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The fourth industrial revolution, i.e., Industry 4.0, is associated with Cyber-Physical Systems (CPS), which are entities integrating hardware (e.g., smart sensors and actuators connected through the Industrial Internet of Things) together with control and analytics software used to drive and support decisions at several levels. The latest developments in Artificial Intelligence (AI) and Machine Learning (ML) have enabled increased autonomy and closer human-robot cooperation in the production and manufacturing industry, thus leading to Autonomous Cyber-Physical Production Systems (ACPPS) and paving the way to the fifth industrial revolution (i.e., Industry 5.0). ACPPS are increasingly critical due to the possible consequences of their malfunctions on human co-workers, and therefore, evaluating their trustworthiness is essential. This article reviews research trends, relevant attributes, modeling languages, and tools related to the model-based trustworthiness evaluation of ACPPS. As in many other engineering disciplines and domains, model-based approaches, including stochastic and formal analysis tools, are essential to master the increasing complexity and criticality of ACPPS and to prove relevant attributes such as system safety in the presence of intelligent behaviors and uncertainties.

Understanding and improving education are critical goals of learning analytics. However, learning is not always mediated or aided by a digital system that can capture digital traces. Learning in such environments can be studied by recording, processing, and analyzing different signals, including video and audio, so that traces of actors’ actions and interactions are captured. Multimodal Learning Analytics refers to analyzing these signals through the use and integration of these multiple modes. However, a need exists to evaluate how research is conducted in the emerging field of multimodal learning analytics to aid and evaluate how these systems work. With the growth of multimodal learning analytics, research trends and technologies are needed to support its development. We conducted a systematic mapping study based on established systematic literature practices to identify multimodal learning analytics research types, methodologies, and trending research themes. Most mapped papers presented different solutions and used evaluation-based research methods to demonstrate an increasing interest in multimodal learning analytics technologies. In addition, we identified 14 topics under four themes––learning context, learning process, systems and modality, and technologies––that can contribute to the growth of multimodal learning analytics.

In the world of microservices, companies must be able to create systems that operate in the most efficient way. To achieve this, anti-patterns must be avoided because of their detriment to the quality of the system. Some of the most troubling anti-patterns are hard to detect because of their appearance at runtime. Effectively removing anti-patterns from a system requires dynamic analysis because of the large size of microservice-based systems. While the detection of anti-patterns is helpful, being able to visualize them offers a great benefit to companies working with microservices. Seeing how the overall system is flowing and recognizing the existence of anti-patterns can help improve microservice-based systems. In this paper, a systematic mapping study was performed to find the current state of research on visualizing anti-patterns in microservices from the dynamic perspective. Several hundred papers were examined and a total of 31 were found to be relevant to the research topic. The papers, when analyzed, revealed that there are mechanisms to detect anti-patterns at runtime in microservices, and there are also mechanisms for visualizing the architecture of a microservice-based system. This study’s findings could help to identify and remove anti-patterns that occur during runtime in microservices, as well as a means of visualizing these anti-patterns.

Modern automotive systems increasingly depend on camera sensors to gather safetycriticaldata used in driver-assisting features of the system. These features can consist offor example, lane-keeping assist and automatic braking where the sensors register objectswithin certain distances. When these camera sensors gather information, the time of theimage is critical for the calculation of speeds, distances, and size of any potential registeredobject in the frame. Limitations of bandwidth and computing in such vehicles creates aneed to use special cameras that do not capture the whole image simultaneously but insteadcapture the images piecewise. These cameras are called rolling shutter cameras. Thisputs pressure on defining when an image was captured when different parts of the imagewere captured at different points in time. For this thesis, this point in time is defined as thechronological middle point in between the camera starting to capture an image and when ithas collected the final part of it. This thesis performs a mapping-study to evaluate methodsto verify the timestamp of an image generated from rolling shutter cameras. Further, thisthesis proposes a new method using multiple digital clocks and presents its performanceusing a proof-of-concept implementation to prove the method’s ability to accurately representtime with sub-millisecond accuracy.

