Managing technical debt (TD) is critical to ensure the sustainability of long-term software projects. However, the time and cost involved in technical debt management (TDM) often discourage practitioners from performing this activity consistently. Continuous Integration and Continuous Delivery (CI/CD) pipelines offer an opportunity to support TDM by embedding automated practices directly into the development workflow. Despite this potential, it remains unclear how TDM tools could be integrated into CI/CD pipelines, and we still lack established best practices for this process. To address this problem, the objective of this study is to understand how TDM tools have been used in CI/CD pipelines and also identify potential configuration anti-patterns. To this end, we conducted a large-scale mining software repository (MSR) study on GitHub. In total, we collected around 600,000 Travis CI configuration files and 50,000 supporting scripts, and identified 3,684 pipelines that contain at least one TDM tool. We applied descriptive statistics to analyze the prevalence of tools and anti-patterns, and our findings show that most tools are executed and integrated using an external script; in addition, Absent Feedback is the most common configuration anti-pattern. We believe that researchers and practitioners can use the evidence of this study to further investigate how to improve both the tools that are integrated in CI/CD and the integration practices.

Continuous software engineering (CSE) has become essential for delivering flexible, market-driven software solutions by integrating development, operations, and business strategy under agile principles. CSE practices also lead to the accumulation of technical debt (TD), highlighting the importance of effective technical debt management (TDM). Traceability can play a key role in TDM by linking TD items to past decisions throughout the software life cycle. However, TD traceability remains underexplored in the literature. This study investigates how software practitioners manage the traceability of TD in CSE environments. We conducted eight semi-structured interviews to understand existing processes, tools used, and challenges. Findings reveal that TD traceability is generally ad hoc, lacks standardized practices, and is primarily supported by tools that focus on visualizing TD in backlogs without preserving decision rationale. These results point out to opportunities for future research to enhance TD traceability in CSE.

Abstract Context Technical debt (TD) is a widely studied metaphor that helps to explain how sub-optimal decisions, which usually have short-term benefits, can harm software maintainability over time. Although incurring TD is not intrinsically bad, tracking and managing TD are crucial to avoid its negative effects. Hence, researchers and practitioners have proposed and developed diverse approaches and tools for managing TD. However, we are still lacking specialized tools for technical debt management (TDM), specifically ones that can be easily integrated into existing development workflows. Objective We present and evaluate TagDebt, a bot that can be integrated within GitHub repositories and automatically assign labels to issues (i.e., SATD or non-SATD). TagDebt helps in the identification of TD (i.e., by looking for self-admitted technical debt (SATD)), leading to more efficient TDM. Methods We carried out a Design Science Research study to design and implement TagDebt. For its evaluation, we executed a Technology Acceptance Model (TAM) study through interviews with 16 practitioners, to check the bot’s usefulness, ease of use, and contextual factors that might impact the bot’s usage (such as team size and practitioners’ roles). Results Overall, practitioners found that TagDebt is useful, especially for organizing issues and reducing manual work. Furthermore, they pointed out that the bot is overall easy to use, and its documentation is clear. The analysis also revealed that contextual factors, such as team and codebase size, impact the decision to adopt TagDebt. Finally, several improvements were suggested, such as including features to check and update the source code. Conclusion TagDebt is a proof-of-concept for the development and usage of more specialized tools for TDM. It helps to make TD visible without disrupting existing workflows, which could lead to increased adoption of TDM tools and, consequently, help practitioners avoid the risks of unmanaged TD.

Abstract Alliances of organizations (joint ventures (JV) and merger & acquisition (M&A)) have increasingly been formed to achieve strategic business goals and, as a consequence, large, complex, software-intensive Systems-of-Systems (SoS) have emerged from the complicated interactions among software systems of different organizations/companies. By presenting unique characteristics, in particular, the emergent behavior, evolutionary development, and dynamic reconfiguration, SoS present a big challenge for the elicitation of their requirements, mainly due to ever-changing requirements that continuously emerge at run-time. At the same time, important information contained in the business process level that could serve as a source of these requirements has been neglected. The main contribution of this work is to present a novel source of information, referred to as Processes-of-Business Processes (PoP), to collect requirements of SoS. PoP refer to dynamic, large, and complex business processes formed from the complicated interplay of business processes of organizations that take part in alliances. We also present RE-PoP, a method that systematically extracts SoS requirements from PoP. To evidence the benefits of PoP and RE-PoP, we applied them in a real-world case study involving the Brazilian public health system. By providing a holistic, accurate view of large business processes, PoP together with RE-PoP can assist requirement engineers in the complicated task of identifying tangled requirements of SoS and its constituent systems, as well as providing traceability among them. Information from the business process level should be systematically used to derive SoS requirements, aiming at promoting the SoS sustainability and longevity that are tightly impacted by the business process level.

