José Maria Monteiro

A mechanism for replicated data consistency in mobile computing environments

Mobile computing allows for the development of new and sophisticated database applications. Such applications require the reading of current and consistent data. In order to improve data availability, increase performance and maximize throughput, data replication is used. However, due to inherent limitations in mobile and other loosely-coupled environments, the concurrency control and replica control mechanisms must be revisited. This paper proposes a new protocol that guarantees the consistency of replicated data in a mobile computing environment, while provide high data availability and ensure an eventual replica convergence towards a strongly consistent state.

R2RML by Assertion: A Semi-automatic Tool for Generating Customised R2RML Mappings

In this paper, we demonstrate the RBA (R2RML By Assertion) tool which automatically generates customized R2RML mappings based on a set of semantic mappings that model the relationship between the relational database schema and a target ontology in RDF. The semantic mappings are specified by a set of correspondence assertions, which are simple to understand.

Challenges for usability testing in ubiquitous systems

Ubiquitous computing expands both the place where the software system is used and the traditional way of interacting with its users. This happens since technologies should be fully integrated in the user daily activities in such way they become indistinguishable. So, in this scenario, new characteristics can emerge like calmness, transparency and context awareness that should be evaluated to assure the ubiquitous system quality. One of the methods used for evaluation of traditional systems is usability testing. Then, in this paper, we identify the main challenges to perform usability testing in ubiquitous systems based on an overview of the literature studies and on our own experience in testing this kind of systems. We also describe our ongoing work where we investigate usability testing to be designed considering context-awareness and to be supported by specific measurements to the ubiquitous computing scenario.

A semi-automatic approach for generating customized R2RML mappings

The Linked Data initiative brought new opportunities for building the next generation of Web applications. However, the full potential of linked data depends on how easy it is to transform data stored in relational databases into RDF triples. Recently, the W3C RDB2RDF Working Group proposed a mapping language, called R2RML, to specify mappings between relational schemas and RDF vocabularies. However, the specification of R2RML mappings is not an easy task. This paper therefore proposes a strategy to simplify the specification of R2RML mappings. The paper first introduces correspondence assertions, which provide a convenient way to manually model mappings between relational schemas and RDF vocabularies. Then, the paper describes a method to automatically generate R2RML mappings from the correspondence assertions.

Measures for Quality Evaluation of Feature Models

In Software Product Lines (SPL), quality evaluation is a critical factor, because an error in a SPL can spread to various end products. However, it is often proved impractical to ensure the quality of all products of a given SPL both for economic reasons and the effort needed due to their large number. In this context, a strategy that can be used is to make quality assessments on the initial phases of the SPL development. This approach avoids having errors that could be propagated to the next SPL phases. So, taking into account the feature model, which is one of the most important artifacts in a SPL since its quality directly affects the quality of the SPL end products, to assure the quality of the feature model is one of the current strategies to assess the quality of a SPL. In this sense, one way to evaluate the feature model is to use measures, which could be associated with the feature model quality characteristics and their quality attributes. This paper presents a measures catalog, which can be used to support the quality evaluation of the feature model. In order to identify these measures, a systematic mapping is conducted and to validate the measures catalog, we perform a peer review with experts in software quality and SPL. Besides that, to evaluate the use of the proposed catalog, we apply the measures in three feature models in the domain of mobile applications. The results show that the proposed measures catalog can be effectively deployed to support the quality evaluation of the feature models.

Exploring quality measures for the evaluation of feature models: a case study

Abstract Evaluating the quality of a feature model is essential to ensure that errors in the early stages do not spread throughout the Software Product Line (SPL). One way to evaluate the feature model is to use measures that could be associated with the feature model quality characteristics and their quality attributes. In this paper, we aim at investigating how measures can be applied to the quality assessment of SPL feature models. We performed an exploratory case study using the COfFEE maintainability measures catalog and the S.P.L.O.T. feature models repository. In order to support this case study, we built a dataset (denoted by MAcchiATO) containing the values of 32 measures from COfFEE for 218 software feature models, extracted from S.P.L.O.T. This research approach allowed us to explore three different data analysis techniques. First, we applied the Spearman’s rank correlation coefficient in order to identify relationships between the measures. This analysis showed that not all 32 measures in COfFEE are necessary to reveal the quality of a feature model and just 15 measures could be used. Next, the 32 measures in COfFEE were grouped by applying the Principal Component Analysis and a set of 9 new grouped measures were defined. Finally, we used the Tolerance Interval technique to define statistical thresholds for these 9 new grouped measures. So, our findings suggest that measures can be effectively used to support the quality evaluation of SPL feature models.

Analyzing the Feature Models Maintainability over their Evolution Process: An Exploratory Study

The feature model is one of the most important artifact of a Software Product Line (SPL). It is built in the early stages of SPL development and describes the main features and relationships. The feature model evolves according to the evolution of the SPL. Thus, it is important to build maintainable feature models. In this scenario, measures have been proven useful in the maintainability evaluation of the feature models. This paper presents an exploratory study on the impact of feature models maintainability over the SPL evolution process. In order to support this analysis, we built a dataset containing a compiled set of 21 maintainability structural measures extracted from 16 feature models and respective versions. Although not conclusive, our findings indicate that the feature models maintainability tends to decrease as it evolves. We also identified the most common changes performed in a feature model during its evolution process.

ReMINDER: An Approach to Modeling Non-Functional Properties in Dynamic Software Product Lines

This paper presents a systematic approach to modeling NFPs in DSPL feature models. In our proposed approach, feature models are annotated with the representation of NFPs, rules for the activation and deactivation of features, constraints between NFPs and features, and context adaptation scenarios. To evaluate the applicability of the proposed approach we carried out an empirical evaluation. The approach yielded good results at identifying NFPs in DSPLs.

DyMMer: a measurement-based tool to support quality evaluation of DSPL feature models

For Dynamic Software Product Lines (DSPLs), evaluating the quality of a feature model is important to ensure that errors in the early stages do not spread throughout the DSPL. Measures extracted from feature models have been proved to be useful in the quality evaluation of such models. However, the process used for computing the values of these quality measures for a large set of feature models can be cumbersome and error prone. To cope with this problem, we present DyMMer, a tool to support the automatic extraction of quality measures from feature models in DSPLs. After that, we can analyse the results and propose improvements for the feature models. Currently, the DyMMer tool is able to collect 40 different quality measures from a DSPL feature model.

On computing temporal functions for a time-dependent networks using trajectory data

Time dependent networks are of key importance to allow computing precise travel times taking into consideration moving objects departure time. However the computation of time functions that are used to annotate time dependent networks are challenging since we must cope with noisy and incomplete traffic data. Recent related works adopt approaches that build Piecewise linear functions, which do not cope with aforementioned problems. In this work, we propose a new method for generating Piecewise linear functions by applying a map-matching technique allied to a curve smoothing approach in order to treat outliers and complete data. We performed experiments using real trajectory data and compared our results with a baseline. Preliminary results show that our approach generates time functions with better approximation than the baseline competitor.