Context: Variant-Rich Systems (VRSs), such as Software Product Lines or variants created through clone & own, aim at reusing existing assets. The long lifespan of families of variants, and the scale of both the code base and the workforce make VRS maintenance and evolution a challenge. Visualization tools are a needed companion. Objective: We aim at mapping the current state of visualization interventions in the area of VRS evolution. We tackle evolution in both functionality and architecture. Three research questions are posed: What sort of analysis is being conducted to assess VRS evolution? (Analysis perspective); What sort of visualizations are displayed? (Visualization perspective); What is the research maturity of the reported interventions? (Maturity perspective). Methods: We performed a systematic mapping study including automated search in digital libraries, expert knowledge, and snowballing. Results: The study reports on 41 visualization approaches to cope with VRS evolution. Analysis wise, feature identification and location is the most popular scenario, followed by variant integration towards a Software Product Line. As for visualization, nodelink diagram visualization is predominant while researchers have come up with a wealth of ingenious visualization approaches. Finally, maturity wise, almost half of the studies are solution proposals. Most of the studies provide proof-of-concept, some of them also include publicly available tools, yet very few face proof-of-value. Conclusions: This study introduces a comparison framework where to frame future studies. It also points out distinct research gaps worth investigating as well as shortcomings in the evidence about relevance and contextual considerations (e.g., scalability).

Understanding and improving education are critical goals of learning analytics. However, learning is not always mediated or aided by a digital system that can capture digital traces. Learning in such environments can be studied by recording, processing, and analyzing different signals, including video and audio, so that traces of actors’ actions and interactions are captured. Multimodal Learning Analytics refers to analyzing these signals through the use and integration of these multiple modes. However, a need exists to evaluate how research is conducted in the emerging field of multimodal learning analytics to aid and evaluate how these systems work. With the growth of multimodal learning analytics, research trends and technologies are needed to support its development. We conducted a systematic mapping study based on established systematic literature practices to identify multimodal learning analytics research types, methodologies, and trending research themes. Most mapped papers presented different solutions and used evaluation-based research methods to demonstrate an increasing interest in multimodal learning analytics technologies. In addition, we identified 14 topics under four themes––learning context, learning process, systems and modality, and technologies––that can contribute to the growth of multimodal learning analytics.

Background: The distribution of retroperitoneal lymph node metastases for patients with nonseminoma and a residual tumour of 10-49 mm in a population-based setting is unknown. This information is needed to justify selection of patients for a unilateral template resection. Objective: To describe the location of retroperitoneal metastases and recurrences in patients with nonseminoma germ cell tumour (NSGCT) with a residual tumour of 10-49 mm. Design, setting, and participants: RETROP is a population-based prospective observational mapping study of 213 patients in Sweden and Norway with a retroperitoneal residual tumour of 10-49 mm who underwent postchemotherapy retroperitoneal lymph node dissection for metastatic NSGCT during 2007-2014 with median follow-up of 100 mo. Patients were classified according to the testis primary tumour and the distribution of unilateral or bilateral lymph node metastases (with reference to the aorta) present on pre- and/or postchemotherapy computed tomography (CT) scans. Outcome measurements and statistical analysis: The distribution and rate of teratoma or cancer in unilateral or bilateral retroperitoneal fields and the location and rate of retroperitoneal recurrence were measured. Results and limitations: In total, 65% of the patients had unilateral retroperitoneal lymph node metastases (RLNMs) on CT scans. Patients with unilateral RLNMs had a low risk of contralateral teratoma or cancer (1.6% for right- and 2.6% for left-sided NSGCT) or retroperitoneal recurrence (0% for right- and 4% for left-sided NSGCT). A weakness of the study is that the pathology specimen could not be fully designated to one specific area for some of the patients. Conclusions: Men with postchemotherapy residual disease of 10-49 mm and unilateral metastases on pre- and postchemotherapy CT scans have a low risk of contralateral disease and should be considered for a unilateral template resection. Patient summary: The surgeon can use computed tomography (CT) scans in

As a leader of the contribution in public policy and scientific knowledge, Policy Studies has impacted a broad audience, both theoretic and practical. This article aims to provide a complete overview of research trends and research themes published in Policy Studies during the period 2015-2020 with a bibliometric approach. Bibliographic data downloaded from Scopus database. The study uses the bibliometric tools with VOSviewer and R studio programming. Findings indicate that Policy Studieshas consistently published in policy science research. During that period, most researchers were from developed countries, and much of their work was influential. Seven main clusters are often discussed in the Policy Studies to more comprehensive detail, the future research not only uses the Scopus indexation but also other credible international indexations.