Managing technical debt (TD) is essential for maintaining long-term software projects. Nonetheless, the time and cost involved in technical debt management (TDM) are often high, which may lead practitioners to omit TDM tasks. The adoption of tools, and particularly the usage of automated solutions, can potentially reduce the time, cost, and effort involved. However, the adoption of tools remains low, indicating the need for further research on TDM automation. To address this problem, this study aims at understanding which TDM activities practitioners are discussing with respect to automation in TDM, what tools they report for automating TDM, and the challenges they face that require automated solutions. To this end, we conducted a mining software repositories (MSR) study on three websites of Stack Exchange (Stack Overflow, Project Management, and Software Engineering) and collected 216 discussions, which were analyzed using both thematic synthesis and descriptive statistics. We found that identification and measurement are the most cited activities. Furthermore, 51 tools were reported as potential alternatives for TDM automation. Finally, a set of nine main challenges were identified and clustered into two main categories: challenges driving TDM automation and challenges related to tool usage. These findings highlight that tools for automating TDM are being discussed and used; however, several significant barriers persist, such as tool errors and poor explainability, hindering the adoption of these tools. Moreover, further research is needed to investigate the automation of other TDM activities such as TD prioritization.

Abstract Context Maintaining software projects over the long term requires controlling the accumulation of technical debt (TD). However, the time and cost associated with technical debt management (TDM) are often high, hindering practitioners from performing TDM tasks. Using tools for TDM has the potential to reduce the effort involved. Despite this, the adoption of such tools remains low, indicating a need for more efficient tool support. Objective This study aims to understand practitioners’ perspectives on tool support for TDM, specifically regarding the selection and use of these tools. Additionally, we identified potential requirements that could be implemented into existing or new TD tools. Method We surveyed practitioners and received 103 answers, from which 89 valid answers were analyzed using thematic synthesis and descriptive statistics. Results Practitioners’ decision-making processes regarding adopting tools are primarily driven by ten main concerns identified from practitioners’ responses (e.g., the load of information provided by tools). Additionally, we elicited 46 requirements and classified them into two main categories (“Information to be provided” and “Tool Usage”). Conclusion Practitioners aim to maintain control over tool execution and outputs. Our study then highlights the necessity of human-centered approaches for TDM automation, i.e., not only tools are essential, but the interaction between tools and practitioners is critical for a more efficient TDM.

Technical debt (TD) refers to non-optimal decisions made in software projects that may lead to short-term benefits, but potentially harm the system’s maintenance in the long-term. Technical debt management (TDM) refers to a set of activities that are performed to handle TD, e.g., identification or measurement of TD. These activities typically entail tasks such as code and architectural analysis, which can be time-consuming if done manually. Thus, substantial research work has focused on automating TDM tasks (e.g., automatic identification of code smells). However, there is a lack of studies that summarize current approaches in TDM automation. This can hinder practitioners in selecting optimal automation strategies to efficiently manage TD. It can also prevent researchers from understanding the research landscape and addressing the research problems that matter the most. The main objective of this study is to provide an overview of the state of the art in TDM automation, analyzing the available tools, their use, and the challenges in automating TDM. We conducted a systematic mapping study (SMS), following the guidelines proposed by Kitchenham et al. From an initial set of 1086 primary studies, 178 were selected to answer three research questions covering different facets of TDM automation. We found 121 automation artifacts that can be used to automate TDM activities. The artifacts were classified in 4 different types (i.e., tools, plugins, scripts, and bots); the inputs/outputs and interfaces were also collected and reported. Finally, a conceptual model is proposed that synthesizes the results and allows to discuss the current state of TDM automation and related challenges. The research community has investigated to a large extent how to perform various TDM activities automatically, considering the number of studies and automation artifacts we identified. Nonetheless, more research is needed towards fully automated TDM, specially concerning the integration of the automation artifacts.

