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Internet of Things (IoT) e um paradigma que permite compor sistemas a partir de objetos equipados com comportamentos de identificacao, sensoriamento ou atuacao alem de capacidades de processamento, os quais podem se comunicar e cooperar para alcancar objetivos. Assim como toda mudanca de paradigma, IoT faz emergir desafios relacionados a diversas areas de pesquisa, incluindo a Engenharia de Software nas diferentes fases de desenvolvimento. Considerando fases iniciais de projeto, este trabalho propoe a abordagem ScenarIoT visando apoiar a especificacao de cenarios no desenvolvimento de sistemas de software baseados em IoT. Esta abordagem e fundamentada em Arranjos de Interacao, os quais representam fluxos recorrentes de interacao entre elementos abstratos do dominio IoT. Estes arranjos puderam ser desenhados aplicando-se uma abordagem baseada em evidencia, ou seja, considerando os resultados obtidos por meio de uma revisao estruturada da literatura conduzida com o objetivo de identificar, analisar e interpretar os conceitos e propriedades do dominio IoT. A abordagem ScenarIoT foi aplicada em dois projetos de turmas de graduacao com o objetivo de observar a sua utilidade. Os resultados dos estudos mostraram que a abordagem e util considerando o contexto onde foi aplicada.

Background: Technical debt (TD) has been an important focus of attention in recent years by the scientific community and the software industry. TD is a concept for expressing the lack of internal software quality that directly affects its capacity to evolve. Some studies have focused on the TD industry perspective. Aims: To characterize how the software industry professionals in Uruguay understand, perceive, and adopt technical debt management (TDM) activities. Method: To replicate a Brazilian survey with the Uruguayan software industry and compare their findings. Results: From 259 respondents, many indicated any awareness of the TD concept due to the faced difficult to realize how to associate such a concept with actual software issues. Therefore, it is possible to observe a considerable variability in the importance of TDM among the respondents. However, a small part of the respondents declares to carry out TDM activities in their organizations. A list of software technologies declared as used by practitioners was produced and can be useful to support TDM activities. Conclusions: The TD concept and its management are not common yet in Uruguay. There are indications of TD unawareness and difficulties in the conduction of some TDM activities considered as very important by the practitioners. There is a need for more effort aiming to disseminate the TD knowledge and to provide software technologies to support the adoption of TDM in Uruguay. It is likely other software engineering communities face similar issues. Therefore, further investigations in these communities can be of interest.

Research synthesis represents an essential element of the knowledge accumulation and application process, which is indispensable to any scientific field such as software engineering. In the case of the software engineering domain, the evidence is produced in both quantitative and qualitative forms, which challenges their combined analysis. Research synthesis methods, in general, follow similar processes but differ in being integrative or interpretative. This chapter intends to introduce the reader to the research synthesis theme. It discusses the most frequently used synthesis methods in software engineering. They range from the ones geared toward interpretative synthesis approaches—for instance, thematic synthesis and meta-ethnography—to those more focused on integrative approaches—e.g., case survey, qualitative comparative analysis, and statistical meta-analysis. Besides brief descriptions of these methods, the structured synthesis method is presented in detail, together with a worked example concerning the synthesis of four primary studies regarding the usage-based reading inspection technique.

Empirical methods like experimentation have become a powerful means to drive the field of software engineering by creating scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision-making and learning. Today empirical methods are fully applied in software engineering. However, they have developed in several iterations since the 1960s. In this chapter we tell the history of empirical software engineering and present the evolution of empirical methods in software engineering in five iterations, i.e., (1) mid-1960s to mid-1970s, (2) mid-1970s to mid-1980s, (3) mid-1980s to end of the 1990s, (4) the 2000s, and (5) the 2010s. We present the five iterations of the development of empirical software engineering mainly from a methodological perspective and additionally take key papers, venues, and books, which are covered in chronological order in a separate section on recommended further readings, into account. We complement our presentation of the evolution of empirical software engineering by presenting the current situation and an outlook in Sect. 4 and the available books on empirical software engineering. Furthermore, based on the chapters covered in this book we discuss trends on contemporary empirical methods in software engineering related to the plurality of research methods, human factors, data collection and processing, aggregation and synthesis of evidence, and impact of software engineering research.

The software startups are a particular scenario where Technical Debt (TD) may occur in an intentional or unintentional way. However, the current knowledge about the perception and management of TD are mainly related to mature software organizations. This chapter contextualizes the startups’ characteristics that can lead to TD incurrence, the concepts related to TD and its management, and presents the results of a survey with Uruguayan software startups. The survey’s primary goal was to understand how software startups perceive and manage TD in their projects. The results refer to the level of understanding of the startup’s practitioners concerning TD concept, the adopted Technical Debt Management (TDM) activities, and the strategies and technologies used in their projects to support such activities. The findings show that startups seem to invest time and effort in TDM activities being TD prevention, one of the most conducted activities. Besides that, it was observed that the participant’s experience and the size of the organization seem to be also related to the perception and management of TD.

