Abstract Context: 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. Objective: Our study explores the impact of one of the most influential human aspects, motivation on RE, aiming to deepen understanding and provide practical guidance. Method: 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. Result: We identified strategies to enhance motivating situations or mitigate demotivating ones, and the consequences resulting from applying these strategies. Conclusion: 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.

Abstract Software testing crucial for ensuring software quality, yet developers’ engagement with it varies widely. Identifying the technical, organizational and social factors that lead to differences in engagement is required to remove barriers and utilize enablers for testing. While much research emphasizes the usefulness of software testing approaches and technical solutions, less is known about why developers do (not) test. This study investigates the first-hand experience of developers with software testing. The study illuminates how developers’ opinions about testing and their testing behavior changes. Through analysis of personal evolutions of practice, we explore when and why testing is used. Employing socio-technical grounded theory (STGT), we construct a theory by systematically analyzing data from 19 in-depth, semi-structured interviews with software developers. Allowing interviewees to reflect on how and why they approach software testing, we explore perspectives that are rooted in their contextual experiences. We develop eleven categories of circumstances that act as conditions for the application and adaptation of testing practices and introduce three concepts that we then use to present a theory of emerging testing strategies (ETS) that explains why developers do (not) use testing practices. This study reveals a new perspective on the connection between testing artifacts and collective reflection of practitioners, and it embraces testing as an experience in which human- and social aspects are entangled with organizational and technical circumstances.

The study of human factors, interaction aspects, and societal issues is an important part of human robot interaction (HRI) research. Qualitative research methods and procedures are well suited to these aims. However, there is room for improvement in the quality of their applications and outcomes in HRI research. Researchers often borrow qualitative methods from social sciences, attempt to adapt them, and risk incomplete inquires and poor applications in HRI. This tutorial will introduce socio-technical grounded theory (STGT), a modern version of the social science grounded theory methods customised to study socio-technical domains such as HRI, where human and interaction aspects are closely intertwined with the technical aspects. The tutorial will equip HRI researchers with foundational knowledge and skills to boost their qualitative research applications and share examples and resources to enable them to produce rich findings and robust outcomes.

Effort estimation is a crucial activity in agile software development, where teams collaboratively review, discuss, and estimate the effort required to complete user stories in a product backlog. Current practices in agile effort estimation heavily rely on subjective assessments, leading to inaccuracies and inconsistencies in the estimates. While recent machine learning-based methods show promising accuracy, they cannot explain or justify their estimates and lack the capability to interact with human team members. Our paper fills this significant gap by leveraging the powerful capabilities of Large Language Models (LLMs). We propose a novel LLM-based multi-agent framework for agile estimation that not only can produce estimates, but also can coordinate, communicate and discuss with human developers and other agents to reach a consensus. Evaluation results on a real-life dataset show that our approach outperforms state-of-the-art techniques across all evaluation metrics in the majority of cases. Our human study with software development practitioners also demonstrates an overwhelmingly positive experience in collaborating with our agents in agile effort estimation.

Abstract The rise in the use of AI/ML applications across industries has sparked more discussions about the fairness of AI/ML in recent times. While prior research on the fairness of AI/ML exists, there is a lack of empirical studies focused on understanding perspectives and experiences of AI practitioners in developing a fair AI/ML system. Understanding AI practitioners’ perspectives and experiences on the fairness of AI/ML systems is important because they are directly involved in its development and deployment and their insights can offer valuable real-world perspectives on the challenges associated with ensuring fairness in AI/ML systems. We conducted semi-structured interviews with 22 AI practitioners to investigate their understanding of what a ‘fair AI/ML’ is, the challenges they face in developing a fair AI/ML system, the consequences of developing an unfair AI/ML system, and the strategies they employ to ensure AI/ML system fairness. By exploring AI practitioners’ perspectives and experiences, this study provides actionable insights to enhance AI/ML fairness, which may promote fairer systems, reduce bias, and foster public trust in AI technologies. Additionally, we also identify areas for further investigation and offer recommendations to aid AI practitioners and AI companies in navigating fairness.

Abstract Mixed methods research is often used in software engineering, but researchers outside of the social or human sciences often lack experience when using these designs. This paper provides guiding principles and advice on how to design mixed method research, and to encourage the intentional, rigorous, and innovative application of mixed methods in software engineering. It also presents key properties of core mixed method research designs. Through a number of fictitious but recognizable software engineering research scenarios, we showcase how to choose suitable mixed method designs and consider the inevitable trade-offs any design choice leads to. We describe several antipatterns that illustrate what to avoid in mixed method research, and when mixed method research should be considered over other approaches.