With the increase of research in self-adaptive systems, there is a need to better understand the way research contributions are evaluated. Such insights will support researchers to better compare new findings when developing new knowledge for the community. However, so far there is no clear overview of how evaluations are performed in self-adaptive systems. To address this gap, we conduct a mapping study. The study focuses on experimental evaluations published in the last decade at the prime venue of research in software engineering for self-adaptive systems - the International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). Results point out that specifics of self-adaptive systems require special attention in the experimental process, including the distinction of the managing system (i.e., the target of evaluation) and the managed system, the presence of uncertainties that affect the system behavior and hence need to be taken into account in data analysis, and the potential of managed systems to be reused across experiments, beyond replications. To conclude, we offer a set of suggestions derived from our study that can be used as input to enhance future experiments in self-adaptive systems.

With the increasing ubiquity and scale of self-adaptive systems, there is a growing need to decentralize the functionality that realizes self-adaptation. Our focus is on architecture-based self-adaptive systems where one or more functions for monitoring, analyzing, planning, and executing are realized by multiple components that coordinate with one another. While some earlier studies have shed light on existing work on the decentralization of self-adaptive systems, there is currently no clear overview of the state of the art in decentralization of self-adaptive systems. Yet, having a precise view on the state of the art in decentralized self-adaptive systems is crucial for researchers to understand existing solutions and drive future research efforts. To address this gap, we conducted a mapping study. The study focused on papers published at 24 important venues that publish research on self-adaptation. The study focused on the motivations for choosing a decentralized approach to realize self-adaptation, the adaptation functions that are decentralized, the realization of the coordination, and the open challenges in the area.

This article reports article reports on a mapping study to investigate the C-ROADS Day 1 C-ITS application Green Light Optimal Speed Advisory (GLOSA). In the study, 64 publications between 2006 and 2019 where reviewed and classified according to a schema developed using thematic analysis of the selected publications. Among the findings were that the typical publication evaluates through simulation benefits for the equipped vehicle, leaving considerable gaps in investigations of societal effects. Additionally, there is a lack of investigation on driver behaviour, both for the equipped vehicle and for fellow road users—the ability to accurately model such behaviour is necessary for reliable simulation results., This is an open access article under the CC BY-NC-ND license.

The purpose of this study is to survey existing information security policy (ISP) construction research to understand to what extent the concept of tailored ISP and user involvement have been considered by researchers. The results are based on a literature mapping study of ISP construction between 1990 and 2017 in Scopus and Web of Science databases. The findings show that researchers have not given tailoring of ISPs any attention and there are only a few researchers that paid attention to involving users in constructing ISPs. This research has implications for both researchers and practitioners and shows the way for the future researches by focusing on the concept of tailored policy and how it can be achieved as well as involving users in such tailoring.

Context Empirical research in software engineering contributes towards developing scientific knowledge in this field, which in turn is relevant to inform decision-making in industry. A number of empirical studies have been carried out to date in software engineering, and the need for guidelines for conducting and evaluating such research has been stressed. Objective: The main goal of this mapping study is to identify and summarize the body of knowledge on research guidelines, assessment instruments and knowledge organization systems on how to conduct and evaluate empirical research in software engineering. Method: A systematic mapping study employing manual search and snowballing techniques was carried out to identify the suitable papers. To build up the catalog, we extracted and categorized information provided by the identified papers. Results: The mapping study comprises a list of 341 methodological papers, classified according to research methods, research phases covered, and type of instrument provided. Later, we derived a brief explanatory review of the instruments provided for each of the research methods. Conclusion: We provide: an aggregated body of knowledge on the state of the art relating to guidelines, assessment instruments and knowledge organization systems for carrying out empirical software engineering research; an exemplary usage scenario that can be used to guide those carrying out such studies is also provided. Finally, we discuss the catalog's implications for research practice and the needs for further research. © 2018 Elsevier B.V.

Software ecosystems (SECOs) and open innovation processes have been claimed as a way forward for the software industry. A proper understanding of requirements is as important for SECOs as for more traditional ones. This article presents a mapping study on the issues of RE and quality aspects in SECOs. Our findings indicate that among the various phases or subtasks of RE, most of the SECO specific research has been accomplished on elicitation, analysis, and modeling. On the other hand, requirement selection, prioritization, verification, and traceability has attracted few published studies. Among the various quality attributes, most of the SECOs research has been performed on security, performance and testability. On the other hand, reliability, safety, maintainability, transparency, usability attracted few published studies. The article provides a review of the academic literature about SECO-related RE activities, modeling approaches, and quality attributes, positions the source publications in a taxonomy of issues and identifies gaps where there has been little research.

