Background: Soft skills, such as the ability to communicate effectively and efficiently or work in a team, are important for software engineering practitioners. Understanding which soft skills are necessary for software professionals can assist in staff recruitment, training, and curriculum development. Various previous works have explored soft skills in job adverts in different contexts (i.e. based on what employers ask for). Aims: In this work, we rely on a study performed in New Zealand, and conduct a similar analysis in Cyprus to explore soft skills for the software industry in a different country in a different continent. Method: A manual analysis of 689 job adverts has been used to analyze job adverts from 2023 and 2024. Qualitative analysis and descriptive statistics were mainly employed for analysis purposes. Results: We have found 36 soft skills, whereas between 2023 and 2024 there are slight differences in the number of skills present per job advert. We also encountered differences in soft skills presence based on the job position category and the company size. Conclusion: The results confirm the existing findings concerning the most in demand soft skills, showing that the software industry needs are global. Nevertheless, there are differences in the soft skills popularity. The results can be used for improving job adverts concerning listing soft skills and performing curricula updates.

Bibliometric studies analyze existing research pub-lications and assist in better understanding a research area. Concerning the area of Software Engineering, many works on analysis of research topics and citations exist but additional data have not been analyzed. In this paper, we present a preliminary work toward a funding analysis in top Software Engineering conferences. We have chosen ICSE, ESEC/FSE and ASE and cover all years since the first proceedings of each conference. We have relied our analysis on data collected from Scopus, whereas we have gathered the funding sources using a combination of automated and manual analysis. Our results show that funding comes from a large number of funding agencies but a small number of them is linked with a large number of publications. Our future research agenda includes the consideration of more venues.

Software developers are social creatures: they communicate, collaborate, and promote their work in a variety of channels. Twitter, GitHub, Stack Overflow, and other platforms offer developers opportunities to network and exchange ideas. Researchers analyze content on these sites to learn about trends and topics in software engineering. However, insight mined from the text of Stack Overflow questions or GitHub issues is highly focused on detailed and technical aspects of software development. In this paper, we present a relatively new online community for software developers called DEV. On DEV users write long-form posts about their experiences, preferences, and working life in software, zooming out from specific issues and files to reflect on broader topics. About 50,000 users have posted over 140,000 articles related to software development. In this work, we describe the content of posts on DEV using a topic model, showing that developers discuss a rich variety and mixture of social and technical aspects of software development. We show that developers use DEV to promote themselves and their work: 83% link their profiles to their GitHub profiles and 56% to their Twitter profiles. 14% of users pin specific GitHub repos in their profiles. We argue that DEV is emerging as an important hub for software developers, and a valuable source of insight for researchers to complement data from platforms like GitHub and Stack Overflow.

Free and open source software has gained a lot of momentum in the industry and the research community. Open source licenses determine the rules, under which the open source software can be further used and distributed. Previous works have examined the usage of open source licenses in the framework of specific projects or online social coding platforms, examining developers specific licensing views for specific software. However, the questions practitioners ask about licenses and licensing as captured in Question and Answer websites also constitute an important aspect toward understanding practitioners general licenses and licensing concerns. In this paper, we investigate open source license discussions using data from the Software Engineering, Open Source and Law Stack Exchange sites that contain relevant data. We describe the process used for the data collection and analysis, and discuss the main results that can be useful for developers, educators and license authors. Our results indicate that clarifications about specific licenses and specific license terms are required.

Software repositories and Question & Answer sites constitute promising and ever-increasing sources of information for software analytics and for the identification of the role of the human factor in software engineering. Empirical evidence suggests that studying the human factor in software-related issues is multifaceted. Although analyses on different levels of developer networks have been performed, there is no existing work that moves beyond developer technical skills to take into account other important factors that might affect development work, such as personality and non-technical skills. For this reason, in this work we propose an approach that aims at finding links between badges – a sort of gamification awarded for developer's participation – personality traits, and interpersonal skills from Stack Overflow developers' community. The Generalized Linear Models (GLM) approach is adopted in order to examine the effects of personality traits and interpersonal skills on the non-technical awarded badges. Experimental results from the application of the proposed framework revealed statistically significant effects of both personality traits and interpersonal skills on the award gamification process.

Skills and competences of people participating in online professional networks constitute an ever-increasing new source for data collection and analysis. An important sub-domain of human resources management (HRM) is the recruitment process. Job advertisements and people profiles are main parts of recruitment and since are now available online, they constitute a key factor of a new e-recruitment era. Data mining for erecruitment analysis is important in order to extract a knowledge base for people analytics. Skills and competences are the key variables for people analytics and can be drawn from job advertisements. Leveraging the raw information of online job offers, provides a rich source for people analytics. Detecting the appropriate skills and competences for a job from raw text data and associate them with a job seeker is an increasing challenge. The main objective of this paper is the proposal of a framework aiming to collect online job advertisements from a web source which concerns IT job offers and to extract from the raw text the required skills and competences for specific jobs. The selected professional networking web source is StackOverflow and multivariate statistical data analysis was used to test the correlations between skills and competences in the job offers dataset. The present work falls in a relatively new field of research, concerning the competence mining of peopleware data with special focus on software development.