Context: There is an increase in the investment and development of data-intensive (DI) solutions — systems that manage large amounts of data. Without careful management, this growing investment will also grow associated technical debt (TD). Delivery of DI solutions requires a multidisciplinary skill set, but there is limited knowledge about how multidisciplinary teams develop DI systems and manage TD. Objective: This research contributes empirical, practice based insights about multidisciplinary DI team TD management practices. Method: This research was conducted as an exploratory observation case study . We used socio-technical grounded theory (STGT) for data analysis to develop concepts and categories that articulate TD and TDs debt management practices. Results: We identify TD that the DI team deals with, in particular technical data components debt and pipeline debt. We explain how the team manages the TD, assesses TD, what TD treatments they consider and how they implement TD treatments to fit sprint capacity constraints. Conclusion: We align our findings to existing TD and TDM taxonomies, discuss their implications and highlight the need for new implementation patterns and tool support for multidisciplinary DI teams.

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 behavior, 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.

Empathy plays a crucial role in software engineering (SE), influencing collaboration, communication, and decision-making. While prior research has highlighted the importance of empathy in SE, there is limited understanding of how empathy manifests in SE practice, what motivates SE practitioners to demonstrate empathy, and the factors that influence empathy in SE work. Our study explores these aspects through 22 interviews and a large scale survey with 116 software practitioners. Our findings provide insights into the expression of empathy in SE, the drivers behind empathetic practices, SE activities where empathy is perceived as useful or less relevant, and the other factors that influence empathy. In addition, we offer practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

The paper entitled “Qualitative Methods in Empirical Studies of Software Engineering” by Carolyn Seaman was published in TSE in 1999. It has been chosen as one of the most influential papers from the third decade of TSE's 50 years history. In this retrospective, the authors discuss the evolution of the use of qualitative methods in software engineering research, the impact it's had on research and practice, and reflections on what is coming and deserves attention.

We propose an approach to address the shortcomings of current mobile app review systems on platforms such as the Apple App Store and Google Play. Currently, these platforms lack review categorisation and authentication of genuine user feedback, posing significant barriers for app developers and users. We propose an approach combining socio-technical grounded theory (STGT) and advanced natural language processing (NLP) tools such as GPT-4 to analyse user reviews, providing deeper insights into app functionalities, problems, and ultimately, user satisfaction. An interactive UI prototype is presented to demonstrate the use of structured, verified feedback. This includes a novel review submission process with categorisation/tagging and a”verified download” tag to ensure review authenticity. The goal of our approach is to enhance the app ecosystem by assisting developers in prioritising improvements and enabling users to make informed choices, encouraging a more robust and user-centric digital marketplace.

Empirical software engineering researchers are committed to investigating better ways of improving software engineering practice. To do this, gathering data about software professionals’ experiences and perspectives on the researched topic is crucial. However, in the last decade, our experience of recruiting software professionals as potential participants in our studies has met with fluctuating success. Therefore, we had to explore multiple possibilities when recruiting participants. This cost us more effort and time than anticipated. In this paper, we briefly discuss the challenges we faced when recruiting participants for empirical research in software engineering, the solutions we implemented to address these challenges, and a concise list of strategies for garnering the interest of potential participants.

Recruiting participants is a cornerstone of Human-Centric Computing (HCC) research, especially in Digital Health research and development. Effective recruitment ensures that the developed systems reflect the needs and experiences of the intended users. This paper explores recruitment strategies, challenges, and experiences encountered in a project focused on enhancing telehealth through technology co-design, development, and evaluation. By detailing recruitment efforts in the Palliative Care cohort through the think-aloud and simulation study phases, this paper provides insights and practical recommendations for future HCC research in the digital health area.

Abstract 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.

Abstract The term ethics is widely used, explored, and debated in the context of developing Artificial Intelligence (AI) based software systems. In recent years, numerous incidents have raised the profile of ethical issues in AI development and led to public concerns about the proliferation of AI technology in our everyday lives. But what do we know about the views and experiences of those who develop these systems – the AI practitioners? We conducted a grounded theory literature review (GTLR) of 38 primary empirical studies that included AI practitioners’ views on ethics in AI and analysed them to derive five categories: practitioner awareness, perception, need, challenge, and approach. These are underpinned by multiple codes and concepts that we explain with evidence from the included studies. We present a taxonomy of ethics in AI from practitioners’ viewpoints to assist AI practitioners in identifying and understanding the different aspects of AI ethics. The taxonomy provides a landscape view of the key aspects that concern AI practitioners when it comes to ethics in AI. We also share an agenda for future research studies and recommendations for practitioners, managers, and organisations to help in their efforts to better consider and implement ethics in AI.

