Daniel Graziotin

Daniel Méndez Fernández, Daniel Graziotin, Stefan Wagner et al.

Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other scientific disciplines, in software engineering, we are still struggling in adapting open science to the particularities of our discipline, rendering progress in our scientific community cumbersome. In this chapter, we reflect upon the essentials in open science for software engineering including what open science is, why we should engage in it, and how we should do it. We particularly draw from our experiences made as conference chairs implementing open science initiatives and as researchers actively engaging in open science to critically discuss challenges and pitfalls, and to address more advanced topics such as how and under which conditions to share preprints, what infrastructure and licence model to cover, or how do it within the limitations of different reviewing models, such as double-blind reviewing. Our hope is to help establishing a common ground and to contribute to make open science a norm also in software engineering.

Verena Käfer, Daniel Graziotin, Ivan Bogicevic et al.

Communication is essential in software engineering. Especially in distributed open-source teams, communication needs to be supported by channels including mailing lists, forums, issue trackers, and chat systems. Yet, we do not have a clear understanding of which communication channels stakeholders in open-source projects use. In this study, we fill the knowledge gap by investigating a statistically representative sample of 400 GitHub projects. We discover the used communication channels by regular expressions on project data. We show that (1) half of the GitHub projects use observable communication channels; (2) GitHub Issues, e-mail addresses, and the modern chat system Gitter are the most common channels; (3) mailing lists are only in place five and have a lower market share than all modern chat systems combined.

Mohammad Kasra Habib, Daniel Graziotin, Stefan Wagner

Requirements elicitation and specification remains a labor-intensive, manual process prone to inconsistencies and gaps, presenting a significant challenge in modern software engineering. Emerging studies underscore the potential of employing large language models (LLMs) for automated requirements generation to support requirements elicitation and specification; however, it remains unclear how to implement this effectively. In this work, we introduce ReqBrain, an Al-assisted tool that employs a fine-tuned LLM to generate authentic and adequate software requirements. Software engineers can engage with ReqBrain through chat-based sessions to automatically generate software requirements and categorize them by type. We curated a high-quality dataset of ISO 29148-compliant requirements and fine-tuned five 7B-parameter LLMs to determine the most effective base model for ReqBrain. The top-performing model, Zephyr-7b-beta, achieved 89.30\% Fl using the BERT score and a FRUGAL score of 91.20 in generating authentic and adequate requirements. Human evaluations further confirmed ReqBrain's effectiveness in generating requirements. Our findings suggest that generative Al, when fine-tuned, has the potential to improve requirements elicitation and specification, paving the way for future extensions into areas such as defect identification, test case generation, and agile user story creation.

Mohammad Kasra Habib, Stefan Wagner, Daniel Graziotin

Requirements Engineering (RE) is the initial step towards building a software system. The success or failure of a software project is firmly tied to this phase, based on communication among stakeholders using natural language. The problem with natural language is that it can easily lead to different understandings if it is not expressed precisely by the stakeholders involved, which results in building a product different from the expected one. Previous work proposed to enhance the quality of the software requirements detecting language errors based on ISO 29148 requirements language criteria. The existing solutions apply classical Natural Language Processing (NLP) to detect them. NLP has some limitations, such as domain dependability which results in poor generalization capability. Therefore, this work aims to improve the previous work by creating a manually labeled dataset and using ensemble learning, Deep Learning (DL), and techniques such as word embeddings and transfer learning to overcome the generalization problem that is tied with classical NLP and improve precision and recall metrics using a manually labeled dataset. The current findings show that the dataset is unbalanced and which class examples should be added more. It is tempting to train algorithms even if the dataset is not considerably representative. Whence, the results show that models are overfitting; in Machine Learning this issue is solved by adding more instances to the dataset, improving label quality, removing noise, and reducing the learning algorithms complexity, which is planned for this research.

Marvin Wyrich, Andreas Preikschat, Daniel Graziotin et al.

