Software engineering involves cognitively demanding activities impacted by individual differences. We investigate how cognitive capability and personality traits are associated with software problem solving accuracy. We assessed cognitive capability using Baddeley's three-minute grammatical reasoning test. Personality was measured using the IPIP-NEO-50 test. Eighty participants (40 software practitioners and 40 software engineering students) completed these two tests with nine interview-style problem solving tasks, comprising six coding-related and three logical-reasoning questions. Our practitioners achieved slightly higher grammatical reasoning accuracy than students, although this difference was not statistically significant. Students achieved higher accuracy on the coding and logical-reasoning tasks. For all, grammatical reasoning accuracy was positively correlated with problem solving accuracy, indicating that individuals with higher reasoning accuracy tended to perform better on applied problem solving tasks. Conscientiousness was the strongest personality-related association, positively correlated with both grammatical reasoning and problem solving accuracy. Openness to experience was also positively correlated with grammatical reasoning and problem solving accuracy. Neuroticism showed a small negative correlation with problem solving accuracy and weak negative correlation with grammatical reasoning accuracy. Practical implications for education and industry include integrating structured reasoning tasks in curricula, and considering the interplay of personality and cognition in recruitment and role allocation.

Neurodivergent women in Software Engineering (SE) encounter distinctive challenges at the intersection of gender bias and neurological differences. To the best of our knowledge, no prior work in SE research has systematically examined this group, despite increasing recognition of neurodiversity in the workplace. Underdiagnosis, masking, and male-centric workplace cultures continue to exacerbate barriers that contribute to stress, burnout, and attrition. In response, we propose a hybrid methodological approach that integrates InclusiveMag's inclusivity framework with the GenderMag walkthrough process, tailored to the context of neurodivergent women in SE. The overarching design unfolds across three stages, scoping through literature review, deriving personas and analytic processes, and applying the method in collaborative workshops. We present a targeted literature review that synthesize challenges into cognitive, social, organizational, structural and career progression challenges neurodivergent women face in SE, including how under/late diagnosis and masking intensify exclusion. These findings lay the groundwork for subsequent stages that will develop and apply inclusive analytic methods to support actionable change.

Humour has long been recognized as a key factor in enhancing creativity, group effectiveness, and employee well-being across various domains. However, its occurrence and impact within software engineering (SE) teams remains under-explored. This paper introduces a comprehensive, literature review-based taxonomy exploring the characterisation and use of humour in SE teams, with the goal of boosting productivity, improving communication, and fostering a positive work environment while emphasising the responsible use of humour to mitigate its potential negative impacts. Drawing from a wide array of studies in psychology, sociology, and organizational behaviour, our proposed framework categorizes humour into distinct theories, styles, models, and scales, offering SE professionals and researchers a structured approach to understanding humour in their work. This study also addresses the unique challenges of applying humour in SE, highlighting its potential benefits while acknowledging the need for further empirical validation in this context. Ultimately, our study aims to pave the way for more cohesive, creative, and psychologically supportive SE environments through the strategic use of humour.

We conducted a workshop on ''Addressing Challenges in Recruiting Participants for Human-Centric Computing Research Studies'' at the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)'24 Conference. In the workshop, we conducted a brainstorming session on ''roadmap development of making participant recruitment easier for human-centric computing studies in both industry and academia''. This article presents 7 stages of participant recruitment and key strategies identified by the authors (workshop participants) during the brainstorming session.

Requirements Engineering (RE)-related activities are critical in developing quality software and one of the most human-dependent processes in software engineering (SE). Hence, identifying the impact of diverse human-related aspects on RE is crucial in the SE context. Our study explores the impact of one of the most influential human aspects, motivation on RE, aiming to deepen understanding and provide practical guidance. By conducting semi-structured interviews with 21 RE-involved practitioners, we developed a theory using socio-technical grounded theory (STGT) that explains the contextual, causal, and intervening conditions influencing motivation in RE-related activities. We identified strategies to enhance motivating situations or mitigate demotivating ones, and the consequences resulting from applying these strategies. Our findings offer actionable insights for software practitioners to manage the influence of motivation on RE and help researchers further investigate its role across various SE contexts in the future.

The COVID-19 pandemic changed the way we live, work and the way we conduct research. With the restrictions of lockdowns and social distancing, various impacts were experienced by many software engineering researchers, especially whose studies depend on human participants. We conducted a mixed methods study to understand the extent of this impact. Through a detailed survey with 89 software engineering researchers working with human participants around the world and a further nine follow-up interviews, we identified the key challenges faced, the adaptations made, and the surprising fringe benefits of conducting research involving human participants during the pandemic. Our findings also revealed that in retrospect, many researchers did not wish to revert to the old ways of conducting human-orienfted research. Based on our analysis and insights, we share recommendations on how to conduct remote studies with human participants effectively in an increasingly hybrid world when face-to-face engagement is not possible or where remote participation is preferred.

