Guilherme H. Travassos

Guilherme H. Travassos, Sabrina Rocha, Rodrigo Feitosa et al.

The advances and availability of technologies involving Generative Artificial Intelligence (AI) are evolving clearly and explicitly, driving immediate changes in various work activities. Software Engineering (SE) is no exception and stands to benefit from these new technologies, enhancing productivity and quality in its software development processes. However, although the use of Generative AI in SE practices is still in its early stages, considering the lack of conclusive results from ongoing research and the limited technological maturity, we have chosen to incorporate these technologies in the development of a web-based software system to be used in clinical trials by a thoracic diseases research group at our university. For this reason, we decided to share this experience report documenting our development team's learning journey in using Generative AI during the software development process. Project management, requirements specification, design, development, and quality assurance activities form the scope of observation. Although we do not yet have definitive technological evidence to evolve our development process significantly, the results obtained and the suggestions shared here represent valuable insights for software organizations seeking to innovate their development practices to achieve software quality with generative AI.

Santiago Matalonga, Domenico Amalfitano, Andrea Doreste et al.

Context: Context-aware contemporary software systems (CACSS) are mainstream. Furthermore, they present challenges for current engineering practices. These challenges are distinctively present when testing CACSS, as the variation of context deepens the limitations of available software testing practices and technologies. Objective: To understand how the industry deals with the variation of context when testing CACSS. Method: A Rapid Review was commissioned to uncover the necessary evidence to achieve the objectives. Results: Our results show that current research initiatives aim to generate or improve Test Suites that can deal with the variation of context and the sheer volume of test input possibilities. To achieve this, they mostly rely on modelling the systems' dynamic behavior and increasing computing resources to generate test inputs. We found no evidence of research results aiming at managing context variation through the testing lifecycle process. Conclusions: We discuss how the identified solutions are not ready for mainstream adoption. They are all domain-specific, and while the ideas and approaches can be reproduced in different settings, the technologies noon to be re-engineered and tailor to the specific CACSS.

Xavier Franch, Daniel Mendez, Andreas Vogelsang et al.

The relevance of Requirements Engineering (RE) research to practitioners is vital for a long-term dissemination of research results to everyday practice. Some authors have speculated about a mismatch between research and practice in the RE discipline. However, there is not much evidence to support or refute this perception. This paper presents the results of a study aimed at gathering evidence from practitioners about their perception of the relevance of RE research and at understanding the factors that influence that perception. We conducted a questionnaire-based survey of industry practitioners with expertise in RE. The participants rated the perceived relevance of 435 scientific papers presented at five top RE-related conferences. The 153 participants provided a total of 2,164 ratings. The practitioners rated RE research as essential or worthwhile in a majority of cases. However, the percentage of non-positive ratings is still higher than we would like. Among the factors that affect the perception of relevance are the research's links to industry, the research method used, and respondents' roles. The reasons for positive perceptions were primarily related to the relevance of the problem and the soundness of the solution, while the causes for negative perceptions were more varied. The respondents also provided suggestions for future research, including topics researchers have studied for decades, like elicitation or requirement quality criteria.