Katia Romero Felizardo

A systematic literature review on the description of software architectures for systems of systems

Software architectures have been recognized as the backbone to the success of any software system. In addition, they are responsible to aggregate quality attributes, such as interoperability, dependability, and maintainability, to these systems. In parallel, currently, a new class of complex software systems has emerged, referred as Systems of Systems (SoS), resulting from a number of operationally and managerially independent software systems working together to fulfill a mission that none system alone could provide. Considering their complexity, the development of SoS has demanded special attention to their software architectures. In this scenario, the description of such architectures, i.e., the way that these architectures are represented/documented, becomes quite important as it can improve communication as well as evaluation and maintenance of these architectures. Despite its relevance, there is still no complete panorama about architectural descriptions of SoS. The main contribution of this paper is to present results of a Systematic Literature Review (SLR) on how SoS software architectures have been described. As main result, there are already important contributions in that direction; however, there is a lack of consensus on how better dealing with these descriptions. We conclude this paper with directions on how a consensus could be achieved and which aspects of the SoS architectural descriptions require further investigation.

A systematic mapping on the use of visual data mining to support the conduct of systematic literature reviews

A systematic literature review (SLR) is a methodology used to find and aggregate all relevant existing evidence about a specific research question of interest. Important decisions need to be made at several points in the review process, relating to search of the literature, selection of relevant primary studies and use of methods of synthesis. Visualization can support tasks that involve large collections of data, such as the studies collected, evaluated and summarized in an SLR. The objective of this paper is to present the results of a systematic mapping study (SM) conducted to collect and evaluate evidence on the use of a specific visualization technique, visual data mining (VDM), to support the SLR process. We reviewed 20 papers and our results indicate a scarcity of research on the use of VDM to help with conducting SLRs in the software engineering domain. However, most of the studies (16 of the 20 studies included in our mapping) have been conducted in the field of medicine and they revealed that the activities of data extraction and data synthesis, related to conducting the review phase of an SLR process, have more VDM support than other activities. In contrast, according to our SM, previous studies using VDM techniques with SLRs have not employed such techniques during the SLR’s planning and reporting phases.

Reference models and reference architectures based on service-oriented architecture: a systematic review

Service-Oriented Architecture (SOA) has received increasing attention by providing low coupling, reuse, productivity, and a better understanding of the business domain. However, there are challenges in creating quality solutions using services. Based on SOA, reference models and reference architectures have been proposed to support the understanding, development, and standardization in the development of service-oriented systems. Considering the relevance of SOA, as well as the lack of a complete panorama about these models and architectures, this paper aims at presenting a detailed view about the establishment and use of these models and architectures. For this, we conducted a systematic review. As main results, we observed a recent increase in the number of work regarding reference models and reference architectures based on SOA, including for different domains. Furthermore, based on the presented view, we identified interesting and important perspectives for future research.

Using systematic mapping to explore software architecture knowledge

Software architectures have played a significant role in determining the success of software systems. In this perspective, a lot of work have been conducted and considerable knowledge in the software architecture area has been accumulated. In another perspective, systematic mapping is a technique that provides an overview of a research area to assess the quantity of evidence existing on a topic of interest. Thus, the main objective of this paper is to introduce systematic mapping in order to explore, understand, organize and summarize software architecture knowledge, aiming at contributing to software architecture area. A simple example of use of this technique is presented and results point out to its viability also in the software architecture research area.

A visual analysis approach to update systematic reviews

Context: In order to preserve the value of Systematic Reviews (SRs), they should be frequently updated considering new evidence that has been produced since the completion of the previous version of the reviews. However, the update of an SR is a time consuming, manual task. Thus, many SRs have not been updated as they should be and, therefore, they are currently outdated. Objective: The main contribution of this paper is to support the update of SRs. Method: We propose USR-VTM, an approach based on Visual Text Mining (VTM) techniques, to support selection of new evidence in the form of primary studies. We then present a tool, named Revis, which supports our approach. Finally, we evaluate our approach through a comparison of outcomes achieved using USR-VTM versus the traditional (manual) approach. Results: Our results show that USR-VTM increases the number of studies correctly included compared to the traditional approach. Conclusions: USR-VTM effectively supports the update of SRs.

