Xiaofeng Wang

Bohan Li, Xin Jin, Jiajun Deng et al.

Camera-based 3D Semantic Occupancy Prediction (SOP) is crucial for understanding complex 3D scenes from limited 2D image observations. Existing SOP methods typically aggregate contextual features to assist the occupancy representation learning, alleviating issues like occlusion or ambiguity. However, these solutions often face misalignment issues wherein the corresponding features at the same position across different frames may have different semantic meanings during the aggregation process, which leads to unreliable contextual fusion results and an unstable representation learning process. To address this problem, we introduce a new Hierarchical context alignment paradigm for a more accurate SOP (Hi-SOP). Hi-SOP first disentangles the geometric and temporal context for separate alignment, which two branches are then composed to enhance the reliability of SOP. This parsing of the visual input into a local-global alignment hierarchy includes: (I) disentangled geometric and temporal separate alignment, within each leverages depth confidence and camera pose as prior for relevant feature matching respectively; (II) global alignment and composition of the transformed geometric and temporal volumes based on semantics consistency. Our method outperforms SOTAs for semantic scene completion on the SemanticKITTI & NuScenes-Occupancy datasets and LiDAR semantic segmentation on the NuScenes dataset.

Zheying Zhang, Tomas Herda, Victoria Pichler et al.

This paper synthesizes the key findings from a full-day XP2025 workshop on "AI and Agile: From Frustration to Success", held in Brugg-Windisch, Switzerland. The workshop brought together over 30 interdisciplinary academic researchers and industry practitioners to tackle the concrete challenges and emerging opportunities at the intersection of Generative Artificial Intelligence (GenAI) and agile software development. Through structured, interactive breakout sessions, participants identified shared pain points like tool fragmentation, governance, data quality, and critical skills gaps in AI literacy and prompt engineering. These issues were further analyzed, revealing underlying causes and cross-cutting concerns. The workshop concluded by collaboratively co-creating a multi-thematic research roadmap, articulating both short-term, implementable actions and visionary, long-term research directions. This cohesive agenda aims to guide future investigation and drive the responsible, human-centered integration of GenAI into agile practices.

Albert Chen, Manas Bundele, Gaurav Ahlawat et al.

The introduction of large language models has brought rapid progress on Text-to-SQL benchmarks, but it is not yet easy to build a working enterprise solution. In this paper, we present insights from building an internal chatbot that enables LinkedIn's product managers, engineers, and operations teams to self-serve data insights from a large, dynamic data lake. Our approach features three components. First, we construct a knowledge graph that captures up-to-date semantics by indexing database metadata, historical query logs, wikis, and code. We apply clustering to identify relevant tables for each team or product area. Second, we build a Text-to-SQL agent that retrieves and ranks context from the knowledge graph, writes a query, and automatically corrects hallucinations and syntax errors. Third, we build an interactive chatbot that supports various user intents, from data discovery to query writing to debugging, and displays responses in rich UI elements to encourage follow-up chats. Our chatbot has over 300 weekly users. Expert review shows that 53% of its responses are correct or close to correct on an internal benchmark set. Through ablation studies, we identify the most important knowledge graph and modeling components, offering a practical path for developing enterprise Text-to-SQL solutions.

Fengyi Li, Kayhan Behdin, Natesh Pillai et al.

Text segmentation based on the semantic meaning of sentences is a fundamental task with broad utility in many downstream applications. In this paper, we propose a graphical model-based unsupervised learning approach, named BP-Seg for efficient text segmentation. Our method not only considers local coherence, capturing the intuition that adjacent sentences are often more related, but also effectively groups sentences that are distant in the text yet semantically similar. This is achieved through belief propagation on the carefully constructed graphical models. Experimental results on both an illustrative example and a dataset with long-form documents demonstrate that our method performs favorably compared to competing approaches.

Anh Nguyen-Duc, Dron Khanna, Des Greer et al.