National audience; The user interfaces (UIs) promote the interaction with the software system to achieve the users' goals. In this way different types of interaction are provided, such as direct manipulation, web UI or tangible interaction. These interfaces have evolved, including artificial intelligence and adaptation mechanisms to answer the evolution of the technological areas. From this evolution emerged the intelligent user interfaces (IUIs) that aim to be more effective, efficient, and natural. Considering the importance of IUI nowadays, we have performed a systematic literature review (SLR) to investigate the design trends of IUIs in the context of contemporary software systems (CSS), such as software systems based on internet of things (IoT) or dedicated to smart cities. Preliminary results show which models and technologies are most used to develop IUIs, and which application domain is mostly represented.; Les interfaces utilisateur (IU) visent à favoriser l'interaction avec le système pour permettre aux utilisateurs d'atteindre leurs buts. Ainsi, différents types d'interaction sont possibles, tels que la manipulation directe, les interfaces web ou l'interaction tangible. Ces interfaces ont évolué au fil du temps, tout en intégrant des mécanismes issus de l'intelligence artificielle, tels des mécanismes d'adaptation, pour répondre à l'évolution des domaines technologiques. De cette évolution ont emergé les interfaces utilisateur intelligentes (IUI) qui visent à être efficaces et naturelles. Ainsi nous sommes en train de mener une revue systématique de la littérature pour étudier les tendances de conception des IUI dans le contexte des systèmes logiciels contemporains (SLC), tels que les systèmes basés sur l'internet des objets ou dédiés aux villes intelligentes. Les résultats préliminaires montrent quels sont les modèles et technologies les plus utilisés pour développer des IUIs, ainsi que le domaine d'application le plus représenté.

Chatbots fazem uso do processamento de linguagem natural para estabelecer dialogos com pessoas como se fossem humanos, podendo ser usados como canais que facilitam a comunicacao entre humanos e entidades (empresas, projetos sociais, projetos de pesquisa, hospitais, escolas/universidades, etc.). O PipaBot e um chatbot que foi construido para facilitar a comunicacao entre as esperadas duas mil participantes (maes) e pesquisadores (as) do Projeto Infância e Poluentes Ambientais (PIPA-UFRJ). O PipaBot foi desenvolvido de forma incremental e iterativa e usou o framework Botpress. Ele esta disponivel em duas versoes: no Messenger do Facebook e no website do PIPA-UFRJ. As acoes disponibilizadas pelo PipaBot sao: i) cadastro de uma participante do projeto; ii) obtencao de informacoes sobre o projeto, consultas medicas, resultados de exames medicos, entre outros. O PipaBot foi avaliado segundo o modelo de aceitacao da tecnologia (TAM - Tecnological Acceptance Model) com 13 participantes e os resultados iniciais forneceram indicios de satisfacao dos usuarios sobre o ponto de vista de sua aceitacao.

Technical debt (TD) is a still incipient subject adopted by software practitioners, despite being an increasing interest topic among researchers. This work aimed to produce a summary of the central concepts related to TD, including the software technologies currently available to manage it. A survey with practitioners from Brazilian software organizations (BSOs) was conducted to assess the knowledge level on TD, including the technologies adopted by the software practitioners in the industry. Following this study, a quasi-systematic literature review was undertaken to gather specific technologies to manage the TD. We observed indications that the general knowledge of the BSOs′ software practitioners regarding TD is low, and only a minority of the participants mentioned strategies to manage TD. Evidence briefings (EBs) synthesized the results from the studies. EBs are one-page documents intended to improve the knowledge transfer between the researchers and the practitioners from the industry. Besides, the characterization of TD and its management technologies in Brazilian Software Organizations, this dissertation also contributes to the distribution of a research package to aid in the studies replication process, containing the survey plan and its instruments. Moreover, the EBs can be used by the software practitioners, as an instrument to aid the inclusion of TD management practices in BSOs. This dissertation produced a paper discussing the survey research at CIbSE 2018, which received the best paper award at the ESELAW track, and an invitation to extend it on a JSERD paper, which is being under development. Another paper, with a general overview of the research conducted at the dissertation, was presented at the SBQS 2018.

Context: Software inspection is a static and formal verification technique that aims to detect defects in the earlier stage of software development. Both academic and industrial professionals have widely applied software inspections since they reduce by up to 60% the number of defects in artifacts produced in the software development cycle, being a way to assure the quality. Goal: This paper proposes the SCENARIOTCHECK technique, a new approach to supporting the quality of IoT scenarios-based description by performing inspections. Method: We carried out two experimental studies to evaluate the feasibility and observe the use of the technique. Results: In both studies, the technique presented adequate performance and acceptance by the participants when compared with an ad-hoc technique. Besides, the subjects' feedback supported us on improving the SCENARIOTCHECK. Conclusions: SCENARIOTCHECK is a feasible inspection technique that supports the identification of defects in IoT scenarios artifacts.

