Carla I. M. Bezerra

Quality characteristics and measures for human---computer interaction evaluation in ubiquitous systems

The advent of ubiquitous systems places even more focus on users, since these systems must support their daily activities in such a transparent way that does not disturb them. Thus, much more attention should be provided to human–computer interaction (HCI) and, as a consequence, to its quality. Dealing with quality issues implies first the identification of the quality characteristics that should be achieved and, then, which software measures should be used to evaluate them in a target system. Therefore, this work aims to identify what quality characteristics and measures have been used for the HCI evaluation of ubiquitous systems. In order to achieve our goal, we performed a large literature review, using a systematic mapping study, and we present our results in this paper. We identified 41 pertinent papers that were deeply analyzed to extract quality characteristics and software measures. We found 186 quality characteristics, but since there were divergences on their definitions and duplicated characteristics, an analysis of synonyms by peer review based on the equivalence of definitions was also done. This analysis allowed us to define a final suitable set composed of 27 quality characteristics, where 21 are generic to any system but are particularized for ubiquitous applications and 6 are specific for this domain. We also found 218 citations of measures associated with the characteristics, although the majority of them are simple definitions with no detail about their measurement functions. Our results provide not only an overview of this area to guide researchers in directing their efforts but also it can help practitioners in evaluating ubiquitous systems using these measures.

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.

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.

Evaluating an IoT Application Using Software Measures

Internet of Things (IoT) allows daily objects, with computing and communication capabilities, to connect to the Internet. In this scenario, an application called GREatRoom runs in an IoT environment, which has distributed wireless labels in places and objects, to detect the presence of nearby users, providing services intuitively and efficiently. Considering that IoT systems have quality characteristics of human-computer interaction similar to those of ubiquitous systems, this paper investigates the applicability of software measures from ubiquitous to IoT systems and presents the positive results achieved in this evaluation.

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.

Requirements Engineering and Variability Management in DSPLs Domain Engineering: A Systematic Literature Review

Recently, Software Product Lines (SPLs) have been used successfully for building products families. However, the currently and complex software products demand more adaptive features. Today, many application domains demand capabilities for flexible adaptation and post-deployment reconfiguration. In this context, Dynamic Software Product Lines (DSPLs) represent a way to produce software products able to change their own behavior at runtime due to the changes in the product use environment. DSPLs present some interesting properties such dynamic variability and reconfiguration at runtime. The dynamic variability is represented by the definition of variants and context information. The reconfiguration at runtime is the process that enables the features activation and deactivation in a configuration product. Both properties are closely related to the requirements engineering and variability management, in the domain engineering life-cycle. In this research, we provide a systematic literature review that aims to identify the activities, assets, tools and approaches that are used in requirements engineering and variability management in DSPLs domain engineering. We performed a manual and automatic search, resulting in 581 papers of which 37 were selected. We also provide a discussion about the challenges and solutions of runtime variability mechanisms in the context of DSPLs.

A pattern language for agile software estimation

This paper presents a pattern language for agile software estimation. The proposed language is composed of eight patterns and their relationships, which were identified through an extensive literature research and interviews with several companies that use agile methodologies. The patterns identified can help agile teams to obtain the main estimates needed in the context of agile software projects.