This research to practice full paper observed that graduate subjects (or courses) are commonly offered in graduate programs and can provide specialized knowledge of different topics that are important for the formation of Ph.D. and Master’s students. At the same time, Systematic Literature Review (SLR) has been increasingly adopted in the computing area as a research method to synthesize the state of the art of a given research topic, identify research groups working on that topic, understand the existing limitations and research gaps, and also identify new research directions. However, it is still not well understood the real benefits and challenges of offering a subject that addresses SLR for graduate students. Moreover, it is not known the difficulties faced by professors (i.e., educators) to teach this subject. The main goal of this paper is to present an experience report of teaching SLR, in particular, the benefits and challenges of this subject for computer science graduate students. In addition, this paper also presents the essential topics of SLR that we recommend to be taught and a better way to teach them, aiming at supporting graduate courses to offer it. For this, we surveyed computer science graduate students who attended the SLR subject that was taught for almost ten years in our institutions. In particular, we collected the lessons learned, findings, and insights; following, we summarized the benefits and challenges for students, the difficulties for professors, and also those essential topics to be taught. As a main result, the SLR subject can be considered a valuable opportunity for graduate students that could use this subject to conduct the required deep literature review of their research topic and have a better comprehension of their research area. Besides and more importantly, this subject can improve important research skills of students, including the ability to recognize research problems, analyze and synthesize data, think critically, and write papers. Therefore, we believe that graduate courses should analyze the possibility of offering the SLR subject.

Background: The software engineering community has increasingly conducted systematic literature reviews (SLR) as a means to summarize evidence from different studies and bring to light the state of the art of a given research topic. While SLR provide many benefits, they also present several problems with punctual solutions for some of them. However, two main problems still remain: the high time-/effort-consumption nature of SLR and the lack of an effective impact of SLR results in the industry, as initially expected for SLR. Aims: The main goal of this paper is to introduce a new view - which we name Sustainability of SLR - on how to deal with SLR aiming at reducing those problems. Method: We analyzed six reference studies published in the last decade to identify, group, and analyze the SLR problems and their interconnections. Based on such analysis, we proposed the view of Sustainability of SLR that intends to address these problems. Results: The proposed view encompasses three dimensions (social, economic, and technical) that could become SLR more sustainable in the sense that the four major problems and 31 barriers (i.e., possible causes for those problems) that we identified could be mitigated. Conclusions: The view of Sustainability of SLR intends to change the researchers' mindset to mitigate the inherent SLR problems and, as a consequence, achieve sustainable SLR, i.e., those that consume less time/effort to be conducted and updated with useful results for the industry.

Large software-intensive systems have emerged in several application domains, such as healthcare, transportation, smart environments, and Industry 4.0. Sometimes referred to as Systems-of-Systems (SoS) and resulted from the integration of various heterogeneous and independent software systems, such large systems lead to high dynamism and often operate in critical and uncertain environments. Hence, the reliability of these systems must be a concern, but traditional reliability approaches fail to cope with such high dynamism and uncertainty. Thus, new solutions are required to ensure the reliability of SoS. Moreover, there is a lack of studies that investigate the reliability of SoS. This paper presents the state of the art of the way that the reliability of SoS has been addressed. After investigating the literature, we selected 27 studies to perform a detailed analysis regarding factors that affect the reliability of SoS and approaches and metrics to improve it. We found an area still gaining maturity with researchers working in isolation and mainly developing solutions for domain-specific problems. There are still various critical open issues, while SoS have been increasingly adopted as a suitable and integrated solution in critical domains.

Context: A tertiary study can be performed to identify related reviews on a topic of interest. However, the elaboration of an appropriate and effective search string to detect secondary studies is challenging for Software Engineering (SE) researchers. Objective: The main goal of this study is to propose a suitable search string to detect secondary studies in SE, addressing issues such as the quantity of applied terms, relevance, recall and precision. Method: We analyzed seven tertiary studies under two perspectives: (1) structure – strings’ terms to detect secondary studies; and (2) field: where searching – titles alone or abstracts alone or titles and abstracts together, among others. We validate our string by performing a twostep validation process. Firstly, we evaluated the capability to retrieve secondary studies over a set of 1537 secondary studies included in 24 tertiary studies in SE. Secondly, we evaluated the general capacity of retrieving secondary studies over an automated search using the Scopus digital library. Results: Our string was capable to retrieve an optimum value of over 90% of the included secondary studies (recall) with a high general precision of almost 60%. Conclusion: The suitable search string for finding secondary studies in SE contains the terms “systematic review”, “literature review”, “systematic mapping”, “mapping study” and “systematic map”.