The evidence-based software engineering approach advocates the use of evidence from empirical studies to support the decisions on the adoption of software technologies by practitioners in the software industry. To this end, many guidelines have been proposed to contribute to the execution and repeatability of literature reviews, and to the confidence of their results, especially regarding systematic literature reviews (SLR). To investigate similarities and differences, and to characterize the challenges and pitfalls of the planning and generated results of SLR research protocols dealing with the same research question and performed by similar teams of novice researchers in the context of the software engineering field. We qualitatively compared (using Jaccard and Kappa coefficients) and evaluated (using DARE) same goal SLR research protocols and outcomes undertaken by similar research teams. Seven similar SLR protocols regarding quality attributes for use cases executed in 2010 and 2012 enabled us to observe unexpected differences in their planning and execution. Even when the participants reached some agreement in the planning, the outcomes were different. The research protocols and reports allowed us to observe six challenges contributing to the divergences in the results: researchers' inexperience in the topic, researchers' inexperience in the method, lack of clearness and completeness of the papers, lack of a common terminology regarding the problem domain, lack of research verification procedures, and lack of commitment to the SLR. According to our findings, it is not possible to rely on results of SLRs performed by novices. Also, similarities at a starting or intermediate step during different SLR executions may not directly translate to the next steps, since non-explicit information might entail differences in the outcomes, hampering the repeatability and confidence of the SLR process and results. Although we do have expectations that the presence and follow-up of a senior researcher can contribute to increasing SLRs' repeatability, this conclusion can only be drawn upon the existence of additional studies on this topic. Yet, systematic planning, transparency of decisions and verification procedures are key factors to guarantee the reliability of SLRs.

Context-Aware Software Systems (CASS) use environmental information to provide better service to the systems’ actors to fulfill their goals. Testing of ubiquitous software systems can be challenging since it is unlikely that, while designing the test cases, the tester can identify all possible context variations. A quasi -Systematic Literature Review has been undertaken to characterize the methods usually used for testing CASS. The analysis and generation of knowledge in this work rely on classifying the extracted information. Established taxonomies of software testing and context-aware were used to characterize and interpret the findings. The results show that, although it is possible to observe the utilization of some software testing methods, few empirical studies are evaluating such methods when testing CASS. The selected technical literature conveys a lack of consensus on the understanding of context and CASS, and on the meaning of software testing. Furthermore, context variation in CASS has only been partially addressed by the identified approaches. They either rely on simulating context or in fixing the values of context variables during testing. We argue that the tests of context-aware software systems need to deal with the diversity of context instead of mitigating their effects.

Contemporary Software Systems, such as Ubiquitous Systems, Context-Aware Systems, and Internet of Things (IoT) led to a new technological revolution, with characteristics like autonomy, seamless connectivity and interaction. The engineering of such systems is challenging due to their novelty and a possible lack of software technologies to deal with them. Together with quality assurance for the system, the artifacts for the development itself should also be assured. One way to ensure the quality of the produced artifacts is software inspections. This paper introduces the SCENARIOTCHECK, a checklist-based inspection technique for IoT-based scenarios. A feasibility study indicated its cost-efficiency and effectiveness in detecting defects in the IoT-based scenario.

International audience; Contemporary software systems, such as the Internet of Things (IoT), Industry 4.0, and Smart Cities represent a technology changing that offer challenges for their construction since they are calling into question our traditional form of developing software. They are a promising paradigm for the integration of devices and communications technologies. It is leading to a shift in the classical monolithic view of development where stakeholders used to receive a software product at the end (that we have been doing for decades), to software systems incrementally materialized through physical objects interconnected by networks and with embedded software to support daily activities. Therefore, we need to revisit the classical way of developing software and start to consider the particularities required by these new sorts of applications. Since such software systems involve different concerns, this paper presents the results of an investigation towards defining a framework to support the software systems engineering of IoT applications. To support its representation, we evolved the Zachman’s Framework as an alternative to the organization of the framework architecture. The filling of such a framework is supported by a) 14 significant concerns of IoT applications, recovered from the technical literature, practitioner’s workshops and a Government Report; b) seven structured facets emerged from IoT data analysis, that together represent the engineering challenges to be faced both by researchers and practitioners towards the advancement of IoT in practice.

Internet of Things is a technology paradigm that enables the interaction of devices and communications technologies with embedded software, integrating different areas and multidisciplinarity. It is built from smart objects, that relies on things interaction and information exchange, which can lead to development challenges. This paper presents research towards the definition of a framework to support the engineering of IoT software systems. From a literature review, we introduce six IoT facets representing knowledge areas and topics to consider while engineering IoT software systems. The proposed framework uses them to have a multifaceted perspective of the IoT problem domain. Three steps going from Project Characterization to a strategy to support decision-making for development compose the framework. The article presents a real case scenario of a shrimp farm used to illustrate its use.

As infecções parasitárias afetam mais de um bilhão de pessoas em 149 países em desenvolvimento e, para diagnosticá-las, utiliza-se um processo lento, capaz de afetar negativamente a saúde dos profissionais envolvidos. Visando este problema, propõe-se uma infraestrutura de baixo custo com o objetivo de transformar microscópios ópticos comuns em digitais. A solução apresentada possibilita a visualização da imagem em um monitor comum, bem como a captura dessas imagens e de informações relevantes. Além disso, as imagens podem ser compartilhadas através de plataformas IoT.Este procedimento torna o processo de observação de amostras mais fácil e confortável, evitando problemas de saúde relacionados ao uso constante do microscópio convencional.