Requirements engineering (RE) comprises human-centric activities requiring collaboration between different software development team roles. While prior research highlights the impact of personality on software development, there is limited empirical evidence on how team members' personalities affect RE. To address this gap, we conducted an exploratory case study in an 11-member software development team, observing 28 team meetings, conducting follow-up interviews, and analyzing the personality profiles of team members using the IPIP-NEO 120 assessment tool developed based on the standard five-factor model of personality. Analysis of the observed meetings and follow-up interviews revealed the potential impacts of team members' diverse characteristics on RE-related activities, along with a set of strategies that may be helpful in overcoming challenges due to team members' diverse characteristics. The personality test scores revealed that most team members obtained high scores on personality traits such as agreeableness, conscientiousness, and openness to experience but had average scores for extraversion and neuroticism. By integrating the findings from observations and interviews with team members' personalities, we found potential impacts of certain personality characteristics on RE-related activities. These findings may provide guidance for software teams looking to manage the impact of team members' diverse personalities on RE-related activities and for future researchers investigating these impacts in different contexts.

This paper shares insights from our first-hand experience with key recruitment challenges encountered in software engineering research, focusing on two distinct participant groups: end-users and software practitioners. By conducting a reflective analysis, we emphasise the particular challenges we faced when engaging these groups during empirical study recruitment phases. Significant challenges we faced in recruiting end-users include ensuring authenticity, maintaining engagement, achieving demographic diversity, and addressing privacy concerns. Conversely, we faced different challenges when recruiting software practitioners, including sourcing the right expertise, utilising online recruiting platforms, navigating time constraints, aligning incentives, obtaining a representative sample, and coordinating with remote and distributed teams. By detailing the strategies we employed to address these challenges, this paper contributes practical knowledge to enhance the efficacy and inclusiveness of research practices, ultimately fostering more robust software engineering research outcomes.

Requirements engineering (RE) is an important part of Software Engineering (SE), consisting of various human-centric activities that require the frequent collaboration of a variety of roles. Prior research has shown that personality is one such human aspect that has a huge impact on the success of a software project. However, a limited number of empirical studies exist focusing on the impact of personality on RE activities. The objective of this study is to explore and identify the impact of personality on RE activities, provide a better understanding of these impacts, and provide guidance on how to better handle these impacts in RE. We used a mixed-methods approach, including a personality test-based survey (50 participants) and an in-depth interview study (15 participants) with software practitioners from around the world involved in RE activities. Through personality test analysis, we found a majority of the practitioners have a high score on agreeableness and conscientiousness traits and an average score on extraversion and neuroticism traits. Through analysis of the interviews, we found a range of impacts related to the personality traits of software practitioners, their team members, and external stakeholders. It was found that having extraversion characteristics is considered as plus points compared to agreeableness, conscientiousness and openness to experience characteristics that have been stated as highly important to have when involved in RE activities. These impacts can vary depending on the RE activities, the overall software development process, and the people involved in these activities. Moreover, we found a set of strategies that can be helpful in overcoming some of the challenges associated with diverse personalities when involved in RE activities. Our identified impacts of personality on RE activities and strategies serve to provide guidance to software practitioners on handling such possible personality impacts on RE activities and for researchers to investigate these impacts in greater depth in future.

Requirements Engineering (RE)-related activities require high collaboration between various roles in software engineering (SE), such as requirements engineers, stakeholders, developers, and so on. Their demographics, views, understanding of technologies, working styles, communication and collaboration capabilities make RE highly human-dependent. Identifying how "human aspects"-such as motivation, domain knowledge, communication skills, personality, emotions, culture, and so on-might impact RE-related activities would help us improve RE and SE in general. This study aims at better understanding current industry perspectives on the influence of human aspects on RE-related activities, specifically focusing on motivation and personality, by targeting software practitioners involved in RE-related activities. Our findings indicate that software practitioners consider motivation, domain knowledge, attitude, communication skills and personality as highly important human aspects when involved in RE-related activities. A set of factors were identified as software practitioners' key motivational factors when involved in RE-related activities, along with important personality characteristics to have when involved in RE. We also identified factors that made individuals less effective when involved in RE-related activities and obtained some feedback on measuring individuals' performance when involved in RE. The findings from our study suggest various areas needing more investigation, and we summarise a set of key recommendations for further research.