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Context: Systematic Literature Reviews (SLRs) are important instruments for both Software Engineering (SE) practitioners and scientific community. Their value directly depends on their quality and up-to-date results. However, most of the SLRs are outdated and the current scenario on how SLRs are documented does not favor their updating process. Goal: In this scenario, the main goal of this paper is to present an experience report on how to transfer the know-how of SLRs to facilitate their updates. Method: To address this issue, we used a Knowledge Management (KM) model, known as Nonaka-Takeuchi model, and described how we instantiated the Model for SLR update. We use two SLRs updates conducted by us to illustrate some of the knowledge sharing issues. Results: Our examples showed that the introduction of the concept of KM in the SLR update is in fact valuable, especially for sharing tacit knowledge (decisions) taken throughout the review process. Conclusions: We conclude that KM principles can be applied to manage the knowledge generated during the update of SLR.

Abstract Systems-of-Systems (SoS) combine heterogeneous, independent systems to offer complex functionalities for highly dynamic smart applications. Besides their dynamic architecture with continuous changes at runtime, SoS should be reliable and work without interrupting their operation and with no failures that could cause accidents or losses. SoS architectural design should facilitate the prediction of the impact of architectural changes and potential failures due to SoS behavior. However, existing approaches do not support such evaluation. Hence, these systems have been usually built without a proper evaluation of their architecture. This article presents Dynamic-SoS, an approach to predict/anticipate at design time the SoS architectural behavior at runtime to evaluate whether the SoS can sustain their operation. The main contributions of this approach comprise: (i) characterization of the dynamic architecture changes via a set of well-defined operators; (ii) a strategy to automatically include a reconfiguration controller for SoS simulation; and (iii) a means to evaluate architectural configurations that an SoS could assume at runtime, assessing their impact on the viability of the SoS operation. Results of our case study reveal Dynamic-SoS is a promising approach that could contribute to the quality of SoS by enabling prior assessment of its dynamic architecture.

Diabetes Mellitus is a life-long health condition that causes a high concentration of glucose in the blood. The foundation of the treatment and prevention of diabetes lays on reeducation and medication to prevent complications caused by high levels of glucose in the blood. New methods, products, and services, like those provided by the Ambient Assisted Living (AAL) domain, for supporting activities of the daily life of people with chronic diseases are effective to assist the management of diabetes disease. Particularly, Health Care Supportive Home (HSH) systems can provide an autonomous life in their residence to patients and supply them with autonomy through the use of different types of technologies. We present the software architecture of DiaManT@Home, a service-oriented HSH system that assists patients diagnosed with diabetes mellitus, and that enhances the self-management of their condition at home. DiaManT@Home was constructing following a well-established process based on the instantiation of a reference architecture for HSH systems. The software architecture of DiaManT@Home was assessed regarding the completeness of its software elements to achieve functional and non-functional requirements using prototypes. Results showed that DiaManT@Home can be considered as a complete solution to an HSH system for assisting patients at home. As future works, DiaManT@Home will be coded following the architecture presented in this work.

Nowadays, most human daily tasks can be performed by means of Mobile Applications (MobApps). Devices running such applications have some limitations (e.g., processing and storage) compared to personal computers. Therefore, integration of MobApps into service-based systems has been a feasible alternative to overcome these limitations. Moreover, these applications must be prepared to deal with the changes at runtime (e.g., user's new needs or modifications in their execution environment). In parallel, Reference Architectures (RA) have been used as an important way to support the development, standardization, and evolution of software systems. Although relevant, RA for the domain of MobApps based on services that require adaptation at runtime is still an issue to be explored in depth. This paper presents a RA for Self-MobApps (named RA4Self-MobApps), which aims to support the development of such applications. To show the applicability of our RA, a case study was conducted. As result, we observe our RA has good perspective to efficiently contribute to the Self-MobApps domain.