Maintenance is often the most expensive and time-consuming of all software system lifecycle phases. Technical Debt (TD) refers to technical decisions on shortcuts and workarounds taken during the software development. It affects the internal quality of software. Therefore, software maintenance can be difficult when the TD is not perceived or managed in the projects. Despite the increasing attention of practitioners and researchers, TD studies indicate its management (TDM) is still incipient. Particularly in Brazilian Software Organizations (BSOs), there is still a lack of information on how practitioners perceive and manage the TD in software projects. This paper reports the results of two studies aiming to investigate the current knowledge level of practitioners from BSOs regarding TD and TDM, and to produce a summary of the available technologies to manage TD. To achieve these objectives, we surveyed practitioners from BSOs and undertook a quasi-Systematic Literature Review (qSLR) to gather specific TDM technologies. The survey results indicated that the general BSOs practitioners' knowledge regarding TD and TDM is still low. Few participants from the survey reported managing TD. The qSLR results provide evidence-based information about a set of TDM technologies, synthesized in evidence briefings to facilitate their use by software practitioners in the industry. Moreover, this paper offers links to a research package to aid in the replication process and support future investigations.

Background: Software product quality assurance affects the acceptance of releases. The one dimensional observational perspective of current software product quality (SPQ) models constrains their use in continuous software engineering environments. Aims: To investigate multidimensional relationships between software product characteristics and build an evidence-based infrastructure to observe SPQ continuously. Method: To mine and manipulate datasets regarding software development and use. Next, to perform multidimensional analytical SPQ interpretations to observe quality. Results: There is empirical evidence on the multidimensionality linkage of quality characteristics throughout the software life cycle. Conclusions: The one-dimensional quality perspective is not enough to observe the SPQ in continuous environments. Alternative mathematical abstractions should be investigated.

Software testing is an important activity in the software development life cycle. Several previous studies reported the results of surveys on software testing practices among practitioners from different countries. In this paper, we analyze these surveys aiming to get their main questions, and replicate a survey with practitioners from Brazil and Uruguay, two emerging South American software development scenarios. This survey was previously conducted in Manaus/Brazil in 2006 and Buenos Aires/Argentina in 2013. The replication’s scope includes three regions (Northern Brazil, Southern Brazil, and Uruguay). A total of 150 software testing practitioners responded to the survey. Its results are compared with the previous executions and other software testing surveys identified in the technical literature, strengthening previous findings. The Brazilian and Uruguayan participants indicate that: (1) documentation of test artifacts (plan, cases, procedures, results) are useful and important for software testing practitioners; (2) system and regression testing are the two test types deemed most useful and important; (3) tools for monitoring and management of test process tasks and bug reports are considered useful and important; (4) it is usual for software companies to have a definition of a testing process and to have a dedicated testing team; (5) there is a lack of measurement of test tasks and coverage in the industry; and (6) tools to support automation of test case generation and execution or code coverage are still poorly used in their organizations.

As a community work, scientific contributions are usually built incrementally, involving some transformation, expansion or refutation of existing conceptual and propositional networks. As the body of knowledge increases, scientists concentrate more effort on ensuring that new hypotheses and observations are needed and consistent with previous findings. In this paper, we will characterize Knowledge Engineering as an important groundwork for structuring scientific knowledge. We argue that knowledge-based computational infrastructures can support researchers in organizing and making explicit the main aspects needed to make inferences or extract conclusions from an existing body of knowledge. This view is also comparatively built, contrasting it with alternatives for manipulating scientific knowledge, namely data-intensive approaches and the computational discovery of scientific knowledge. The current state of the art is presented with 22 knowledge representations and computational infrastructure implementations, with their main relevant properties analyzed and compared. Based on this review and on the theoretical foundations of Knowledge Engineering, a high level step-by-step approach for specifying and constructing scientific computational environments is described. The paper concludes by indicating paths for further development of the view initiated here, especially related to the technical specificities that originates from applying Knowledge Engineering to scientific knowledge.

Part 3: Mining OSS Data; International audience; Software release planning is crucial to software projects that adopt incremental development. Open source projects depend on their globally distributed maintainers’ communities who share project information, usually described in the software project repository as issues, to plan the contents and timing of the next releases. This paper introduces an approach based on software issues to support decision-making regarding open source software development activities such as release planning and retrospectives. It uses the PageRank algorithm to suggest an importance ranking of the software issues based on the issues dependencies topology. When based on a highly connected topology, project leaders can use this rank as an input to planning activities. The observation of two open source projects indicates the feasibility of our approach.