Research on human aspects within the field of software engineering (SE) has been steadily gaining prominence in recent years. These human aspects have a significant impact on SE due to the inherently interactive and collaborative nature of the discipline. In this paper, we present a systematic literature review (SLR) on human aspects affecting developer-user interactions. The objective of this SLR is to plot the current landscape of primary studies by examining the human aspects that influence developer-user interactions, their implications, interrelationships, and how existing studies address these implications. We conducted this SLR following the guidelines proposed by Kitchenham et al. We performed a comprehensive search in six digital databases, and an exhaustive backward and forward snowballing process. We selected 46 primary studies for data extraction. We identified various human aspects affecting developer-user interactions in SE, assessed their interrelationships, identified their positive impacts and mitigation strategies for negative effects. We present specific recommendations derived from the identified research gaps. Our findings suggest the importance of leveraging positive effects and addressing negative effects in developer-user interactions through the implementation of effective mitigation strategies. These insights may benefit software practitioners for effective user interactions, and the recommendations proposed by this SLR may aid the research community in further human aspects related studies.

The use of Emerging Technologies, such as Artificial Intelligence (AI), Learning Analytics (LA) and Extended Reality (XR) applications, in higher education has proliferated in recent times, as these technologies are considered to have a significant impact on the future of postsecondary teaching and learning. We wanted to find out the emerging technologies used in computing education, its evaluation and effectiveness, and limitations and gaps for future research. We carried out a Systematic Literature Review study on the use of Emerging Technologies in higher education computing education to identify the state of the art in the use of these three groups of technologies for assessment and feedback practices. After systematic search and filtering from a search pool of 3038 studies published between 2016 and 2021, we selected 38 articles for detailed meta-analysis. Our findings reveal that 71% of the reviewed studies are journal articles, 50% studies focus on learning analytics, and the majority of the studies employ quantitative approaches. The results from this systematic review suggest that XR technologies have received least attention to date in computing education (amongst the emerging technologies considered for the review) and there is a lack of frameworks for design, evaluation and use of emerging technologies in higher education. The findings of this review will be beneficial for researchers and educators to obtain an in-depth understanding of the main areas of application of emerging technologies in higher education computing education, an inventory of emerging technology tools used for assessment and feedback, effectiveness indicators, and evaluation approaches that have been used. For evidence-based guidance on future assessment and feedback practices using emerging technologies, we also present a brief research agenda, drawing attention to the need to trial more XR, focus on formative assessment and feedback practices, better understand impact of human-centric issues and take more thoughtful consideration of ethics in the use of emerging technologies in computing education.

Software engineering (SE) requires developers to collaborate with stakeholders, and understanding their emotions and perspectives is often vital. Empathy is a concept characterising a person’s ability to understand and share the feelings of another. However, empathy continues to be an under-researched human aspect in SE. We studied how empathy is practised between developers and end users using a mixed methods case study. We used an empathy test, observations, and interviews to collect data and socio-technical grounded theory and descriptive statistics to analyse data. We identified the nature of awareness required to trigger empathy and enablers of empathy. We discovered barriers to empathy and a set of potential strategies to overcome these barriers. We report insights on emerging relationships and present a set of recommendations and potential future works on empathy and SE for software practitioners and SE researchers.

Background: Research shows that emotional intelligence (EI) should be used alongside cognitive intelligence during requirements change (RC) handling in Software Engineering (SE), especially in agile settings. Objective: We wanted to study the role of EI in-depth during RC handling. Method: We conducted a mixed-methods study (an interview study followed by a survey study) with 124 software practitioners. Findings: We found the causal condition, intervening condition and causes lead to key direct consequences of regulating own emotions, managing relationships, and extended consequences of sustaining productivity, setting and sustaining team goals. We found several strategies of supporting EI during RC handling. Further, we found strong correlations between six strategies and one being aware of own emotions, regulating own emotions, sustaining team productivity, and setting and sustaining team goals. Conclusion: Empathising with others and tracking commitments and decisions as a team are key strategies that have strong correlations between managing emotions, between sustaining team productivity, and between setting and sustaining team goals. To the best of our knowledge, the framework we present in this paper is the first theoretical framework on EI in SE research. We provide recommendations for software practitioners to consider during RC handling.

Ethics in AI has become a debated topic of public and expert discourse in recent years. But what do people who build AI—AI practitioners—have to say about their understanding of AI ethics and the challenges associated with incorporating it into the AI-based systems they develop? Understanding AI practitioners’ views on AI ethics is important as they are the ones closest to the AI systems and can bring about changes and improvements. We conducted a survey aimed at understanding AI practitioners’ awareness of AI ethics and their challenges in incorporating ethics. Based on 100 AI practitioners’ responses, our findings indicate that the majority of AI practitioners had a reasonable familiarity with the concept of AI ethics, primarily due to workplace rules and policies . Privacy protection and security was the ethical principle that the majority of them were aware of. Formal education/training was considered somewhat helpful in preparing practitioners to incorporate AI ethics. The challenges that AI practitioners faced in the development of ethical AI-based systems included (i) general challenges, (ii) technology-related challenges, and (iii) human-related challenges. We also identified areas needing further investigation and provided recommendations to assist AI practitioners and companies in incorporating ethics into AI development.

