Abstract
Logic Programming languages, such as Prolog, provide a high-level, declarative approach to programming. Despite the power, flexibility and good performance that Prolog systems have achieved, some deficiencies in Prolog's evaluation strategy - SLD resolution - limit the potential of the logic programming paradigm. Tabled evaluation is a recognized and powerful technique that overcomes SLD's susceptibility in dealing with recursion and redundant sub-computations. In a tabled evaluation, there are several points where we may have to choose between different tabling operations. The decision on which operation to perform is determined by the scheduling algorithm. The two most successful tabling scheduling algorithms are local scheduling and batched scheduling. In previous work, we have developed a framework, on top of the Yap Prolog system, that supports the combination of different linear tabling strategies for local scheduling. In this work, we propose the extension of our framework to support batched scheduling. In particular, we are interested in the two most successful linear tabling strategies, the DRA and DRE strategies. To the best of our knowledge, no other Prolog system supports both strategies simultaneously for batched scheduling. Our experimental results show that the combination of the DRA and DRE strategies can effectively reduce the execution time for batched evaluation.

Abstract
Deduplication is now widely accepted as an efficient technique for reducing storage costs at the expense of some processing overhead, being increasingly sought in primary storage systems [7, 8] and cloud computing infrastructures holding Virtual Machine (VM) volumes [2, 1, 5]. Besides a large number of duplicates that can be found across static VM images [3], dynamic general purpose data from VM volumes allows space savings from 58% up to 80% if deduplicated in a cluster-wide fashion [1, 4]. However, some of these volumes persist latency sensitive data which limits the overhead that can be incurred in I/O operations. Therefore, this problem must be addressed by a cluster-wide distributed deduplication system for such primary storage volumes.

Abstract

Abstract
Introduction. The strong dynamic nature of the Web is a well-known reality. Nonetheless, research on Web dynamics is still a minor part of mainstream Web research. This is largely the case in Web link analysis. In this paper we investigate and measure the impact of time in link-based ranking algorithms on a particular subset of the Web, specifically blogs. Method. Using a large collection of blog posts that span more than three years, we compare a traditional link-based ranking algorithm with a time-biased alternative, providing some insights into the evolution of link data over time. We designed two experiments to evaluate the use of temporal features in authority estimation algorithms. In the first experiment we compare time-independent and time-sensitive ranking algorithms with a reference rank based on the total number of visits to each blog. In the second, we use feedback from communication media domain experts to contrast different rankings of Portuguese news Websites. Results. The distribution of citations to a Web document over time contains valuable information. Based on several examples we show that time-independent algorithms are unable to capture the correct popularity of sites with high citation activity. Using a reference rank based on the number of visits to a site, we show that a time-biased approach has a better performance. Conclusions. Although both time-independent and time-aware approaches are based on the same raw data, the experiments indicate that they can be treated as complementary signals for relevance assessment by information retrieval systems. We show that temporal information present in blogs can be used to derive stable time-dependent features, which can be successfully used in the context of Web document ranking.

Abstract
The existence of replicated code in a system makes that system harder to maintain and evolve. To remove replicated code the usual way is to use refactorings. However there are always clones that cannot be removed by refactorings alone. Some are due to lack of composition mechanisms in the underlying programming language. We propose the use of roles to remove such clones since roles provide a finer degree of composition. We sketch four role refactorings to remove code clones and apply them in a case study using the JHotDraw framework. Results show that roles have a positive impact in clone reduction as they were able to remove almost all clones traditional refactorings could not. © 2013 IEEE.

Abstract
Code replication has significant drawbacks in system maintenance. Code replication can have its origins in the composition limitations of the language. Several proposals have tried to overcome these limitations. A popular one is traits. However, traits do not support state or visibility control. Static roles are also a way of composing classes that has the benefits of traits and offers state, visibility control and other advantages as block renaming. We compare both approaches on how they are used to compose classes, and how they can be used to reduce code replication caused by composition limitations. As a case study we will compare how both approaches can reduce code replication by detecting and removing code clones within the JHotDraw framework. Results show that roles are capable of reducing a larger amount of replicated code than traits.