Security and performance are critical nonfunctional requirements for software systems. Thus, it is crucial to include verification activities during software development to identify defects related to such requirements, avoiding their occurrence after release. Software verification, including testing and reviews, encompasses a set of activities that have a purpose of analyzing the software searching for defects. Security and performance verification are activities that look at defects related to these specific quality attributes. Few empirical studies have been focused on how is the state of the practice in security and performance verification. This paper presents the results of a case study performed in the context of Brazilian organizations aiming to characterize security and performance verification practices. Additionally, it provides a set of conjectures indicating recommendations to improve security and performance verification activities.

Simulation-based studies (SBS) have become an interesting investigation approach for Software Engineering (SE). However, the reports on experiments with dynamic simulation models found in the technical literature lack relevant information, hampering the full understanding of the procedures and results reported, as well as their replicability. Apart from the limitations on the length in conferences and journal papers, some of the relevant information seems to be missing due to methodological issues not considered when conducting such studies. This is the case of missing research questions and goals, lack of evidence regarding the dynamic simulation model validity, poorly designed simulation experiments, amongst others. Based on findings from a previous quasi-systematic literature review, we propose a set of reporting guidelines for SBS with dynamic models in the context of SE aiming at providing guidance on which information the report should contain. Furthermore, these guidelines were evolved to support SBS planning by identifying potential threats to simulation study validity and in making recommendations to avoid them, through qualitative analysis and external evaluation. Finally, we conducted different evaluations regarding both the reporting and planning guidelines, apart from using them to support the planning of a SBS as regards software evolution. A set of 33 reporting and planning guidelines for different stages of the simulation lifecycle and focused on the experimentation with dynamic simulation models have been put together. The first assessments point to a comprehensive set of guidelines, supporting a comprehensive preparation and review of the plans and reports from the studies, apart from the planning of a SBS focused on software evolution, potentially reducing the threats to the experimentation with the validity of dynamic simulation models. The 33 guidelines cannot be understood as separate groups for reporting and planning as they overlap in many aspects. The main goal is to use the guidelines to support the planning of a simulation-based study with dynamic models so that experimenters may identify potential threats to validity and produce relevant information for a complete simulation experiment report in advance. Despite their initial contribution to increase the validity of SBS, the reporting and planning of simulation-based experiments with dynamic models still has to be discussed and improved in SE. Therefore, additional assessments of this set of guidelines are needed to strengthen the confidence in their completeness and usefulness.

Context Software architecture degrades when changes violating the design-time architectural intents are imposed on the software throughout its life cycle. Such phenomenon is called architecture erosion. When changes are not controlled, erosion makes maintenance harder and negatively affects software evolution. Objective To study the effects of architecture erosion on a large software project and determine whether search-based module clustering might reduce the conceptual distance between the current architecture and the design-time one. Method To run an exploratory study with Apache Ant. First, we characterize Ant’s evolution in terms of size, change dispersion, cohesion, and coupling metrics, highlighting the potential introduction of architecture and code-level problems that might affect the cost of changing the system. Then, we reorganize the distribution of Ant’s classes using a heuristic search approach, intending to re-emerge its design-time architecture. Results In characterizing the system, we observed that its original, simple design was lost due to maintenance and the addition of new features. In optimizing its architecture, we found that current models used to drive search-based software module clustering produce complex designs, which maximize the characteristics driving optimization while producing class distributions that would hardly be acceptable to developers maintaining Ant. Conclusion The structural perspective promoted by the coupling and cohesion metrics precludes observing the adequate software module clustering from the perspective of software engineers when considering a large open source system. Our analysis adds evidence to the criticism of the dogma of driving design towards high cohesion and low coupling, at the same time observing the need for better models to drive design decisions. Apart from that, we see SBSE as a learning tool, allowing researchers to test Software Engineering models in extreme situations that would not be easily found in software projects.

The development of innovative software usually happens in an environment of high uncertainty conditions regarding the problem, the solution, and business issues. Thus, the software needs to be delivered fast and iteratively to the intended customers, which can quickly experiment the ideas developed for the product and give adequate feedback regarding the new features. This development configuration can lead software innovation Startups to avoid activities regarding the creation and updating of documentation and models about the software ideas and features, which raise the risk of losing software knowledge that can support successive software development iterations. Aiming at contributing to supporting software knowledge registering, we conducted an exploratory study to characterize knowledge registration practices used in innovative software projects to make clear software ideas and features. Moreover, we want to observe what influence practitioners when making decisions on using one or another registration practice. The data collected from six experts from six different software innovation Startups through semi-structured interviews and a questionnaire supported the identification of registration practices and factors influencing the decision making on using such practices. The results provide an indication in the context of software innovation Startups that can contribute to future research and proposals to support the engineering of innovative software.

Background: In the era of digitalization, context awareness has become more important to allow software systems adaptation. Therefore, the quality assurance of such systems must consider the variation of context. However, there is a lack of software quality technologies doing so, which can increase the risk of failure of these systems. Objective/Aim: To evidence recent advances regarding the testing of context-aware software systems (CASS), focusing on the abstraction that context should freely vary during test execution as it does in production environments. Method: Based on knowledge acquired with quasi-Systematic Literature Reviews, we evaluate current testing approaches and discuss benefits and limitations of applying the observation above about CASS.Results: It was not possible to observe any software testing technology supporting the unconstrained variation of context during testing a CASS. The practitioners, meanwhile, can use three main evidence-based strategies to test CASS: to assure functional correctness before turning to testing context-aware requirements; to design test cases to target context variables and to take advantage of automatic testing tools as much as possible.Conclusions: To allow context to vary during testing freely, seems plausible. It provides a new frame of thought to enable the design of novel technologies to improve our capacity of testing CASS.