Advances in Artificial Intelligence (AI), and in particular in Machine Learning (ML), are introducing profound changes to scholarly submissions across publication venues, affecting in particular the contributions that are being submitted to Software Engineering (SE) conferences and journals. In this context, it is not always clear whether manuscripts submitted to SE venues under the umbrella term SE for AI are indeed relevant to SE, in the sense that they explicitly contain contributions to the SE body of knowledge. This leads to recurring discussions on whether certain AI-related submissions are appropriate to SE venues, or should instead be submitted to other journals and conferences, including AI or ML-specific ones. In this editorial, we discuss the kinds of AI-related contributions that are a better fit-and a less good fit-for publication in the IEEE Transactions on Software Engineering.

Abstract Context Responding to change and continuously improving processes, practices, and products are core to agile software development. It is no different in large-scale agile, where multiple software development teams need to respond both to changes in their external environments and to changes within the organization. Objective With this study, we aim to advance knowledge on coordination in large-scale agile by developing a model of the types of organizational changes that influence coordination mechanisms. Method We conducted a longitudinal case study in a growing large-scale agile organization, focusing on how external and internal changes impact coordination over time. We collected our data through 62 days of fieldwork across one and a half years. We conducted 37 interviews, observed 118 meetings at all organizational levels, collected supplementary material such as chat logs and presentations, and analyzed the data using thematic analysis. Results Our findings demonstrate how external events, such as onboarding new clients, and internal events, such as changes in the team organization, influence coordination mechanisms in the large-scale software development program. We find that external and internal change events lead to the introduction of new coordination mechanisms, or the adjustment of existing ones. Further, we find that continuous scaling requires continuous change and adjustment. Finally, we find that having the right mechanisms in place at the right time strengthens resilience and the ability to cope with change in coordination needs in complex large-scale environments. Conclusions Our findings are summarized in an empirically based model that provides a practical approach to analyzing change, aimed at supporting both researchers and practitioners dealing with change in coordination mechanisms in large-scale agile development contexts.

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 large-scale agile software development, many teams work together to achieve overarching project goals. The more teams, the greater the coordination requirements. Despite the growing popularity of large-scale agile, inter-team coordination is challenging to practice and research. We conducted a case study over 1.5 years in a large-scale software development firm to better understand which inter-team coordination mechanisms are used in large-scale agile and how they support inter-team coordination. Based on a thematic analysis of 31 interviews, 113 hours of observations, and supplemental material, we identified 27 inter-team coordination mechanisms. From this, we offer the following contributions. First, we propose a taxonomy of inter-team coordination with three categories: coordination meetings, such as communities of practice, inter-team stand-ups, and retrospectives; coordination roles, such as the program architects and the platform team; and coordination tools and artefacts, such as Slack and JIRA as well as inter-team task boards, product backlogs, and roadmaps. Second, the coordination mechanisms displayed combinations of four key characteristics, technical, organizational, physical, and social (TOPS), which form the basis of the TOPS framework to capture the multifaceted characteristics of coordination mechanisms.Technicalrelates to the software product and/or technical tools supporting software development.Organizationalpertains to the structural aspects of the organization.Physicalrefers to tangible or spatial characteristics.Socialcaptures interpersonal and community-based characteristics. Finally, the taxonomy and the TOPS framework provide a knowledge base and a structured approach for researchers to study as well as for software practitioners to understand and improve inter-team coordination in large-scale agile.

The predicted increase in demand for data-intensive solution development is driving the need for software, data, and domain experts to effectively collaborate in multi-disciplinary data-intensive software teams (MDSTs). We conducted a socio-technical grounded theory study through interviews with 24 practitioners in MDSTs to better understand the challenges these teams face when delivering data-intensive software solutions. The interviews provided perspectives across different types of roles including domain, data and software experts, and covered different organisational levels from team members, team managers to executive leaders. We found that the key concern for these teams is dealing with data-related challenges. In this article, we present a theory of dealing with data challenges that explains thechallengesfaced by MDSTs including gaining access to data, aligning data, understanding data, and resolving data quality issues; thecontextin andconditionunder which these challenges occur, thecausesthat lead to the challenges, and the relatedconsequencessuch as having to conduct remediation activities, inability to achieve expected outcomes and lack of trust in the delivered solutions. We also identifiedcontingenciesor strategies applied to address the challenges including high-level strategic approaches such as implementing data governance, implementing new tools and techniques such as data quality visualisation and monitoring tools, as well as building stronger teams by focusing on people dynamics, communication skill development and cross-skilling. Our findings have direct implications for practitioners and researchers to better understand the landscape of data challenges and how to deal with them.