[Context] The COVID-19 pandemic has had a disruptive impact on how people work and collaborate across all global economic sectors, including the software business. While remote working is not new for software engineers, forced Work-from-home situations to come with both constraints, limitations, and opportunities for individuals, software teams and software companies. As the "new normal" for working might be based on the current state of Work From Home (WFH), it is useful to understand what has happened and learn from that. [Objective] The goal of this study is to gain insights on how their WFH environment impacts software projects and software companies. We are also interested in understanding if the impact differs between software startups and established companies. [Method] We conducted a global-scale, cross-sectional survey during spring and summer 2021. Our results are based on quantitative and qualitative analysis of 297 valid responses. [Results] We observed a mixed perception of the impact of WFH on software project management, resilience, and innovation. Certain patterns on WFH, control and coordination mechanisms and collaborative tools are observed globally. We find that team, agility and leadership are the three most important factors for achieving resilience during the pandemic. Although startups do not perceive the impact of WFH differently, there is a difference between engineers who work in a small team context and those who work in a large team context. [Conclusion] The result suggests a contingency approach in studying and improving WFH practices and environment in the future software industry.

Jorge Melegati, Xiaofeng Wang

Background: Given the social aspects of Software Engineering (SE), in the last twenty years, researchers from the field started using research methods common in social sciences such as case study, ethnography, and grounded theory. More recently, case survey, another imported research method, has seen its increasing use in SE studies. It is based on existing case studies reported in the literature and intends to harness the generalizability of survey and the depth of case study. However, little is known on how case survey has been applied in SE research, let alone guidelines on how to employ it properly. Aims: This article aims to provide a better understanding of how case survey has been applied in Software Engineering research. Method: To address this knowledge gap, we performed a systematic mapping study and analyzed 12 Software Engineering studies that used the case survey method. Results: Our findings show that these studies presented a heterogeneous understanding of the approach ranging from secondary studies to primary inquiries focused on a large number of instances of a research phenomenon. They have not applied the case survey method consistently as defined in the seminal methodological papers. Conclusions: We conclude that a set of clearly defined guidelines are needed on how to use case survey in SE research, to ensure the quality of the studies employing this approach and to provide a set of clearly defined criteria to evaluate such work.

Kai-Kristian Kemell, Anh Nguyen-Duc, Xiaofeng Wang et al.

Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in development methods poses a challenge for software engineering education, creating a gap between education and industry. General theories such as the Essence Theory of Software Engineering can help bridge this gap by presenting software engineering students with higher-level frameworks upon which to build an understanding of software engineering methods and practical project work. In this paper, we study Essence in an educational setting to evaluate its usefulness for software engineering students while also investigating barriers to its adoption in this context. To this end, we observe 102 student teams utilize Essence in practical software engineering projects during a semester long, project-based course.

Dron Khanna, Anh Nguyen-Duc, Xiaofeng Wang

Software startups have emerged as an interesting multiperspective research area. Inspired by Lean Startup, a startup journey can be viewed as a series of experiments that validate a set of business hypotheses an entrepreneurial team make explicitly or inexplicitly about their startup. It is little known about how startups evolve through business hypothesis testing. This study proposes a novel approach to look at the startup evolution as a Minimum Viable Product(MVP) creat- ing process. We identified relationships among business hypotheses and MVPs via ethnography and post-mortem analysis in two software star- tups. We observe that the relationship between hypotheses and MVPs is incomplete and non-linear in these two startups. We also find that entrepreneurs do learn from testing their hypotheses. However, there are hypotheses not tested by MVPs and vice versa, MVPs not related to any business hypothesis. The approach we proposed visualizes the flow of entrepreneurial knowledge across pivots via MVPs.

Henry Edison, Xiaofeng Wang, Ronald Jabangwe et al.

To keep the competitive advantage and adapt to changes in the market and technology, companies need to innovate in an organised, purposeful and systematic manner. However, due to their size and complexity, large companies tend to focus on maintaining their business, which can potentially lower their agility to innovate. This study aims to provide an overview of the current research on innovation initiatives and to identify the challenges of implementing the initiatives in the context of large software companies. The investigation was performed using a systematic mapping approach of published literature on corporate innovation and entrepreneurship. Then it was complemented with interviews with four experts with rich industry experience. Our study results suggest that, there is a lack of high quality empirical studies on innovation initiative in the context of large software companies. A total of 7 studies are conducted in such context, which reported 5 types of initiatives: intrapreneurship, bootlegging, internal venture, spin-off and crowdsourcing. Our study offers three contributions. First, this paper represents the map of existing literature on innovation initiatives inside large companies. The second contribution is to provide an innovation initiative tree. The third contribution is to identify key challenges faced by each initiative in large software companies. At the strategic and tactical levels, there is no difference between large software companies and other companies. At the operational level, large software companies are highly influenced by the advancement of Internet technology. Large software companies use open innovation paradigm as part of their innovation initiatives. We envision a future work is to further empirically evaluate the innovation initiative tree in large software companies, which involves more practitioners from different companies.