Static code analysis tools and integrated development environments present developers with quality-related software metrics, some of which describe the understandability of source code. Software metrics influence overarching strategic decisions that impact the future of companies and the prioritization of everyday software development tasks. Several software metrics, however, lack in validation: we just choose to trust that they reflect what they are supposed to measure. Some of them were even shown to not measure the quality aspects they intend to measure. Yet, they influence us through biases in our cognitive-driven actions. In particular, they might anchor us in our decisions. Whether the anchoring effect exists with software metrics has not been studied yet. We conducted a randomized and double-blind experiment to investigate the extent to which a displayed metric value for source code comprehensibility anchors developers in their subjective rating of source code comprehensibility, whether performance is affected by the anchoring effect when working on comprehension tasks, and which individual characteristics might play a role in the anchoring effect. We found that the displayed value of a comprehensibility metric has a significant and large anchoring effect on a developer's code comprehensibility rating. The effect does not seem to affect the time or correctness when working on comprehension questions related to the code snippets under study. Since the anchoring effect is one of the most robust cognitive biases, and we have limited understanding of the consequences of the demonstrated manipulation of developers by non-validated metrics, we call for an increased awareness of the responsibility in code quality reporting and for corresponding tools to be based on scientific evidence.

Paul Ralph, Nauman bin Ali, Sebastian Baltes et al.

Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e.g. a questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards for research methods commonly used in software engineering. These living documents, which should be continuously revised to reflect evolving consensus around research best practices, will improve research quality and make peer review more effective, reliable, transparent and fair.

Daniel Graziotin, Per Lenberg, Robert Feldt et al.

A meaningful and deep understanding of the human aspects of software engineering (SE) requires psychological constructs to be considered. Psychology theory can facilitate the systematic and sound development as well as the adoption of instruments (e.g., psychological tests, questionnaires) to assess these constructs. In particular, to ensure high quality, the psychometric properties of instruments need evaluation. In this paper, we provide an introduction to psychometric theory for the evaluation of measurement instruments for SE researchers. We present guidelines that enable using existing instruments and developing new ones adequately. We conducted a comprehensive review of the psychology literature framed by the Standards for Educational and Psychological Testing. We detail activities used when operationalizing new psychological constructs, such as item pooling, item review, pilot testing, item analysis, factor analysis, statistical property of items, reliability, validity, and fairness in testing and test bias. We provide an openly available example of a psychometric evaluation based on our guideline. We hope to encourage a culture change in SE research towards the adoption of established methods from psychology. To improve the quality of behavioral research in SE, studies focusing on introducing, validating, and then using psychometric instruments need to be more common.

Simone V. Spiegler, Daniel Graziotin, Christoph Heinecke et al.

A number of qualitative studies find that team leadership is one essential success factor for evolving into a mature agile team. One such qualitative study suggests the 9-Factor Theory of Scrum Master roles, which claims that the Scrum Master performs a set of 9 leadership roles which are transferred to the team over time (Spiegler et al., 2019). We aimed at conducting a quantitative exploration that examines the presence and change of the 9-Factory Theory in relation to team maturity. We conducted an online survey with 67 individuals at the conglomerate Robert Bosch GmbH. Descriptive statistics reveal that the Scrum Master and the agile team score differently on the 9 factors and that the Scrum Master role is most often distributed in teams that had been working between 3 and 5 months in an agile manner. Yet, we also find that the leadership roles predominantly remain with one dedicated Scrum Master. Based on our results we suggest to group the 9-Factor Theory into three clusters: the Scrum Master is rather linked to psychological team factors (1), while the team tends to be linked to rather product-related factors (2). Organizational factors (3) are less often present. Our practical implications suggest an extension of the Scrum Master description. Furthermore, our study lays groundwork for future quantitative testing of leadership in agile teams.

Falko Koetter, Matthias Blohm, Jens Drawehn et al.