Background:Requirements Changes (RCs) – the additions/modifications/deletions of functional/non-functional requirements in software products – are challenging for software practitioners to handle. Handling some changes may significantly impact the emotions of the practitioners.Objective:We wanted to know the key challenges that make RC handling difficult, how these impact the emotions of software practitioners, what influences their RC handling, and how RC handling can be made less emotionally challenging.Method:We followed a mixed-methods approach. We conducted two survey studies, with 40 participants and 201 participants respectively. The presentation of key quantitative data was followed by descriptive statistical analysis, and the qualitative data was analysed using Strauss–Corbinian Grounded Theory, and Socio–Technical Grounded Theory analysis techniques.Findings:We found (1) several key factors that make RC handling an emotional challenge, (2) varying emotions that practitioners feel when it is challenging to handle RCs, (3) how stakeholders, including practitioners themselves, peers, managers and customers, influence the RC handling and how practitioners feel due to the stakeholder influence, and (4) practices that can be used to better handle RCs.Conclusion:Some challenges are technical and some are social which also belong to aspects of agile practice, emotional intelligence, and likely belong to cognitive intelligence. Therefore, to better handle RCs with positive emotions in socio–technical environments, agility, emotional intelligence, and cognitive intelligence need to work in synergy with each other.

Background:A preliminary study we conducted showed that software practitioners respond to requirements changes (RCs) with different emotions, and that their emotions vary at stages of the RC handling life cycle, such asreceiving, developing,anddeliveringRCs. Furthermore, such developer emotions have direct linkages to cognition, productivity, and decision making. Therefore, it is important to gain a comprehensive understanding the role of emotions in a critical scenarios like handling RCs.Objective:We wanted to study how practitionersemotionallyrespond to RCs.Method:We conducted a world-wide survey with the participation of 201 software practitioners. In our survey, we used the Job-related Affective Well-being Scale (JAWS) and open-ended questions to capture participants’ emotions when handling RCs in their work and query about the different circumstances when they feel these emotions. We used a combined approach of statistical analysis, JAWS, and Socio-Technical Grounded Theory (STGT)for Data Analysisto analyse our survey data.Findings:We identified (1) emotional responses to RCs, i.e., the most commonemotionsfelt by practitioners when handling RCs; (2) differentstimuli– such as the RC, the practitioner, team, manager, customer – that trigger these emotions through their own different characteristics; (3)emotion dynamics, i.e., the changes in emotions during the RC handling life cycle; (4)RC stageswhere particular emotions are triggered; and (5)time related aspectsthat regulate the emotion dynamics.Conclusion:Practitioners are not pleased with receiving RCs all the time. Last minute RCs introduced closer to a deadline especially violate emotional well-being of practitioners. We present some practical recommendations for practitioners to follow, including a dual-purpose emotion-centric decision guide to help decide when to introduce or accept an RC, and some future key research directions.

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.

Grounded Theory (GT), a sociological research method designed to study social phenomena, is increasingly being used to investigate the human and social aspects of software engineering (SE). However, being written by and for sociologists, GT is often challenging for a majority of SE researchers to understand and apply. Additionally, SE researchers attempting ad hoc adaptations of traditional GT guidelines for modern socio-technical (ST) contexts often struggle in the absence of clear and relevant guidelines to do so, resulting in poor quality studies. To overcome these research community challenges and leverage modern research opportunities, this paper presentsSocio-Technical Grounded Theory(STGT) designed to ease application and achieve quality outcomes. It defines what exactly is meant by an ST research context and presents the STGT guidelines that expand GT's philosophical foundations, provide increased clarity and flexibility in its methodological steps and procedures, define possible scope and contexts of application, encourage frequent reporting of a variety of interim, preliminary, and mature outcomes, and introduce nuanced evaluation guidelines for different outcomes. It is hoped that the SE research community and related ST disciplines such as computer science, data science, artificial intelligence, information systems, human computer/robot/AI interaction, human-centered emerging technologies (and increasingly other disciplines being transformed by rapid digitalisation and AI-based augmentation), will benefit from applying STGT to conduct quality research studies and systematically produce rich findings and mature theories with confidence.

The growing diffusion of software in society and its influence on people demands from its creators that their work carefully considers human values such as transparency, social responsibility, and equality. But how do software practitioners address human values in software engineering practice? We interviewed 31 software practitioners from two organizations, each having a strong values framework, with the aim to understand: (a) practitioners’ perceptions of human values and their role in software engineering; (b) practices that practitioners use to address human values in software; and (c) challenges they face during this process. We report our findings from two contrasting case organizations on how practitioners “engineer” values in their unique organizational settings. We found evidence that organizational culture significantly contributes to how values are addressed in software. We summarize recommendations from the practitioners to support proactive engineering of values-conscious software.