Migrating a family of software systems from ad-hoc development approaches such as `clone-and-own' towards software product lines (SPL) is a challenging task. Software architecture recovery techniques can play a crucial role in such a migration. However, it is to date still unclear how these techniques, which have been mostly developed for single system architecture recovery in mind, can be utilized in an SPL context most effectively. In this paper, we present a mapping study examining 35 research articles with the purpose of discussing the current state of the art in applying software architecture recovery techniques for SPL and identifying potential research gaps in this area. The results provide evidence that currently used approaches do not seem to consider the potential architectural degradation that might exist in the family of systems to be migrated. Moreover, it is hard to generalize across empirical studies as currently it seems difficult to compare and benchmark the approaches applied for software product line architecture (SPLA) extraction/reconstruction., REVaMP2 - Round-Trip Engineering and Variability Management Platform and Process - http://www.revamp2-project.eu

Background: Since the mid-1990s concerns have been raised regarding the possible links between suicide and the Internet, especially among adolescents and young adults. Aims: To identify the nature and extent of the scientific publications, especially original research studies, on suicide and the Internet, and to investigate how the field has developed over time. In particular, this mapping study looks at types of publications, topic areas, focus of original research papers, and suicide-related variables of interest in publications. Method: A search of three major databases (PubMED, PsycINFO, and Sociological Abstracts) was conducted to identify papers published until the end of January 2015. Results: The study identified 237 publications on suicide and the Internet published from 1997 to the end of January 2015. These included 122 original research papers. The three most frequent topic areas covered in publications were searching for information on suicide, online interventions, and online suicide-related behaviors. The online mediums most frequently studied were online forums/message boards, search engines, intervention and information websites, and social media. Limitations: The mapping study did not include an analysis of results of research studies and did not assess their quality. Conclusion: The field is rapidly evolving, as seen in the recent increase in the number of publications. However, there are gaps in terms of the countries where research is conducted and the coverage of topics.

Context. The effective generation of test data is regarded as very important in the software testing. However, mature and effective techniques for generating string test data have seldom been explored due to the complexity and flexibility in the expression form of the string comparing to other data types. Objectives. Based on this problem, this study is to investigate strengths and limitations of existing string test data generation techniques to support future work for exploring an effective technique to generate string test data. This main goal was achieved via two objectives. First is investigating existing techniques for string test data generation; as well as finding out criteria and Classes-Under-Test (CUTs) used for evaluating the ability of string test generation. Second is to assess representative techniques through comparing effectiveness and efficiency. Methods. For the first objective, we used a systematic mapping study to collect data about existing techniques, criteria, and CUTs. With respect to the second objective, a comparison study was conducted to compare representative techniques selected from the results of systematic mapping study. The data from comparison study was analysed in a quantitative way by using statistical methods. Results. The existing techniques, criteria and CUTs which are related to string test generation were identified. A multidimensional categorisation was proposed to classify existing string test data generation techniques. We selected representative techniques from the search-based method, symbolic execution method, and random generation method of categorisation. Meanwhile, corresponding automated test generation tools including EvoSuite, Symbolic PathFinder (SPF), and Randoop, which achieved representative techniques, were selected to assess through comparing effectiveness and efficiency when applied to 21 CUTs. Conclusions. We concluded that: search-based method has the highest effectiveness and efficiency in three selecte

Context: Facing the implementation of the EU General Data Protection Regulation in May 2018, many commercial software providers will soon need to adapt their products to new privacy-related constraints. Privacy patterns defined for different aspects of the software engineering process promise to be a useful concept for this task. In this situation, it seems valuable to characterize the state of the research related to privacy patterns.Objective: To identify, characterize and classify the contributions made by published research results related to patterns in the context of considering privacy concerns in engineering software. Method: A literature review in form of a mapping study of scientific articles was performed. The resulting map structures the relevant body of work into multiple dimensions, illustrating research focuses and gaps.Results: Results show that empirical evidence in this field is scarce and that holistic approaches to engineering privacy into software based on patterns are lacking. This potentially hinders industrial adoption.Conclusion: Based on these results, we recommend to empirically validate existing privacy patterns, to consolidate them in pattern catalogues and languages, and to move towards seamless approaches from engineering privacy requirements to implementation.

