SMS-Builder: An adaptive software tool for building systematic mapping studies

A Systematic Mapping Study is an instrument frequently used to carry out a search process, identification, and classification of studies in different fields. Researchers in front of this type of process have a challenge while managing the data about these studies. This paper presents a software tool that has been created to help those who need to build a systematic mapping study. In addition, this work follows the evidence-based software engineering approach and extends it through a software tool by including different ways of adapting this process

SMS-Builder: An adaptive software tool for building systematic mapping studies

A Systematic Mapping Study is an instrument frequently used to carry out a search process, identification, and classification of studies in different fields. Researchers in front of this type of process have a challenge while managing the data about these studies. This paper presents a software tool that has been created to help those who need to build a systematic mapping study. In addition, this work follows the evidence-based software engineering approach and extends it through a software tool by including different ways of adapting this process

Software Engineering Applications enabled by Blockchain Technology: A Systematic Mapping Study

The novel, yet disruptive blockchain technology has witnessed growing attention, due to its intrinsic potential. Besides the conventional domains that benefit from such potential, such as finance, supply chain and healthcare, blockchain use cases in software engineering have emerged recently. In this study, we aim to contribute to the body of knowledge of blockchain-oriented software engineering by providing an adequate overview of the software engineering applications enabled by blockchain technology. To do so, we carried out a systematic mapping study and identified 22 primary studies. Then, we extracted data within the research type, research topic and contribution type facets. Findings suggest an increasing trend of studies since 2018. Additionally, findings reveal the potential of using blockchain technologies as an alternative to centralized systems, such as GitHub, Travis CI, and cloud-based package managers, and also to establish trust between parties in collaborative software development. We also found out that smart contracts can enable the automation of a variety of software engineering activities that usually require human reasoning, such as the acceptance phase, payments to software engineers, and compliance adherence. In spite of the fact that the field is not yet mature, we believe that this systematic mapping study provides a holistic overview that may benefit researchers interested in bringing blockchain to the software industry, and practitioners willing to understand how blockchain can transform the software development industry.publishedVersio

Mapping the systematic literature studies about software ecosystems

There is a need to improve the definition and development of technological ecosystems in order to solve the main problems detected in previous studies. To achieve this goal, it is required to identify and analyse the solutions available in the literature in the field of software engineering applied to ecosystems. The research in software ecosystems is a relatively young research area, but there are already several works that analyse the literature associated. To conduct a new systematic literature review is necessary to ensure that there are no studies that do the same, namely, that do not answer the same research questions. The identification of the need for a review was done through a study focused on systematic literature reviews and mapping studies about software ecosystems. This work aims to describe the mapping conducted as part of that study. It provides a global state of the art of this kind of studies in the area of software ecosystems

Architectural Support for Software Performance in Continuous Software Engineering: A Systematic Mapping Study

The continuous software engineering paradigm is gaining popularity in modern development practices, where the interleaving of design and runtime activities is induced by the continuous evolution of software systems. In this context, performance assessment is not easy, but recent studies have shown that architectural models evolving with the software can support this goal. In this paper, we present a mapping study aimed at classifying existing scientific contributions that deal with the architectural support for performance-targeted continuous software engineering. We have applied the systematic mapping methodology to an initial set of 215 potentially relevant papers and selected 66 primary studies that we have analyzed to characterize and classify the current state of research. This classification helps to focus on the main aspects that are being considered in this domain and, mostly, on the emerging findings and implications for future researc

Software development in startup companies: A systematic mapping study

Context: Software startups are newly created companies with no operating history and fast in producing cutting-edge technologies. These companies develop software under highly uncertain conditions, tackling fast-growing markets under severe lack of resources. Therefore, software startups present an unique combination of characteristics which pose several challenges to software development activities. Objective: This study aims to structure and analyze the literature on software development in startup companies, determining thereby the potential for technology transfer and identifying software development work practices reported by practitioners and researchers. Method: We conducted a systematic mapping study, developing a classification schema, ranking the selected primary studies according their rigor and relevance, and analyzing reported software development work practices in startups. Results: A total of 43 primary studies were identified and mapped, synthesizing the available evidence on software development in startups. Only 16 studies are entirely dedicated to software development in startups, of which 10 result in a weak contribution (advice and implications (6); lesson learned (3); tool (1)). Nineteen studies focus on managerial and organizational factors. Moreover, only 9 studies exhibit high scientific rigor and relevance. From the reviewed primary studies, 213 software engineering work practices were extracted, categorized and analyzed. Conclusion: This mapping study provides the first systematic exploration of the state-of-art on software startup research. The existing body of knowledge is limited to a few high quality studies. Furthermore, the results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context