Nattakarn Phaphoom, Xiaofeng Wang, Sarah Samuel et al.

In the context of cloud computing, risks associated with underlying technologies, risks involving service models and outsourcing, and enterprise readiness have been recognized as potential barriers for the adoption. To accelerate cloud adoption, the concrete barriers negatively influencing the adoption decision need to be identified. Our study aims at understanding the impact of technical and security-related barriers on the organizational decision to adopt the cloud. We analyzed data collected through a web survey of 352 individuals working for enterprises consisting of decision makers as well as employees from other levels within an organization. The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability. The result from our logistic regression analysis confirms the criticality of the security concern, which results in an up to 26-fold increase in the non-adoption likelihood. Our study underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Carmine Giardino, Xiaofeng Wang, Pekka Abrahamsson

Software startups are newly created companies with little operating history and oriented towards producing cutting-edge products. As their time and resources are extremely scarce, and one failed project can put them out of business, startups need effective practices to face with those unique challenges. However, only few scientific studies attempt to address characteristics of failure, especially during the early- stage. With this study we aim to raise our understanding of the failure of early-stage software startup companies. This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach. The results present how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework. Despite strategies reveal the first need to understand the problem/solution fit, actual executions prioritize the development of the product to launch on the market as quickly as possible to verify product/market fit, neglecting the necessary learning process.

Daniel Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.

The growing literature on affect among software developers mostly reports on the linkage between happiness, software quality, and developer productivity. Understanding happiness and unhappiness in all its components -- positive and negative emotions and moods -- is an attractive and important endeavor. Scholars in industrial and organizational psychology have suggested that understanding happiness and unhappiness could lead to cost-effective ways of enhancing working conditions, job performance, and to limiting the occurrence of psychological disorders. Our comprehension of the consequences of (un)happiness among developers is still too shallow, being mainly expressed in terms of development productivity and software quality. In this paper, we study what happens when developers are happy and unhappy while developing software. Qualitative data analysis of responses given by 317 questionnaire participants identified 42 consequences of unhappiness and 32 of happiness. We found consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts. Our classification scheme, available as open data enables new happiness research opportunities of cause-effect type, and it can act as a guideline for practitioners for identifying damaging effects of unhappiness and for fostering happiness on the job.

Daniel Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.

The happy-productive worker thesis states that happy workers are more productive. Recent research in software engineering supports the thesis, and the ideal of flourishing happiness among software developers is often expressed among industry practitioners. However, the literature suggests that a cost-effective way to foster happiness and productivity among workers could be to limit unhappiness. Psychological disorders such as job burnout and anxiety could also be reduced by limiting the negative experiences of software developers. Simultaneously, a baseline assessment of (un)happiness and knowledge about how developers experience it are missing. In this paper, we broaden the understanding of unhappiness among software developers in terms of (1) the software developer population distribution of (un)happiness, and (2) the causes of unhappiness while developing software. We conducted a large-scale quantitative and qualitative survey, incorporating a psychometrically validated instrument for measuring (un)happiness, with 2220 developers, yielding a rich and balanced sample of 1318 complete responses. Our results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains. We also identified 219 factors representing causes of unhappiness while developing software. Our results, which are available as open data, can act as guidelines for practitioners in management positions and developers in general for fostering happiness on the job. We suggest considering happiness in future studies of both human and technical aspects in software engineering.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

