The rapid evolution of blockchain technology has created a diverse ecosystem of platforms, tools, and applications, and understanding how these technologies are adopted and used in practice is essential for advancing Blockchain-Oriented Software Engineering. This paper presents Web3BlockSet, a curated dataset that enables empirical insights into the blockchain ecosystem through the analysis of Mining Software Repositories on GitHub. We collected 391,596 Issues and Pull Requests from organizations that maintain core blockchain technologies and from community developers who create applications. The dataset offers broad categorization across the blockchain stack, a dual perspective of technology vendors and adopters, and rich metadata that supports diverse analytical approaches.

Abstract Scrum is widely adopted in software project management due to its adaptability and collaborative nature. The recent emergence of Large Language Models (LLMs) has created new opportunities to support knowledge-intensive Scrum practices. However, existing research has largely focused on technical activities such as coding and testing, with limited evidence on the use of LLMs in management-related Scrum activities. In this study, we investigate the use of LLMs in Scrum management activities through a survey of 70 Brazilian professionals. Among them, 49 actively use Scrum, and 33 reported using LLM-based assistants in their Scrum practices. The results indicate a high level of proficiency and frequent use of LLMs, with 85% of respondents reporting intermediate or advanced proficiency and 52% using them daily. LLM use concentrates on exploring Scrum practices, with artifacts and events receiving targeted yet uneven support, whereas broader management tasks appear to be adopted more cautiously. The main benefits include increased productivity (78%) and reduced manual effort (75%). However, several critical risks remain, as respondents report ‘almost correct’ outputs (81%), confidentiality concerns (63%), and hallucinations during use (59%). This work provides one of the first empirical characterizations of LLM use in Scrum management, identifying current practices, quantifying benefits and risks, and outlining directions for responsible adoption and integration in Agile environments.

In recent years, Software Engineering (SE) scholars and practitioners have emphasized the importance of integrating soft skills into SE education. However, teaching and learning soft skills are complex, as they cannot be acquired passively through raw knowledge acquisition. On the other hand, hackathons have attracted increasing attention due to their experiential, collaborative, and intensive nature, which certain tasks could be similar to real-world software development. This paper aims to discuss the idea of hackathons as an educational strategy for shaping SE students' soft skills in practice. Initially, we overview the existing literature on soft skills and hackathons in SE education. Then, we report preliminary empirical evidence from a seven-day hybrid hackathon involving 40 students. We assess how the hackathon experience promoted innovative and creative thinking, collaboration and teamwork, and knowledge application among participants through a structured questionnaire designed to evaluate students' self-awareness. Lastly, our findings and new directions are analyzed through the lens of SelfDetermination Theory (SDT), which offers a psychological lens to understand human behavior. This paper contributes to academia by advocating the potential of hackathons in SE education and proposing concrete plans for future research within SDT. For industry, our discussion has implications around developing soft skills in future SE professionals, thereby enhancing their employability and readiness in the software market.

Search Based Software Engineering (SBSE) seeks to reformulate Software Engineering complex problems as search problems to be, hereafter, optimized through the usage of artificial intelligence techniques. As pointed out by Harman in 2007, in his seminal paper about the current state and future of SBSE, it would be very attractive to have convincing examples of human competitive results in order to champion the field. A landmark effort in this direction was made by Souza and others, in the paper titled “The Human Competitiveness of Search Based Software Engineering”, published at SSBSE’2010, voted by the SBSE community as the most influential paper of the past editions in the 10th anniversary of the SSBSE, in 2018. This paper presents a preliminary systematic mapping study to provide an overview of the current state of human competitiveness of SBSE, carried out via a snowball reading of Souza’s paper. The analyses of the 29 selected papers showed a growing interest in this topic, especially since 2010. Seven of those papers presented relevant experimental results, thus demonstrating the human competitiveness of results produced by SBSE approaches.

Search Based Software Engineering approaches have proven to be feasible and promising in tackling a number of software engineering problems. More recently, researchers have been considering the challenges and opportunities related to involving users’ expertise in the resolution process, among other reasons, to deal with the mistrust or misunderstanding of fully automated optimisation approaches. This paper presents a preliminary study concerned at assessing the users’ subjective perception when his/her preferences are considered in an Interactive SBSE approach. Regarding the evaluation, we conducted a placebo-controlled study with 12 software engineering practitioners by simulating a Next Release Problem scenario. The results indicate that most (68%) of the gain achieved by the interactive approach could be attributed to being the placebo effect, that is, refers strictly to the fact that the user felt part of the optimisation process. In addition, there was an important increased confidence in the results, even in the placebo group.