Agile methods are predominantly focused on delivering business values. But can Agile methods be adapted to effectively address and deliver human values such as social justice, privacy, and sustainability in the software they produce Human values are what an individual or a society considers important in life. Ignoring these human values in software can pose difficulties or risks for all stakeholders (e.g., user dissatisfaction, reputation damage, financial loss). To answer this question, we selected the Scaled AgileFramework (SAFe), one of the most commonly used Agile methods in the industry, and conducted a qualitative case study to identify possible intervention points within SAFe that are the most natural to address and integrate human values in software. We present five high-level empirically-justified sets of interventions in SAFe: artefacts, roles, ceremonies, practices, and culture. We elaborate how some currentAgile artefacts (e.g., user story), roles (e.g., product owner), ceremonies (e.g., stand-up meeting), and practices (e.g., business-facing testing) in SAFe can be modified to support the inclusion of human values in software. Further, our study suggests new and exclusive values-based artefacts (e.g., legislative requirement), ceremonies (e.g., values conversation), roles (e.g., values champion), and cultural practices (e.g., induction and hiring) to be introduced in SAFe for this purpose. Guided by our findings, we argue that existingAgile methods can account for human values in software delivery with some evolutionary adaptations.

Background:Originally, developers aimed to identify most software requirements upfront in software development projects. However, agile methods explicitly encourage software requirements to be changed throughout development, i.e., many Requirements Changes (RCs) occur.Objective:The objective of this study is to better understand RCs and produce a taxonomy of RCs in agile contexts.Method:We ran a mixed-methods approach comprising a series of studies: an interview-based study (10 participants from New Zealand and Australia), a focused literature review, and an in-depth survey (40 participants world-wide).Results:Key characteristics of RCs in agile we found relate to differenttypesandforms, agile RCs have multiplereasonsandsources, they are brought by differentcarriers, and their emergence in agile is via a variety ofevents.Summary:The presented taxonomy provides a guide for software practitioners to use to help manage RC-related issues in agile contexts.

Scrum, the most popular agile method and project management framework, is widely reported to be used, adapted, misused, and abused in practice. However, not much is known about how Scrum actually works in practice, and critically, where, when, how and why it diverges from Scrum by the book. Through a Grounded Theory study involving semi-structured interviews of 45 participants from 30 companies and observations of five teams, we present our findings on how Scrum works in practice as compared to how it is presented in its formative books. We identify significant variations in these practices such as work breakdown, estimation, prioritization, assignment, the associated roles and artefacts, and discuss the underlying rationales driving the variations. Critically, we claim that not all variations are process misuse/abuse and propose a nuanced classification approach to understanding variations asstandard, necessary, contextual,andclear deviationsfor successful Scrum use and adaptation.

Self-assignment, where software developers choose their own tasks, is a common practice in agile teams. However, it is not known why developers select certain tasks. It is important for managers to be aware of these reasons to ensure sustainable self-assignment practices. We investigated developers’ preferences while they are choosing tasks for themselves. We collected data from 42 participants working in 25 different software companies. We applied Grounded Theory procedures to study and analyse factors for self-assigning tasks, which we grouped into three categories:task-based,developer-based, andopinion-based. We found that developers have individual preferences and not all factors are important to every developer. Managers share some common and varying perspectives around the identified factors. Most managers want developers to give higher priority to certain factors. Developers often need to balance between task priority and their own individual preferences, and managers facilitate this through a variety of strategies. Morerisk-aversemanagers encourage expertise-based self-assignment to ensure tasks are completed quickly. Managers who arerisk-balancingencourage developers to choose tasks that provide learning opportunities only when there is little risk of delays or reduced quality. Finally,growth-seekingmanagers regularly encourage team members to pick tasks outside their comfort zone to encourage growth opportunities. Our findings will help managers to understand what developers consider when self-assigning tasks and help them empower their teams to practice self-assignment in a sustainable manner.

Abstract Self-assignment, a self-directed method of task allocation in which teams and individuals assign and choose work for themselves, is considered one of the hallmark practices of empowered, self-organizing agile teams. Despite all the benefits it promises, agile software teams do not practice it as regularly as other agile practices such as iteration planning and daily stand-ups, indicating that it is likely not an easy and straighforward practice. There has been very little empirical research on self-assignment. This Grounded Theory study explores how self-assignment works in agile projects. We collected data through interviews with 42 participants representing 28 agile teams from 23 software companies and supplemented these interviews with observations. Based on rigorous application of Grounded Theory analysis procedures such as open, axial, and selective coding, we present a comprehensive grounded theory of making self-assignment work that explains the (a) context and (b) causal conditions that give rise to the need for self-assignment, (c) a set of facilitating conditions that mediate how self-assignment may be enabled, (d) a set of constraining conditions that mediate how self-assignment may be constrained and which are overcome by a set of (e) strategies applied by agile teams, which in turn result in (f) a set of consequences, all in an attempt to make the central phenomenon, self-assignment, work. The findings of this study will help agile practitioners and companies understand different aspects of self-assignment and practice it with confidence regularly as a valuable practice. Additionally, it will help teams already practicing self-assignment to apply strategies to overcome the challenges they face on an everyday basis.

