ALBERT

Description: During software development activities, it is important for Information and Communication Technology (ICT) practitioners to know and understand practices and guidelines regarding information privacy, as software requirements must comply with data privacy laws and members of development teams should know current legislation related to the protection of personal data. In order to gain a better understanding on how industry ICT practitioners perceive the practical relevance of software privacy and privacy requirements and how these professionals are implementing data privacy concepts, we conducted a survey with ICT practitioners from software development organizations to get an overview of how these professionals are implementing data privacy concepts during software design. We performed a systematic literature review to identify related works with software privacy and privacy requirements and what methodologies and techniques are used to specify them. In addition, we conducted a survey with ICT practitioners from different organizations. Findings revealed that ICT practitioners lack a comprehensive knowledge of software privacy and privacy requirements and the Brazilian General Data Protection Law (Lei Geral de Proteção de Dados Pessoais, LGPD, in Portuguese), nor they are able to work with the laws and guidelines governing data privacy. Organizations are demanded to define an approach to contextualize ICT practitioners with the importance of knowledge of software privacy and privacy requirements, as well as to address them during software development, since LGPD must change the way teams work, as a number of features and controls regarding consent, documentation, and privacy accountability will be required.

Description: The correct classification of requirements has become an essential task within software engineering. This study shows a comparison among the text feature extraction techniques, and machine learning algorithms to the problem of requirements engineer classification to answer the two major questions “Which works best (Bag of Words (BoW) vs. Term Frequency–Inverse Document Frequency (TF-IDF) vs. Chi Squared (CHI2)) for classifying Software Requirements into Functional Requirements (FR) and Non-Functional Requirements (NF), and the sub-classes of Non-Functional Requirements?” and “Which Machine Learning Algorithm provides the best performance for the requirements classification task?”. The data used to perform the research was the PROMISE_exp, a recently made dataset that expands the already known PROMISE repository, a repository that contains labeled software requirements. All the documents from the database were cleaned with a set of normalization steps and the two feature extractions, and feature selection techniques used were BoW, TF-IDF and CHI2 respectively. The algorithms used for classification were Logist Regression (LR), Support Vector Machine (SVM), Multinomial Naive Bayes (MNB) and k-Nearest Neighbors (kNN). The novelty of our work is the data used to perform the experiment, the details of the steps used to reproduce the classification, and the comparison between BoW, TF-IDF and CHI2 for this repository not having been covered by other studies. This work will serve as a reference for the software engineering community and will help other researchers to understand the requirement classification process. We noticed that the use of TF-IDF followed by the use of LR had a better classification result to differentiate requirements, with an F-measure of 0.91 in binary classification (tying with SVM in that case), 0.74 in NF classification and 0.78 in general classification. As future work we intend to compare more algorithms and new forms to improve the precision of our models.

Description: Information and Communication Technology (ICT) Governance is increasingly necessary and present in organizations aiming to improve the maturity of their ICT processes. This paper presents an analysis of the ICT Governance processes of a Brazilian Federal Public Administration agency. To assess the maturity of the ICT Governance processes, we surveyed and diagnosed the processes performed by the agency and organized a series of meetings/discussions to assist in the improvement and modeling of the processes related to the ICT Contract Planning process. As a result, we proposed improvements and identified the maturity level of the existing ICT processes, also assessing the awareness of employees of the General Coordination of Information Technology regarding these processes. Our findings reveal that the agency still needs to implement the following processes: (1) ICT People Management; (2) Business Process Modeling (Automated/to Automate); (3) Change Management; (4) Execution Monitoring of the ICT Projects and Services Portfolio; and (5) ICT Service Continuity Management. We also identified several artifacts that need to be implemented by the agency in different processes and collected survey participants’ suggestions about new processes to improve the maturity in ICT Governance.

Description: Internet of Things comprises an increasing number of interconnected smart devices, where communication happens anytime, anywhere, reducing hardware costs and the complexity of the architectures. Reading Radio Frequency Identification tags using ultra high frequency is a high-cost activity because of its infrastructure and the radio frequency identification tag reading device for these frequencies. This work proposes an architecture that enables the cost reduction of Radio Frequency Identification tag reading equipment operating ultra high frequency in an infrastructure using cloud computing and microservices. The use of cloud computing and microservices was necessary due to scalability and the management of large volumes of data that can be generated by reading Radio Frequency Identification tags using ultra high frequency and the complexity of the architecture related to the theme of this work. The proposed architecture was applied in a real case study to verify its adherence and compliance. The proposed architecture can be used in any system that presents similar characteristics to the one proposed in this work. In scenarios where reading distance is a fundamental requirement, it is necessary to include an external antenna for better results. Other practical experiments will be carried out to evaluate the use of the proposed architecture in other contexts related to the use of Internet of Things and reading of Radio Frequency Identification tags.

Description: Agile methods fit well for software development teams in the requirements elicitation activities. It has brought challenges to organizations in adopting the existing traditional methods, as well as new ones. Design Thinking has been used as a requirements elicitation technique and immersion in the process areas, which brings the client closer to the software project team and enables the creation of better projects. With the use of data triangulation, this paper brings a literature review that collected the challenges in software requirements elicitation in agile methodologies and the use of Design Thinking. The result gave way to a case study in a Brazilian public organization project, via user workshop questionnaire with 20 items, applied during the study, in order to identify the practice of Design Thinking in this context. We propose here an overview of 13 studied challenges, from which eight presented strong evidence of contribution (stakeholders involvement, requirements definition and validation, schedule, planning, requirement details and prioritization, and interdependence), three presented partial evidence of contribution and two were not eligible for conclusions (non-functional requirements, use of artifacts, and change of requirements). The main output of this work is to present an analysis of the use of Design Thinking to see if it fits properly to be used as a means of solving the challenges of elicitation of software requirements when using agile methods.

Description: Computer science is a predominantly male field of study. Women face barriers while trying to insert themselves in the study of computer science. Those barriers extend to when women are exposed to the professional area of computer science. Despite decades of social fights for gender equity in Science, Technology, Engineering, and Mathematics (STEM) education and in computer science in general, few women participate in computer science, and some of the reasons include gender bias and lack of support for women when choosing a computer science career. Open source software development has been increasingly used by companies seeking the competitive advantages gained by team diversity. This diversification of the characteristics of team members includes, for example, the age of the participants, the level of experience, education and knowledge in the area, and their gender. In open source software projects women are underrepresented and a series of biases are involved in their participation. This paper conducts a systematic literature review with the objective of finding factors that could assist in increasing women’s interest in contributing to open source communities and software development projects. The main contributions of this paper are: (i) identification of factors that cause women’s lack of interest (engagement), (ii) possible solutions to increase the engagement of this public, (iii) to outline the profile of professional women who are participating in open source software projects and software development projects. The main findings of this research reveal that women are underrepresented in software development projects and in open source software projects. They represent less than 10% of the total developers and the main causes of this underrepresentation may be associated with their workplace conditions, which reflect male gender bias.