Affects---emotions and moods---have an impact on cognitive activities and the working performance of individuals. Development tasks are undertaken through cognitive processes, yet software engineering research lacks theory on affects and their impact on software development activities. In this paper, we report on an interpretive study aimed at broadening our understanding of the psychology of programming in terms of the experience of affects while programming, and the impact of affects on programming performance. We conducted a qualitative interpretive study based on: face-to-face open-ended interviews, in-field observations, and e-mail exchanges. This enabled us to construct a novel explanatory theory of the impact of affects on development performance. The theory is explicated using an established taxonomy framework. The proposed theory builds upon the concepts of events, affects, attractors, focus, goals, and performance. Theoretical and practical implications are given.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

The study of affects (i.e., emotions, moods) in the workplace has received a lot of attention in the last 15 years. Despite the fact that software development has been shown to be intellectual, creative, and driven by cognitive activities, and that affects have a deep influence on cognitive activities, software engineering research lacks an understanding of the affects of software developers. This note provides (1) common misconceptions of affects when dealing with job satisfaction, motivation, commitment, well-being, and happiness; (2) validated measurement instruments for affect measurement; and (3) our recommendations when measuring the affects of software developers.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

For more than 30 years, it has been claimed that a way to improve software developers' productivity and software quality is to focus on people and to provide incentives to make developers satisfied and happy. This claim has rarely been verified in software engineering research, which faces an additional challenge in comparison to more traditional engineering fields: software development is an intellectual activity and is dominated by often-neglected human aspects. Among the skills required for software development, developers must possess high analytical problem-solving skills and creativity for the software construction process. According to psychology research, affects-emotions and moods-deeply influence the cognitive processing abilities and performance of workers, including creativity and analytical problem solving. Nonetheless, little research has investigated the correlation between the affective states, creativity, and analytical problem-solving performance of programmers. This article echoes the call to employ psychological measurements in software engineering research. We report a study with 42 participants to investigate the relationship between the affective states, creativity, and analytical problem-solving skills of software developers. The results offer support for the claim that happy developers are indeed better problem solvers in terms of their analytical abilities. The following contributions are made by this study: (1) providing a better understanding of the impact of affective states on the creativity and analytical problem-solving capacities of developers, (2) introducing and validating psychological measurements, theories, and concepts of affective states, creativity, and analytical-problem-solving skills in empirical software engineering, and (3) raising the need for studying the human factors of software engineering by employing a multidisciplinary viewpoint.

Stefan Hellweger, Xiaofeng Wang

For more then a decade the term User Experience (UX) has been highly debated and defined in many ways. However, often UX remains as a vague concept and it may be hard to understand the very nature of it. In this paper we aimed at providing a better understanding of this concept. We explored the multi-faceted UX literature, reviewing the current state-of- the-art knowledge and emphasizing the multi-dimensional nature of the concept. Based on the literature review we built a conceptual framework of UX using the elements that are linked to it and reported in different studies. To show the potential use of the framework, we examined the UX delivered by different phone applications on different mobile devices using the elements in the framework. Several interesting insights have been obtained in terms of how the phone applications deliver different UX. Our study opens up a promising line of investigating the contemporary meaning of UX.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

Studies show that software developers' happiness pays off when it comes to productivity.

Xiaofeng Wang, Federico Gobbo, Michael Lane

Time is one of the most important factors dominating agile software development processes in distributed settings. Effective time management helps agile teams to plan and monitor the work to be performed, and create and maintain a fast yet sustainable pace. The Pomodoro Technique is one promising time management technique. Its application and adaptation in Sourcesense Milan Team surfaced various benefits, challenges and implications for distributed agile software development. Lessons learnt from the experiences of Sourcesense Milan Team can be useful for other distributed agile teams to turn time from enemy into an ally.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

For decades now, it has been claimed that a way to improve software developers' productivity is to focus on people. Indeed, while human factors have been recognized in Software Engineering research, few empirical investigations have attempted to verify the claim. Development tasks are undertaken through cognitive processing abilities. Affective states - emotions, moods, and feelings - have an impact on work-related behaviors, cognitive processing activities, and the productivity of individuals. In this paper, we report an empirical study on the impact of affective states on software developers' performance while programming. Two affective states dimensions are positively correlated with self-assessed productivity. We demonstrate the value of applying psychometrics in Software Engineering studies and echo a call to valorize the human, individualized aspects of software developers. We introduce and validate a measurement instrument and a linear mixed-effects model to study the correlation of affective states and the productivity of software developers.