Abstract Context As a novel coronavirus swept the world in early 2020, thousands of software developers began working from home. Many did so on short notice, under difficult and stressful conditions. Objective This study investigates the effects of the pandemic on developers’ wellbeing and productivity. Method A questionnaire survey was created mainly from existing, validated scales and translated into 12 languages. The data was analyzed using non-parametric inferential statistics and structural equation modeling. Results The questionnaire received 2225 usable responses from 53 countries. Factor analysis supported the validity of the scales and the structural model achieved a good fit (CFI = 0.961, RMSEA = 0.051, SRMR = 0.067). Confirmatory results include: (1) the pandemic has had a negative effect on developers’ wellbeing and productivity; (2) productivity and wellbeing are closely related; (3) disaster preparedness, fear related to the pandemic and home office ergonomics all affect wellbeing or productivity. Exploratory analysis suggests that: (1) women, parents and people with disabilities may be disproportionately affected; (2) different people need different kinds of support. Conclusions To improve employee productivity, software companies should focus on maximizing employee wellbeing and improving the ergonomics of employees’ home offices. Women, parents and disabled persons may require extra support.

Achieving effective inter-team coordination is one of the most pressing challenges in large-scale software development. Hybrid approaches of traditional and agile development promise combining the overview and predictability of long-term planning on an inter-team level with the flexibility and adaptability of agile development on a team level. It is currently unclear, however, why such hybrids often fail. Our case study within a large software development unit of 13 teams at a global enterprise software company explores how and why a combination of traditional planning on an inter-team level and agile development on a team level can result in ineffective coordination. Based on a variety of data, including interviews with scrum masters, product owners, architects and senior management, and using Grounded Theory data analysis procedures, we identify a lack of dependency awareness across development teams as a key explanation of ineffective coordination. Our findings show how a lack of dependency awareness emerges from misaligned planning activities of specification, prioritization, estimation and allocation between agile team and traditional inter-team levels and ultimately prevents effective coordination. Knowing about these issues, large-scale hybrid projects in similar contexts can try to better align their planning activities across levels to improve dependency awareness and in turn achieve more effective coordination.

Agile adoption is typically understood as a one-off organizational process involving a staged selection of agile development practices. This view of agility fails to explain the differences in the pace and effectiveness of individual teams transitioning to agile development. Based on a Grounded Theory study of 31 agile practitioners drawn from 18 teams across five countries, we present a grounded theory of becoming agile as a network of on-going transitions across five dimensions: software development practices, team practices, management approach, reflective practices, and culture. The unique position of a software team through this network, and their pace of progress along the five dimensions, explains why individual agile teams present distinct manifestations of agility and unique transition experiences. The theory expands the current understanding of agility as a holistic and complex network of on-going multidimensional transitions, and will help software teams, their managers, and organizations better navigate their individual agile journeys.

One of the most efficient ways of reducing household energy consumption is through an online feedback system, which helps users in reducing their household energy. There are several research and commercial products available, yet over-consumption issues are still prevalent. An important factor fueling these issues is rendering too many features or information in the online feedback system, which results in a decrease in use of those applications over time. This study aims to develop a user-friendly system with a minimal set of features that would help the residential users achieve maximum savings. The energy control system (ECoS) consists of three major features, i.e., (a) visualization of energy, (b) recommendation of energy saving decision to users, (c) remote appliance control through recommendations, with thirteen sub-features. Based on an analysis of energy savings and user preferences, we identified the top seven sub-features suitable to be in ECoS to help users save energy. In addition, this article also provides recommendations to energy providers on the list of features that they should include in their online application to help their users save a significant amount of energy.

A retrospective is a standard agile meeting practice designed for agile software teams to reflect and tune their process. Despite its integral importance, we know little about what aspects are focused upon during retrospectives and how reflection occurs in this practice. We conducted Case Study research involving data collected from interviews of sixteen software practitioners from four agile teams and observations of their retrospective meetings. We found that the important aspects focused on during the retrospective meeting include identifying and discussing obstacles, discussing feelings, analyzing previous action points, identifying background reasons, identifying future action points and generating a plan. Reflection occurs when the agile teams embody these aspects within three levels of reflection: reporting and responding, relating and reasoning, and reconstructing. Critically, we show that agile teams may not achieve all levels of reflection simply by performing retrospective meetings. One of the key contributions of our work is to present a reflection framework for agile retrospective meetings that explains and embeds three levels of reflection within the five steps of a standard agile retrospective. Agile teams can use this framework to achieve better focus and higher levels of reflection in their retrospective meetings.

Task allocation is considered an important activity in software project management. However, the process of allocating tasks in agile software development teams has not received much attention in empirical research. Through a pilot study involving mixed open-ended and closed-ended interviews questions with 11 agile software practitioners working within a software development organization in India, we explain the process of task allocation as including three different mechanisms of workflow across teams: team-independent, team-dependent, and hybrid workflow; and five types of task allocation strategies: manager-driven, team-driven, individual-driven, manager-assisted and team-assisted. Knowing these workflow mechanisms and task allocation strategies will help software teams and project managers make more effective decisions around workflow and task allocation.