Several models of software testing effort estimation take into account intrinsic characteristics for the whole software development, presenting no evidence of how they effectively affect the test effort. Also, most of such estimation models only estimate the effort regarding the execution of tests. However, in software testing projects the activity usually requiring more effort is the test design & implementation one. Better precision in the identification of the effort factors influencing these activities can result in estimates with a higher degree of accuracy. Therefore, this paper presents a study on the factors affecting the effort in performing test design & implementation of large-scale software projects in a Brazilian government company. The study was carried out through observing the factors influencing the effort in two Web Services testing projects. The identified factors were made explicit through a clear description procedure, which took into account the tasks and artifacts comprising the duties regarding test design & implementation activity based on IEEE 29119 standard. It supported the identification and classification of 24 effort factors concerned with a Web Services test design & implementation process into five different categories.

A qualidade de um produto de software deve ser vista de forma ampla, considerando-se quatro dimensões importantes: Engenharia de Software, Serviço, Qualidade do Produto e Organizacional. Apesar de existirem normas e modelos que tratem elementos destas dimensões, não há nenhum modelo que avalie produtos de software considerando estas quatro dimensões de uma forma ampla e holística, levando as organizações a lançarem mão de diferentes modelos para garantirem a avaliação de sua diversidade procedimental e organizacional. Este artigo apresenta o modelo QPS, um modelo para avaliação da qualidade de produtos de software, e os primeiros resultados de sua implementação e avaliação em organizações brasileiras.

ContextCurrent software systems have increasingly implemented context-aware adaptations to handle the diversity of conditions of their surrounding environment. Therefore, people are becoming used to a variety of context-aware software systems (CASS). This context-awareness brings challenges to the software construction and testing because the context is unpredictable and may change at any time. Therefore, software engineers need to consider the dynamic context changes while testing CASS. Different test case design techniques (TCDT) have been proposed to support the testing of CASS. However, to the best of our knowledge, there is no analysis of these proposals on the advantages, limitations and their effective support to context variation during testing. ObjectiveTo gather empirical evidence on TCDT concerned with CASS by identifying, evaluating and synthesizing knowledge available in the literature. MethodTo undertake a secondary study (quasi-Systematic Literature Review) on TCDT for CASS regarding their assessed quality characteristics, used coverage criteria, test type, and test technique. ResultsFrom 833 primary studies published between 2004 and 2014, just 17 studies regard the design of test cases for CASS. Most of them focus on functional suitability. Furthermore, some of them take into account the changes in the context by providing specific test cases for each context configuration (static perspective) during the test execution. These 17 studies revealed five challenges affecting the design of test cases and 20 challenges regarding the testing of CASS. Besides, seven TCDT are not empirically evaluated. ConclusionA few TCDT partially support the testing of CASS. However, it has not been observed evidence on any TCDT supporting the truly context-aware testing, which that can adapt the expected output based on the context variation (dynamic perspective) during the test execution. It is an open issue deserving greater attention from researchers to increase the testing coverage and ensure users confidence in CASS.

Context: Surveys constitute an valuable tool to capture a large-scale snapshot of the state of the practice. Apparently trivial to adopt, surveys hide, however, several pitfalls that might hinder rendering the result valid and, thus, useful. Goal: We aim at providing an overview of main pitfalls in software engineering surveys and report on practical ways to deal with them. Method: We build on the experiences we collected in conducting many studies and distill the main lessons learnt. Results: The eight lessons learnt we report cover different aspects of the survey process ranging from the design of initial research objectives to the design of a questionnaire. Conclusions: Our hope is that by sharing our lessons learnt, combined with a disciplined application of the general survey theory, we contribute to improving the quality of the research results achievable by employing software engineering surveys., Final CR version

The relevance of Requirements Engineering (RE) research to practitioners is a prerequisite for problem-driven research in the area and key for a long-term dissemination of research results to everyday practice. To better understand how industry practitioners perceive the practical relevance of RE research, we have initiated the RE-Pract project, an international collaboration conducting an empirical study. This project opts for a replication of previous work done in two different domains and relies on survey research. To this end, we have designed a survey to be sent to several hundred industry practitioners at various companies around the world and ask them to rate their perceived practical relevance of the research described in a sample of 418 RE papers published between 2010 and 2015 at the RE, ICSE, FSE, ESEC/FSE, ESEM and REFSQ conferences. In this paper, we summarise our research protocol and present the current status of our study and the planned future steps., Accepted for the 25th International Requirements Engineering Conference, 2017

International audience; Context-awareness feature has been widely employed in the last years due to their usefulness to enhance systems functional reliability and user experience. Different software and hardware technologies can be integrated and used to capture context information, without user intervention. However, the heterogeneity of technology makes interoperability a great development challenge. Moreover, its evaluation for the context-aware system is also not trivial. Considering the relevance of the topic, we performed a characterization research (secondary study) aiming at revealing evidence on how interoperability has been addressed in context-aware software systems (CASS). Despite the observed conceptual divergence on interoperability, we present a set of evidence-based characteristics that can support decision-making and evaluation of interoperability on such systems. This work also introduces some research challenges aiming at to improve what we know about interoperability in CASS.