Software ecosystems is one promising strategy for organizations to find new market segments, new innovative value propositions creating new value streams. However, understanding internal and external actors, resources and relationships that could be leveraged in a SECO is critical for their strategic decisions. The consequence of mistakes may be costly failures that can force an organization to move out of a market. This paper describes a systematic mapping study that targets description of software ecosystems. Our conjecture is that adequate description support leads to modeling, which will improve information and in turn strategic decisions. The survey searches existing literature for description techniques and their application for comprehensive description. The study identifies and maps 63 primary studies out of 937 candidates according to their degree of modeling support and several other important aspects for SECO description. The analysis indicates that no approach fully supports comprehensive SECO descriptions, supporting domain specific and view specific modeling of ecosystem concerns. The analysis is used to highlight areas for a future research agenda.

Context: Model-Driven Development (MDD) and Service-Oriented Architecture (SOA) are two challenging research areas in software engineering. MDD is about improving software development whilst SOA is a service-based conceptual development style, therefore investigating the available proposals in the literature to use MDD when developing SOA may be insightful. However, no studies have been found with this purpose. Objective: This work aims at assessing the state of the art in MDD for SOA systems. It mainly focuses on: what are the characteristics of MDD approaches that support SOA; what types of SOA are supported; how do they handle non-functional requirements. Method: We conducted a mapping study following a rigorous protocol. We identified the representative set of venues that should be included in the study. We applied a search string over the set of selected venues. As result, 129 papers were selected and analysed (both frequency analysis and correlation analysis) with respect to the defined classification criteria derived from the research questions. Threats to validity were identified and mitigated whenever possible. Results: The analysis allows us to answer the research questions. We highlight: (1) predominance of papers from Europe and written by researchers only; (2) predominance of top-down transformation in software development activities; (3) inexistence of consolidated methods; (4) significant percentage of works without tool support; (5) SOA systems and service compositions more targeted than single services and SOA enterprise systems; (6) limited use of metamodels; (7) very limited use of NFRs; and (8) limited application in real cases. Conclusion: This mapping study does not just provide the state of the art in the topic, but also identifies several issues that deserve investigation in the future, for instance the need of methods for activities other than software development (e.g., migration) or the need of conducting more real case studies., Peer Reviewed, Postprint (author's final draft)

The popularity of Open Source Software (OSS) has increased the interest in using it in safety critical applications. The aim of this study is to review research carried out on usage of open source code in development of safety-critical software and systems. We conducted a systematic mapping study through searches in library databases and manual identification of articles from open source conferences.We have identified 22 studies about using open source software, mainly in automotive, aerospace, medical and nuclear domains. Moreover, only a few studies present complete safety systems that are released as OSS in full. The most commonly used OSS functionalities are operating systems, imaging, control and data management. Finally most of the integrated OSS have mature code bases and a commit history of more than five years.

[EN] The HCI community has developed guidelines and recommendations for improving the usability system that are usually applied at the last stages of the software development process. On the other hand, the SE community has developed sound methods to elicit functional requirements in the early stages, but usability has been relegated to the last stages together with other nonfunctional requirements. Therefore, there are no methods of usability requirements elicitation to develop software within both communities. An example of this problem arises if we focus on the Model-Driven Development paradigm, where the methods and tools that are used to develop software do not support usability requirements elicitation. In order to study the existing publications that deal with usability requirements from the first steps of the software development process, this work presents a mapping study. Our aim is to compare usability requirements methods and to identify the strong points of each one

Context: Software startups are newly created companies with no operating history and are extremely fast in producing cutting-edge technologies. These companies develop software un- der highly uncertain conditions, tackling fast growing markets with severe lack of resources. Startups present an unique combination of characteristics which pose several challenges to the software development activities, creating interesting problems for software engineers. However, despite the increasing economical importance and the high failure rate, there are only a few sci- entific studies attempting to address software engineering (SE) issues, especially for early-stages startups. In a context where a wrong decision can easily lead the entire business to failure, the support of SE can contribute to foster performances of startups and making a big impact on a large number of companies. Objective: In view of a lack of primary studies, the first step to attending the software development strategies with scientific and engineering approaches is by an understanding of the startups’ behavior. For this reason this research aims to understand how software development strategies are engineered by practitioners, in the period of time that goes from idea conception to the first open beta release of the software product. Methods: This research combines a systematic review of the state-of-the-art with a cross- sectional case study conducted in 13 web startups recently founded and distributed in di↵erent geographic areas and market sectors. A grounded theory approach guided the execution of a sys- tematic mapping study, integrated with semi-structured interviews and follow-up questionnaires to explore the state-of-practice. Results: We selected, classified and evaluated 37 relevant studies. The systematic review revealed that the studies which constitute the body of knowledge are generally not rigorously designed and executed, make use of inconsistent terminology, and cover only small samples of