Software Engineering (SE) is an important topic to be taught in Computer Science courses. However, teaching of theoretical concepts with no link to their practical applications or no examples in the student's context may discourage learning, justifying why teaching and learning are great challenges of education in universities. In attempt to bridge such gap, several approaches have been proposed and applied to improve teaching and learning SE such as project based learning (PBL), a well-known approach already applied to teach SE. Nevertheless, there's a lack of understanding about how to better apply PBL and how to take advantage of this approach, for future use. There is also a lack of experience report describing how to use, its challenges and difficulties, what could be hampering to widely adopt it. We present our experience applying a PBL approach combined with project management to create an environment considering aspects such as dealing with managers and real stakeholders. The goal is to bring students closer to the reality of developing a software project in the business context. Our experience indicates positive results on the adoption of a PBL approach. In general, students were enthusiastic and positive about the use of this approach, the presence of a manager and the importance of using real-world problems with real stakeholders.

Owing to the critical role of software-intensive systems in society, software engineers have the accountability to consider sustainability as a goal while structuring a software system. However, there are no practical guidelines providing a tangible decomposition of the sustainability aspect. Moreover, there are limited quantifiable methods to support sustainable design and analysis.The purpose of this study is to help software practitioners to take sustainability into account by providing systematic guidelines for the software engineering process. We propose a framework that presents a meta model to decompose sustainability requirements and an assessment approach to evaluate sustainability achievements.This work presents an integrated framework that combines a goal-based approach, scenario-based approach, and feature modeling to gather sustainability related requirements and corresponding features. For sustainability assessment, software analysis and machine learning techniques are utilized to analyze software products based on sustainability metrics and criteria.The empirical study conducted with participants from academia and industry revealed that the proposed framework improves participant's ability to consider sustainability aspect in their software engineering tasks through focusing on requirements, design, and evaluation. With the provided sustainability meta-model, the participants could extract more stakeholders, requirements, and features in shorter time. Moreover, the empirical study result also demonstrated that this study is capable to indicate specific scenarios that should be redesigned to improve the sustainability achievements level.

Context: Despite being defined during the first phase of the Systematic Literature Review (SLR) process, the protocol is usually refined when other phases are performed. Several researchers have reported their experiences in applying SLRs in Software Engineering (SE) however, there is still a lack of studies discussing the iterative nature of the protocol definition, especially how it should be perceived by researchers conducting SLRs. Objective: The main goal of this study is to perform a survey aiming to identify: (i) the perception of SE researchers related to protocol definition; (ii) the activities of the review process that typically lead to protocol refinements; and (iii) which protocol items are refined in those activities. Method: A survey was performed with 53 SE researchers. Results: Our results show that: (i) protocol definition and pilot test are the two activities that most lead to further protocol refinements; (ii) data extraction form is the most modified item. Besides that, this study confirmed the iterative nature of the protocol definition. Conclusions: An iterative pilot testcan facilitate refinements in the protocol.

Self-adaptive Software (SaS), a special class of software system, constantly deals with some type of changes (i.e., structural and/or behavioral) to meet the user's new needs or autonomously react to modifications in its execution environment.Software adaptation, when manually performed, becomes an onerous and error-prone activity.Automated approaches have been adopted as a feasible alternative to overcome such adversities because they reduce the human involvement to a minimum.Based on this scenario, a Reference Architecture for SaS (RA4SaS) [1], [2] was designed in previous work.This architecture enables the adaptation of SaS at runtime by means of a controlled adaptation approach.In this sense, an automated process and a complete infrastructure to allow the phases of such process were also developed.This paper presents the design and implementation of a new module for automatic generation of source code for our architecture based on template engines [3].In short, the main benefits of this module can be summarized in three items: (i) higher design flexibility, maintenance and evolution of SaS; (ii) introduction of new capabilities for automatic generation of source code; and (iii) performance improvement.To present the operation of this new module, a case study was conducted.As result, we have observed that our architecture has good perspective to efficiently contribute to the SaS area.

Context: In order to preserve the value of Systematic Literature Reviews (SLRs), they should be frequently updated including new studies produced after the conduction of the reviews.However, most of SLRs are outdated and there is a lack of works that support the conduction of SLRs updates.Objective: The main goal of this paper is to report our experience in updating two of our SLRs.Method: To update these two SLRs, we used automated techniques based on VTM (Visual Text Mining) to guarantee the presence of relevant studies.Results: From our experience, some factors to satisfactorily update SLRs were identified: (i) to adopt software tools to support the updating process; (ii) to provide as much as possible information of previous SLR; (iii) to involve researchers from previous SLR; and (iv) to reuse protocol from preliminar SLR.Conclusions: Reported lessons learned can be used as a basis of knowledge to guide researchers when updating their SLRs.

