner that is both declarative and results in provably correct code. In our approach, abstract data types are specified using relational algebra and functional dependencies; a novel fuse operation on relational indexes specifies where the underlying physical data structure representation has sharing. We permit the ...

Data structure selection and tuning is laborious but can vastly improve application performance and memory footprint. We introduce ARTEMIS a multiobjective, cloud-based optimisation framework that automatically finds optimal, tuned data structures and rewrites applications to use them. ARTEMIS achieves substantial performance improvements for every project in a set of 29 Java programs uniformly...

Streaming algorithms aim to summarize a large volume of data into a compact summary, by maintaining a data structure that can be incrementally modified as updates are observed. They allow the approximation of particular quantities. The AMS Sketch is focused on approximating the sum of squared entries of a vector defined by a stream of updates. This quantity is naturally related to the Euclidean...