Software Product Lines are usually specified using feature models. A hierarchically arranged set of features with different relationships among them represents a feature model. However, there is a lack of techniques to support the detection of semantic defects in feature models. In this context, it was recently developed FMCheck, a checklist-based inspection technique to support the detection of defects in feature models. The results of a first study conducted by FMCheck's developers indicated its feasibility (more effective) when compared to ad-hoc techniques. This paper reports the replication accomplished by an independent research group following a different experimental design but using the same artifacts. The obtained results strengthened the previous findings, indicating that FMCheck is more effective than ad-hoc inspections. However, additional replications should be performed with different experimental designs to understand better the influence of the artifacts inspected over such findings.

The Internet of Things (IoT) is a new technological paradigm that brings together the physical and virtual worlds to provide software systems everywhere through daily life objects. The IoT can transform how we interact with the environment surrounding us, leading to a significant multidisciplinary technological shift. However, since it is a new field of research and development, there is a lack of consensus and understanding of its concepts and features, as we observed when engineering some software systems in the field. Therefore, we performed investigations to characterize IoT regarding its definition, characteristics, and applications, organizing the area and revealing its challenges and research opportunities. A structured literature review of secondary studies supported the answering of three research questions: What is “Internet of Things”? Which characteristics can define an IoT domain? Which are the areas of IoT application? The structured literature review leads to 15 subsequent studies from which we recovered 34 definitions - discussed in the light of the technical evolution - 29 characteristics and several IoT application areas. Furthermore, the results include an IoT characterization based on identification, sensing, and actuation capabilities, besides a discussion of the relation between IoT and Cyber-Physical Systems (CPS), regarding other research areas and terms often associated with IoT aiming at to bring clarification to the field. In this work, we offer an essential overview of the IoT state-of-the-art and a characterization, presenting issues that should be addressed to contribute to its strengthening and establishment.

Context-awareness is the ability of a system to gather information from its context and adapt its behaviors. This feature makes the testing of Context-aware software systems more challenging. Based on this assumption, this research proposes an approach to design functional test cases for context-aware software systems, the CATS Design. In its development, ideas from other domains presenting similar issues were tailored to the problem of testing context-aware software systems. This paper presents the design process of CATS Design, and its two empirical evaluation stages: 1) through a proof of concept, and 2) with an observational study involving eight undergraduate students in Uruguay. The results suggest that it is feasible to apply CATS Design for designing test cases for context-aware software systems.

Use cases specifications are artifacts employed in all stages of software development, from the requirements elicitation to implementation. During this process, issues related to ambiguity, redundancy, inconsistency, and incompleteness can affect these specifications. These issues can harm software engineers' understanding and, consequently, affect the software quality. Given this context, this paper describes an empirical study to evaluate two different use cases specifications approaches (textual and graphical-based forms). We compared the approaches by assessing the degree of correctness and the time spent to generate the specifications. In addition, we performed an analysis focusing on evaluating the ease of use and usefulness of each approach. The quantitative results showed that textual form and graphical-based specifications presented similar levels of correctness and the time spent to generate them were also similar. The qualitative results indicated that the subjects had difficulties using both approaches; however, subjects stated that graphic-based specifications were easier and more useful to specify use cases.

Recently, DevOps has emerged as an alternative for software organizations inserted into a dynamic market to handle daily software demands. As claimed, it intends to make the software development and operations teams to work collaboratively. However, it is hard to observe a shared understanding of DevOps, what potentially hinders the discussions in the literature and can confound observations when conducting empirical studies. Therefore, we performed a Multivocal Literature Review aiming at characterizing DevOps in multiple perspectives, including data sources from technical and gray literature. Grounded Theory procedures were used to rigorous analyze the collected data. It allowed us to achieve a grounded definition for DevOps, as well as to identify its recurrent principles, practices, required skills, potential benefits, challenges and what motivates the organizations to adopt it. Finally, we understand the DevOps movement has identified relevant issues in the state-of-the-practice. However, we advocate for the scientific investigations concerning the potential benefits and drawbacks as a consequence of adopting the suggested principles and practices.

