Compacting XML Structures Using a Dynamic Labeling Scheme

Abstract. Due to the growing popularity of XML as a data exchange and storage format, the need to develop efficient techniques for stor-ing and querying XML documents has emerged. A common approach to achieve this is to use labeling techniques. However, their main prob-lem is that they either do not support updating XML data dynamically or impose huge storage requirements. On the other hand, with the ver-bosity and redundancy problem of XML, which can lead to increased cost for processing XML documents, compaction of XML documents has be-come an increasingly important research issue. In this paper, we propose an approach called CXDLS combining the strengths of both, labeling and compaction techniques. Our approach exploits repetitive consecu-tive subtrees and tags for compacting the structure of XML documents by taking advantage of the ORDPATH labeling scheme. In addition it stores the compacted structure and the data values separately. Using our proposed approach, it is possible to support efficient query and update processing on compacted XML documents and to reduce storage space dramatically. Results of a comprehensive performance study are provided to show the advantages of CXDLS.

Weaving Variability into Domain Metamodels

International audienceDomain-Specific Modeling Languages (DSMLs) describe the concepts of a particular domain and their relationships, in a meta-model. From a given DSML, it is possible to describe a wide range of different models. These models often share a common base and vary on some parts. Current approaches tend to distinguish the variability language from the DSMLs themselves, implying greater learning curve for DSMLs stakeholders and a significant overhead in product line engineering of DSLs. We propose to consider variability concepts as an independent aspect to be woven into the DSML to introduce variability capabilities. In particular we detail how variability is woven and how to perform product line derivation. We validate our approach through the weaving of variability into two very different metamodels: Ecore and SmartAdapter, our aspect-oriented modelling weaver, thus adding exibility in the weaving process itself. These results emphasize how new abilities of the language can be provided by this means

Evaluating the usability of a visual feature modeling notation

International audienceFeature modeling is a popular Software Product Line Engineering (SPLE) technique used to describe variability in a product family. A usable feature modeling tool environment should enable SPLE practitioners to produce good quality models, in particular, models that effectively communicate modeled information. FAMILIAR is a text-based environment for manipulating and composing Feature Models (FMs). In this paper we present extensions we made to FAMILIAR to enhance its usability. The extensions include a visualization of FMs, or more precisely , a feature diagram rendering mechanism that supports the use of a combination of text and graphics to describe FMs, their configurations, and the results of FM analyses. We also present the results of a preliminary evaluation of the environment's usability. The evaluation involves comparing the use of the extended environment with the previous text-based console-driven version. The preliminary experiment provides some evidence that use of the new environment results in increased cognitive effectiveness of novice users and improved quality of new FMs

Evaluating a Textual Feature Modelling Language: Four Industrial Case Studies

Abstract. Feature models are commonly used in software product line engineer-ing as a means to document variability. Since their introduction, feature models have been extended and formalised in various ways. The majority of these ex-tensions are variants of the original tree-based graphical notation. But over time, textual dialects have also been proposed. The textual variability language (TVL) was proposed to combine the advantages of both graphical and textual notations. However, its benefits and limitations have not been empirically evaluated up to now. In this paper, we evaluate TVL with four cases from companies of differ-ent sizes and application domains. The study shows that practitioners can benefit from TVL. The participants appreciated the notation, the advantages of a textual language and considered the learning curve to be gentle. The study also reveals some limitations of the current version of TVL.

THE OBJECT-ORIENTED FUNCTIONAL DATA LANGUAGE

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