Using Forward Snowballing to update Systematic Reviews in Software Engineering

Background: A Systematic Literature Review (SLR) is a methodology used to aggregate relevant evidence related to one or more research questions. Whenever new evidence is published after the completion of a SLR, this SLR should be updated in order to preserve its value. However, updating SLRs involves significant effort. Objective: The goal of this paper is to investigate the application of forward snowballing to support the update of SLRs. Method: We compare outcomes of an update achieved using the forward snowballing versus a published update using the search-based approach, i.e., searching for studies in electronic databases using a search string. Results: Forward snowballing showed a higher precision and a slightly lower recall. It reduced in more than five times the number of primary studies to filter however missed one relevant study. Conclusions: Due to its high precision, we believe that the use of forward snowballing considerably reduces the effort in updating SLRs in Software Engineering; however the risk of missing relevant papers should not be underrated.

Systematic mapping study on high-level language virtual machines

Background: There is a large body of literature on research in virtual machine for high-level languages, i.e., high-level language virtual machines (HLL VMs). Despite being a well-established research area, there are no studies focusing on characterizing the sorts of research that have been conducted and shedding light on most investigated subjects as well as subjects requiring further research. Objectives: To conduct a systematic mapping study of the literature describing research into HLL VM. Research method: We undertook a systematic mapping study of the literature based upon searching of major electronic databases. Results: 128 papers have been selected and classified by their contribution, employed HLL VM implementation, type and date of publication. Conclusions: The majority of the selected studies concentrate on improvements for boosting performance, introducing better garbage collection capabilities, and adapting HLL VMs or their core components to meet the requirements for embedded platforms. Furthermore, from examining the selected studies we have found that Java virtual machine (JVM) implementations are by far the most employed within academic settings. Among them, Jikes Research Virtual Machine is the most-widely used.

The Use of Visual Text Mining to Support the Study Selection Activity in Systematic Literature Reviews: A Replication Study

Background: Systematic literature reviews (SLRs)are an important component to identify and aggregate research evidence from different empirical studies. One of the activities associated with the SLR process is the selection of primary studies. The process used to select primary studies can be arduous, particularly when the researcher faces large volumes of primary studies. Aim: An experiment was conducted as a pilot test to compare the performance and effectiveness of graduate students in selecting primary studies manually and using visual text mining (VTM) techniques. This paper describes a replication study. Method: The same experimental design and materials of the previous experiment were used in the current experiment. Result: The previous experiment revealed that VTM techniques can speed up the selection of primary studies and increase the number of studies correctly included/excluded (effectiveness). The results of the replication confirmed that studies are more rapidly selected using VTM. We observed that the level of experience in researching has a direct relationship with the effectiveness. Conclusion: VTM techniques have proven valuable in the selection of primary studies.

Developing and evaluating web multimodal interfaces - a case study with usability principles

In this paper we describe an approach to facilitate the design of Web multimodal interfaces aiming at improving the user experience and the user interface usability using speech recognition together with the usual graphical user interfaces. We present a proposal for usability evaluation based on the heuristic evaluation, which considers the multimodal principles identified during a case study. As a result of using the proposed approach in the case study and from literature review, we report our considerations for the design, development and improvement of the Web multimodal interfaces.

Externalising tacit knowledge of the systematic review process

Systematic Reviews (SRs) have recently intensified in Software Engineering. However, there is a lack of work that makes explicit how the process to perform SR is in practice. The goal of this paper is externalising the process that reflects how SRs are currently performed, transforming tacit knowledge into explicit knowledge. We describe the phases and activities that compose the process and the relationship among them, and explore the iterative characteristic of this process, focusing on intra- and inter-phase iterations that are necessary to conduct the process appropriately. To achieve the proposed goal, we devised the process based on practical experience acquired for several years by research groups in Software Engineering, which include graduate students and researchers who have applied SR. The process has been applied in several SRs and seems to be effective in keeping the focus of the review at all phases. Moreover, the externalisation of the process has been useful to help researchers improving the process execution quality. As the process reflects the practice and is explained in details, it can be used as a guide to better understand the SR process and its details. This shall contribute to improve all SR process phases, and hence the quality of SR results.