Context: The representativeness of samples in Software Engineering primary studies is still a great challenge, mainly when identifying available sources for establishing adequate sampling frames, characterizing subjects and stimulating their participation in (opinion) surveys. The lack of survey guidelines taking into account the specificities of Software Engineering increases the research challenge. Goal: To introduce a conceptual framework for supporting the identification of representative samples for surveys in Software Engineering. Method: Based on knowledge acquired in the technical literature and researchers' experience, to organize a set of guidelines to systematically support sampling in Software Engineering surveys. To perform in vitro empirical studies to observe and evolve the guidelines. Results: An empirically evaluated set of planning activities and tasks with recommendations to support the identification of representative samples for surveys in Software Engineering is available. Conclusion: Surveys have been supporting relevant investigations in Software Engineering in the last decades. This conceptual framework can contribute to strength representativeness of their results. However, some important issues regarding survey research are still open and deserves attention from the empirical Software Engineering community.

Business process models support the business process management, being BPMN a widespread used notation for their modeling. However, the lack of consistent correspondence between the business process textual description and its derived models can jeopardize their quality. The technical literature offers diverse approaches for verifying the quality of such models, but there is a lack of supporting detection of semantic defects in BPMN models. Thus, based on our previous experiences on developing and applying inspection techniques for different Software Engineering artifacts, we developed BPCheck, a checklist-based inspection technique for BPMN models. Results from a first observational study conducted with inexperienced reviewers indicate the viability of BPCheck. Most of the subjects were able to detect more defects than false positives, taking from 10 to 20 min to report a defect. Such findings will drive us to evolve BPCheck aiming at to improve its efficiency and effectiveness.

Context: Ubiquitous Computing (or UbiComp) represents a paradigm in which information processing is thoroughly integrated into everyday objects and activities. From a Software Engineering point of view this development scenario brings new challenges in tailoring or building software processes, impacting current software technologies. However, it has not yet been explicitly shown how to characterize a software project with the perception of ubiquitous computing. Objective: This paper presents a conceptual framework to support the characterization of ubiquitous software projects according to their ubiquity adherence level. It also intends to apply such characterization approach to some projects, aiming at observing their adherence with ubiquitous computing principles. Method: To follow a research strategy based on systematic reviews and surveys to acquire UbiComp knowledge and organize a conceptual framework regarding ubiquitous computing, which can be used to characterize UbiComp software projects. Besides, to demonstrate its application by characterizing some software projects. Results: Ubiquitous computing encapsulates at least 11 different high abstraction level characteristics represented by 123 functional and 45 restrictive factors. Based on this a checklist was organized to allow the characterization of ubiquitous software projects, which has been applied on 26 ubiquitous software projects from four different application domains (ambient intelligence, pervasive healthcare, U-learning, and urban space). No project demonstrated to support more than 65% of the characteristics set. Service omnipresence was observed in all of these projects. However, some characteristics, although identified as necessary in the checklist, were not identified in any of them. Conclusion: There are characteristics that identify a software project as ubiquitous. However, a ubiquitous software project does not necessarily have to implement all of them. The application domain can influence the appearing of UbiComp characteristics in software projects, promoting an increase of their adherence to UbiComp and, thus, for additional software technologies to deal with these ubiquitous requirements.

Context: The results of large-scale studies in software engineering can be significantly impacted by samples' representativeness. Diverse population sources can be used to support sampling for such studies. Goal: To compare two samples, one from the crowdsourcing platform Mechanical Turk and another from the professional social network LinkedIn, in an online experiment for evaluating the relevance of Java code snippets to programming tasks. Method: To compare the samples (subjects' experience, programming habits) and experimental results concerned with three experimental trials. Results: LinkedIn's subjects present significantly higher levels of experience in Java programming and programming in general than Mechanical Turk's subjects. The experimental results revealed a significant difference between samples and suggested that LinkedIn's subjects were more pessimistic than Mechanical Turk's subjects despite a high level consistency in the experimental results. Conclusion: The combined use of sources of sampling can bring benefits to large scale studies in software engineering, especially when heterogeneity is desired in the population. Thus, it can be useful to investigate and characterize alternative sources of sampling for performing large-scale studies in software engineering.

Context: Several empirical studies investigated the benefits and drawbacks of acquiring a Software Reference Architecture (SRA) to construct a family of software systems with similar architectural needs. However, these empirical results have not been synthesized by any study yet. Such synthesized evidence is essential to make informed decisions whether or not to adopt an SRA in an organization. Goal: To aggregate existing empirically- grounded evidence about the benefits and drawbacks of SRAs, aiming at supporting organizations' decision making on their adoption. Method: To identify primary studies in the technical literature through a systematic literature review, and then, use the Structured Synthesis Method (SSM) to aggregate qualitative and quantitative evidence through the use of diagrammatic models. Results: From the five identified primary studies, five SRA benefits have considerably increased their belief value after aggregation: interoperability of software systems, reduced development costs, improved communication among stakeholders, reduced risk, and reduced time- to-market. Also, one drawback of SRAs has increased its belief value: the required learning curve for developers. Conclusions: The aggregated results consolidate knowledge and confidence on some of the studied SRA effects. The commonly reported effects showed a clear increment of their belief and pointed out to broader generalization. The effects that did not show any belief increment are important to detect areas requiring further evidence to reach a higher degree of consolidation. Practitioners might benefit from these results to support the decision of adopting an SRA in practice.