International audience

Abstract Gang of Four (GoF) patterns are well‐known best practices for the design of object‐oriented systems. In this paper, we aim at empirically assessing their relationship to energy consumption, ie, a performance indicator that has recently attracted the attention of both researchers and practitioners. To achieve this goal, we investigate pattern‐participating methods (ie, those that play a role within the pattern) and compare their energy consumption to the consumption of functionally equivalent alternative (nonpattern) solutions. We obtained the alternative solution by refactoring the pattern instances using well‐known transformations (eg, replace polymorphism with conditional statements). The comparison is performed on 169 methods of 2 GoF patterns (namely, State/Strategy and Template Method), retrieved from 2 well‐known open source projects. The results suggest that for the majority of cases the alternative design excels in terms of energy consumption. However, in some cases (eg, when the method is large in size or invokes many methods) the pattern solution presents similar or lower energy consumption. The outcome of our study can be useful to both researchers and practitioners, because we: (1) provide evidence on a possible negative effect of GoF patterns, and (2) can provide guidance on which cases the use of the pattern is not hurting energy consumption.

The Ambient Assisted Living (AAL) domain aims to support the daily life activities of elders, patients with chronic conditions or disabled people, with a focus on ICT (Informatics and Communication Technologies). Important advances in AAL software systems have been already made, assisting people in their home, work, and social environments. Because of their critical nature, these systems must be developed focused on their quality. Hence, quality attributes (QAs), such as safety, reliability, and security, must be identified and well defined to successfully achieve the system purposes. However, there is not a set of QAs specific for AAL systems, hence, new systems have been developed based on general standards, such as ISO/IEC 25010, or based on particular experiences. This paper introduces the QM4AAL, a quality model (QM) for AAL systems. The QM4AAL was established and evaluated based on evidence from several published works found through conduction of a systematic mapping study. As result, the QM4AAL details QAs requirements, adaptive (e.g., self-configuring or situation-aware) or static properties, and stakeholders of AAL systems and their constituents systems (e.g., activity monitoring or health status monitoring systems). We intend this QM can orient the design and assessment of current and future AAL systems.

Systems-of-Systems (SoS) refer to large, complex, and software-intensive systems, resulted from the interoperability among heterogeneous, independent constituent systems. The main purpose of SoS is to perform tasks that could not be achieved by these constituents separately; besides, unique SoS characteristics impose new challenges to their development processes. We conducted a Systematic Mapping to identify initiatives, trends, and challenges in the SoS development and, as a result, 32 initiatives were identified. We also evaluated these initiatives with regard to the adherence to the technical processes of IEEE/ISO/IEC 15288:2015 and to the software implementation essential processes of IEEE/ISO/IEC 12207:2008. In general, these initiatives emphasize artifacts in the early stages of the development processes, addressing mainly requirements and architecture. Moreover, 17 of them emphasize the testing activity. We also summarized the SoS characteristics addressed in the studies and discuss the main trends and challenges.

The ability to modify its own structure and/or behavior at runtime is a native feature in the development of Self-adaptive Software (SaS).In previous work, a Reference Architecture for SaS (RA4SaS), an automated process for adaptation, and a framework for decision-making were developed to assist the development of SaS.Although such initiatives have collaborated with evolution of SaS, the design of the Decisionmaking Systems (DmS), element of first class for SaS, is manually conducted.Therefore, this paper presents a tool called DmS-Modeler, which aims to assist the development of DmS for SaS, providing facilities for modeling, calibration of such system, and automatic generation of infrastructure (i.e., source code and databases).Aiming to present the applicability of our tool, a case study was conducted and the results enable us to have good perspectives of contribution to the SaS area and other domains of software systems.

Reference architectures are a special type of software architectures that have been proposed for supporting standardization, development, and evolution of software systems of a given domain.As these architectures could contribute for knowledge reuse and increased productivity, several companies have been creating specific reference architectures for their field of expertise.Nonetheless, there is no mechanism that enable recovering, publishing, and sharing existing reference architectures for the public.The main contribution of this paper is to present RARep (Reference Architecture Repository), a web-based reference architecture repository supporting the dissemination of materials related to reference architectures.As a result, this tool can facilitate the access to information on reference architectures and, hence, promote the sharing of architectural knowledge contained in such architectures.