In this paper, we describe various technologies that are being used in virtual garment fitting and simulation. There, we have focused about the usage of anthropometry in clothing industry and avatar generation of virtual garment fitting. Most commonly used technologies for avatar generation in virtual environment have been discussed in this paper such as generic body model and laser scanning. Moreover, this paper includes the real-time tracking technologies used in virtual garment fitting like markers and depth cameras in various related researches as well as how the virtual cloth generation and simulation carried out in the related researches. Apart from these, virtual clothing methods such as geometrical, physical and hybrid based models were also discussed in this paper. As ease allowance has a major impact on virtual cloth fitting, it is also considered in this paper related to similar researches. Within this paper, all the above mentioned areas were described thoroughly while stating the existing gap of the virtual garment fitting in online marketplaces.

Requirements Engineering (RE) requires the collaboration of various roles in SE, such as requirements engineers, stakeholders and other developers, and it is thus a very highly human dependent process in software engineering (SE). Identifying how “human aspects” – such as personality, motivation, emotions, communication, gender, culture and geographic distribution – might impact on the RE process would assist us in better supporting successful RE. The main objective of this paper is to systematically review primary studies that have investigated the effects of various human aspects on the RE process. We wanted to identify if any critical human aspects have been found, and what might be the relationships between different human aspects impacting the RE process. A systematic literature review (SLR) was conducted and identified 474 initial primary research studies. These were eventually filtered down to 74 relevant, high-quality primary studies. No primary study to date was found to focus on identifying what are the most influential human aspects on the RE process. Among the studied human aspects, the effects of communication have been considered in many studies of RE. Other human aspects such as personality, motivation and gender have mainly been investigated to date in relation to more general SE studies that include RE as one phase. Findings show that studying more than one human aspect together is beneficial, as this reveals relationships between various human aspects and how they together impact the RE process. However, the majority of these studied combinations of human aspects are unique. From 56.8 percent of studies that identified the effects of human aspects on RE, 40.5 percent identified the positive impact, 30.9 percent negative, 26.2 percent identified both impacts whereas 2.3 percent mentioned that there was no impact. This implies that a variety of human aspects positively or negatively affects the RE process and a well-defined theoretical analysis on the effects of different human aspects on RE remains to be defined and practically evaluated. The findings of this SLR help researchers who are investigating the impact of various human aspects on the RE process by identifying well-studied research areas, and highlight new areas that should be focused on in future research.

In this paper, we describe various technologies that are being used in virtual garment fitting and simulation.There, we have focused on the usage of anthropometry in the clothing industry and avatar generation of virtual garment fitting.Most commonly used technologies for avatar generation in virtual environment have been discussed in this paper such as generic body model method and laser scanning technologies.Moreover, this paper includes the usage of real-time tracking technologies used in virtual garment fitting like markers and depth cameras.Apart from these, virtual clothing methods such as geometrical, physical and hybrid-based models were also discussed in this paper.As ease allowance has a major impact on virtual cloth fitting, it is also considered in this paper relating to similar research studies.As the final stage, our proposed design has been explained including the steps of the experiment that has been conducted to generate a twodimensional model of the garment item.Within this paper, all the above-mentioned areas were described thoroughly while stating the existing gap of the virtual garment fitting in online marketplaces and our proposed solution to bridge that gap.

In online apparel market, there is a high return rate mainly due to the size mismatches. As a solution, Virtual garment technologies have been introduced for finding apparels with precise fit whereas most of these technologies are categorized under commercial 3D applications. Therefore, suitability of these 3D applications to check the fitness of selected garment item to a particular user in online marketplace is less due to network latency issues, the need of high user intervention and computational power albeit to the ability of providing highly accurate fitness for a selected garment. Within this paper, a lightweight solution is presented which assists the decision making process of end users in the online market to select perfectly fitted garment by considering human body measurements and garment measurements. The suggested fitting model is consolidated with 2D patterns of human body and finished garments which has the ability of identifying the fitness and manifesting it using seven predefined areas along with user preference and distance ease values. This research has only concerned on generating the fitting model for short sleeve men's shirts due to the limited time frame. The procedure of generating the 2D block pattern from a finished short sleeve shirt has been discerned through an experiment and standard error values which are associated with aforementioned conversion has been recognized using the experiment results. The implemented model was endeavoured on 20 participants and qualitative approaches were used to evaluate the implemented model resulting an accuracy of 81.2%. A survey was conducted to evaluate the visualization of the system output, and received 76% positive responses