The project manager has been a ubiquitous feature of traditional software development projects. However, agile software development (ASD) methods which emphasize selforganizing teams and rapid response to change have done away with the project manager's title. New job titles such as the scrum master and product owner have been introduced instead. It is unclear as to what extent the "project manager" is still encountered in the agile software industry. An online survey was posted out to agile special interest groups on popular social media platforms to discover the frequency of the job title "project manager" in agile projects. Analysis of the 97 responses from 31 countries around the world revealed that: a) the title of project manager is still widely used (67%); b) there is a correlation between the team size and presence of project manager such that there is a higher probability the project manager will be present in teams of 5-10 members and those over 25 members; and c) there is an inverse correlation between the co-location of a team and presence of project manager. Further research is needed to better understand why the project manager continues to be present on ASD projects and how their role may have changed.

Software is created by people for people working in a range of environments and under various conditions. Understanding the cooperative and human aspects of software development is crucial in order to comprehend how methods and tools are used, and thereby improve the creation and maintenance of software. Both researchers and practitioners have recognized the need to investigate these aspects, but the results of such investigations are dispersed in different conferences and communities. The goal of this workshop is to provide a forum for discussing high quality research on human and cooperative aspects of software engineering. We aim to provide both a meeting place for the community and the possibility for researchers interested in joining the field to present and discuss their work in progress and to get an overview over the field.

Self-organizing teams have been recognized and studied in various forms-as autonomous groups in socio-technical systems, enablers of organizational theories, agents of knowledge management, and as examples of complex-adaptive systems. Over the last decade, self-organizing teams have taken center stage in software engineering when they were incorporated as a hallmark of Agile methods. Despite the long and rich history of self-organizing teams and their recent popularity with Agile methods, there has been little research on the topic within software wngineering. Particularly, there is a dearth of research on how Agile teams organize themselves in practice. Through a Grounded Theory research involving 58 Agile practitioners from 23 software organizations in New Zealand and India over a period of four years, we identified informal, implicit, transient, and spontaneous roles that make Agile teams self-organizing. These roles-Mentor, Coordinator, Translator, Champion, Promoter, and Terminator-are focused toward providing initial guidance and encouraging continued adherence to Agile methods, effectively managing customer expectations and coordinating customer collaboration, securing and sustaining senior management support, and identifying and removing team members threatening the self-organizing ability of the team. Understanding these roles will help software development teams and their managers better comprehend and execute their roles and responsibilities as a self-organizing team.

Software is created by people for people working in varied environments, under various conditions. Thus understanding cooperative and human aspects of software development is crucial to comprehend how methods and tools are used, and thereby improve the creation and maintenance of software. Over the years, both researchers and practitioners have recognized the need to study and understand these aspects. Despite recognizing this, researchers in cooperative and human aspects have no clear place to meet and are dispersed in different research conferences and areas. The goal of this workshop is to provide a forum for discussing high quality research on human and cooperative aspects of software engineering. We aim at providing both a meeting place for the growing community and the possibility for researchers interested in joining the field to present their work in progress and get an overview over the field.

Grounded Theory (GT) is gaining popularity as research method in Software Engineering; however, it is still not widely understood. We present some patterns based on the use of GT to study Software Engineering contexts including our own experiences of applying classic GT in an attempt to make it more accessible for Software Engineering researchers (aka 'geeks').

Agile teams are described as "self-organizing". How these teams actually organize themselves in practice, however, is not well understood. Through Grounded Theory research involving 24 Agile practitioners across 14 software organizations in New Zealand and India, we identified six informal roles that team members adopt in order to help their teams self-organize. These roles --- Mentor, Co-ordinator, Translator, Champion, Promoter, and Terminator --- help teams learn Agile practices, liaise with customers, maintain management support, and remove ineffective team members. Understanding these roles will help software teams become self-organizing, and should guide Agile coaches in working with Agile teams.

Evangelists for Agile methods strongly encourage all projects to follow every practice of their chosen method. Based on a Grounded Theory study involving 40 participants at 16 organizations, and corroborated by 4 independent case studies, we argue that development methods and practices must be adapted to fit their contexts. Understanding Agility in context will help development teams, their managers, and Agile coaches to adapt development processes to fit their projects' contexts.

When researchers extend a conventional communication application to mobile devices, the communication becomes ubiquitous. We recently examined a mobile communication application from a usability perspective. We found that despite the potentially high utility of the mobile communication application, it had usability issues that required user interface redesign. This paper is an alert for mobile and ubiquitous multimedia designers that they must not ignore usability considerations when designing software and hardware solutions for ubiquitous mobility.