Population aging has brought important challenges at social, economical, and healthcare issues, mainly due to the increasing number of people that need intensive care. Ambient Assisted Living (AAL) systems that aim at assisting people in their health-related activities have emerged. In another perspective, Reference Architectures (RAs) are a special type of software architecture that promotes reuse of design expertise and facilitates the development, standardization, and evolution of software systems. During the last years, important RAs for AAL systems have been created. However, there is a lack of studies that compare RAs for healthcare systems in AAL domain, making the selection among RAs a rather difficult task. In this paper, we present a comparative analysis and evaluate the completeness of that healthcare RAs. Specifically, we intend to offer: (i) a guide to select the most complete and adequate RA for software projects, and (ii) to describe research directions to improve existing and future RAs for that systems.

Ambient Assisted Living (AAL) has become focus of attention for governmental organisations, and healthcare and ICT researchers. AAL includes methods, products, services, and software systems to support the everyday lives of elders. To develop AAL software systems, reference architectures (i.e., a special software architecture that guides the development, standardization, and evolution of systems architectures) have been proposed. Despite of the existing reference architectures, their use is a difficult task, due their high level of abstraction. Moreover, these architectures do not support the development of systems for telemonitoring and self-management of chronic diseases at home. The main objective of this project is to propose a reference architecture for Healthcare Supportive Home (HSH) systems. With this project we will contribute in promoting and reusing the knowledge of expertise and in supporting the development, standardization, evolution, and quality of HSH software systems.

Systems-of-Systems (SoS) refer to a new class of software-intensive systems, where their constituent systems work cooperatively in order to fulfill specific missions. Characterized by managerial and operational independence, geographic distribution, evolutionary development, and emergent behavior, SoS bring substantial challenges to the software engineering area. SESoS 2015, held in Florence, Italy, on May 17, 2015, as a joint workshop of the 37th International Conference on Software Engineering (ICSE), provided a forum to exchange ideas and experiences, analyze current research and development issues, discuss promising solutions, and to explore inspiring visions for the future of Software Engineering (SE) for SoS.

The development of Self-adaptive Software (SaS) presents specific innovative features compared to traditional ones since this type of software constantly deals with structural and/or behavioral changes at runtime.Capabilities of human administration are showing a decrease in relative effectiveness, since some tasks have been difficult to manage introducing potential problems, such as change management and simple human error.Self-healing systems, a system class of SaS, have emerged as a feasible solution in contrast to management complexity, since such system often combines machine learning techniques with control loops to reduce the number of situations requiring human intervention.This paper presents a framework based on learning techniques and the control loop (MAPE-K) to support the decision-making activity for SaS.In addition, it is noteworthy that this framework is part of a wider project developed by the authors of this paper in previous work (i.e., reference architecture for SaS [1]).Aiming to present the viability of our framework, we have conducted a case study using a flight plan module for Unmanned Aerial Vehicles.The results have shown an environment accuracy of about 80%, enabling us to project good perspectives of contribution to the SaS area and other domains of software systems, and enabling knowledge sharing and technology transfer from academia to industry.

Currently, Systems-of-Systems (SoS) have performed an important role in diverse application domains, with representative examples in airport, military, and smart-cities, including crisis/emergency management.SoS refer to complex software-intensive systems, resulted from interoperability of independent constituent systems, performing new missions that could not be performed by any constituents working separately.For these critical systems, their quality is undoubtedly essential.However, in general, there is a lack of studies that discuss how quality has been addressed in such systems.The main contribution of this paper is to present an experience of establishing a quality model (i.e., a set of quality characteristics/attributes, subcharacteristics, and metrics) for SoS, in particular, for the crisis/emergent management domain.This quality model is based on ISO/IEC 25010 and it has also proved to be an important support to evaluate a system of this domain, however their construction must be performed with caution.Experience such as presented in this work could be repeated in other domains, contributing to improve the quality of a diversity of critical, complex SoS that are currently being built.

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.

Software systems have become increasingly large and complex, often resulting from the integration of several operationally independent systems, thus leading to a new class of systems called Systems-of-Systems (SoS). Moreover, SoS have currently become essentially software-dependent systems, thus arising the Software-intensive Systems-of-Systems (SiSoS). However, in spite of their relevance, there is a lack of a common understanding of what exactly SiSoS are, their characteristics and types, as well as other elements that surround them. In this context, the main contribution of this work is to provide a conceptual model that provides a comprehensive understanding about them. For this purpose, we have extended the ISO/IEC/IEEE 42010 International Standard by considering related studies and previous taxonomies about SoS. In order to illustrate the use of our model, two software-intensive systems were analyzed and discussed. By establishing a common understanding about SiSoS, results achieved until now have showed us that this model can provide an important support to the research on SiSoS and, as a consequence, it can contribute to the development of these systems.

Reference architectures have emerged as a special type of software architecture that achieves well-recognized understanding of specific domains, promoting reuse of design expertise and facilitating the development, standardization, and evolution of software systems. Because of their advantages, several reference architectures have been proposed and have been also successfully used, including in the industry. However, the most of these architectures are still built using an ad-hoc approach, lacking of a systematization to their construction. If existing, these approaches could motivate and promote the building of new architectures and also support evolution of existing ones. In this scenario, the main contribution of this paper is to present the evolution of ProSA-RA, a process that systematizes the design, representation, and evaluation of reference architectures. ProSA-RA has been already applied in the establishment of reference architectures for different domains and this experience was used to evolve our process. In this paper, we illustrate an application of ProSA-RA in the robotics domain. Results achieved through the use of ProSA-RA have showed us that it is a viable, efficient process and, as a consequence, it could contribute to the reuse of knowledge in several applications domains, by promoting the establishment of new reference architectures.

Software Product Line (SPL) has arisen as an approach for developing a family of software-intensive systems at lower costs, within shorter time, and with higher quality. In particular, SPL is supported by a product line architecture (sometimes also referred to as reference architecture) that captures the architectures of a product family. From another perspective, a special type of architecture that contains knowledge about a specific domain has been increasingly investigated, resulting in the research area of Reference Architecture. In spite of the positive impact of this type of architecture on reuse and productivity, the use of the knowledge contained in existing reference architectures in order to develop SPL has not been widely explored yet. The main contribution of this paper is to present a process, named ProSA-RA2PLA, that systematizes the use of reference architectures for building product line architectures. To illustrate the application of this process, we have built a product line architecture for an SPL of software testing tools using a reference architecture of that domain. Based on initial results, we have observed that benefits can be achieved, mainly regarding improvement in reuse and productivity to develop SPL.

The term bug prevalence is derived from the medical world vocabulary and applied to Software Product Line (SPL), meaning all products that are affected by one particular bug. In single systems development, this concept is not relevant since a bug is either present or not. However, when it comes to SPL, analyzing the bug prevalence of a certain bug is still a challenge and a highly relevant topic, since the same bug may be present in several products. To support this analysis, the main contribution of this paper is the Product Genealogy approach. A core concept in our approach is the Product Genealogy Tree, in which the hierarchy of products in the SPL is represented, reflecting how each product evolved or was derived from another or from the core assets. In this context, the benefit of such a tree is the rapid visualization of the product's structure in the SPL, providing input on which products are to be examined initially. Besides that, in this paper we introduce a novel analogy between the medical genetics world and SPL in order to better explain the principles of our approach.

Software architecture has received increasing attention of practitioners and researchers, since it has played a significant role in determining the success and quality of software systems. At the same time, the success of Open Source Software (OSS) has also sparked interest of researchers in the universities and in the software industry. OSS has been largely used and developed and, as a consequence, the OSS quality has been a concern and an interesting subject for researchers. However, in spite of narrow relation between software architecture and software quality, there is lack of more detailed works that investigate how software architecture can influence OSS quality. In this paper, we present a case study reporting how software architecture is directly related to OSS quality. We have hence proposed architecture refactoring activity in order to repair software architectures, aiming at improving mainly maintainability, functionality and usability of these systems.

Mutation testing (Mutation Analysis), although powerful in revealing faults, is considered a computationally expensive criterion, due to the high number of mutants created and the effort to determine the equivalent mutants. Using mutation-based alternative testing criteria it is possible to reduce the number of mutants but it is still necessary to determine the equivalent ones. In this paper the Bayesian Learning(one of the Artificial Intelligence techniques used in machine learning) is investigated to define the Bayesian Learning-Based Equivalent Detection Technique (BaLBEDeT), which provides guidelines to help the tester to analyze the live mutants in order to determine the equivalent ones.