Advances in artificial intelligence have renewed interest in conversational agents. Additionally to software developers, today all kinds of employees show interest in new technologies and their possible applications for customers. German insurance companies generally are interested in improving their customer service and digitizing their business processes. In this work we investigate the potential use of conversational agents in insurance companies theoretically by determining which classes of agents exist which are of interest to insurance companies, finding relevant use cases and requirements. We add two practical parts: First we develop a showcase prototype for an exemplary insurance scenario in claim management. Additionally in a second step, we create a prototype focusing on customer service in a chatbot hackathon, fostering innovation in interdisciplinary teams. In this work, we describe the results of both prototypes in detail. We evaluate both chatbots defining criteria for both settings in detail and compare the results and draw conclusions for the maturity of chatbot technology for practical use, describing the opportunities and challenges companies, especially small and medium enterprises, face.

Stefan Wagner, Daniel Méndez Fernández, Michael Felderer et al.

While being an important and often used research method, survey research has been less often discussed on a methodological level in empirical software engineering than other types of research. This chapter compiles a set of important and challenging issues in survey research based on experiences with several large-scale international surveys. The chapter covers theory building, sampling, invitation and follow-up, statistical as well as qualitative analysis of survey data and the usage of psychometrics in software engineering surveys.

Daniel Graziotin, Fabian Fagerholm

Software companies and startups often follow the idea of flourishing happiness among developers. Perks, playground rooms, free breakfast, remote office options, sports facilities near the companies, company retreats, you name it. The rationale is that happy developers should be more productive and also retained. But is it the case that happy software engineers are more productive? Moreover, are perks the way to go to make developers happy? Are developers happy at all? What are the consequences of unhappiness among software engineers? These questions are important to ask both from the perspective of productivity and from the perspective of sustainable software development and well-being in the workplace. Managers, team leaders, as well as team members should be interested in these concerns. This chapter provides an overview of our studies on the happiness of software developers. You will learn why it is important to make software developers happy, how happy they really are, what makes them unhappy, and what is expected regarding happiness and productivity while developing software.

Falko Koetter, Matthias Blohm, Monika Kochanowski et al.

Advances in artificial intelligence have renewed interest in conversational agents. So-called chatbots have reached maturity for industrial applications. German insurance companies are interested in improving their customer service and digitizing their business processes. In this work we investigate the potential use of conversational agents in insurance companies by determining which classes of agents are of interest to insurance companies, finding relevant use cases and requirements, and developing a prototype for an exemplary insurance scenario. Based on this approach, we derive key findings for conversational agent implementation in insurance companies.

Yang Wang, Daniel Graziotin, Stefan Kriso et al.

Context: Safety analysis is a predominant activity in developing safety-critical systems. It is a highly cooperative task among multiple functional departments due to increasingly sophisticated safety-critical systems and close-knit development processes. Communication occurs pervasively. Motivation: Effective communication channels among multiple functional departments influence safety analysis, quality as well as a safe product delivery. However, the use of communication channels during safety analysis is sometimes arbitrary and poses challenges. Objective: Investige the existing communication channels, their usage frequencies, their purposes and challenges during safety analysis in industry.. Method: Multiple case study of experts (survey: 39, interview: 21) in safety-critical companies including software developers, quality engineers and functional safety managers. Direct observations and documentation review were also conducted. Results: Popular communication channels during safety analysis include formal meetings, project coordination tools, documentation and telephone. Email, personal discussion, training, internal communication software and boards are also in use. Training involving safety analysis happens 1-4 times per year, while other aforementioned communication channels happen ranges from 1-4 times per day to 1-4 times per month. We summarise 28 purposes for these communication channels. Communication happens mostly for the purpose of clarifying safety requirements, fixing temporary problems, conflicts and obstacles and sharing safety knowledge. The top challenges are reported. Conclusion: During safety analysis, to use communication channels effectively and avoid challenges, a clear purpose of communication during safety analysis should be established at the beginning. To derive countermeasures of fixing the top 10 challenges are potential next steps.

Per Lenberg, Robert Feldt, Lucas Gren et al.

Researchers are increasingly recognizing the importance of human aspects in software development. Since qualitative methods are used to explore human behavior in-depth, we believe that studies using such methods will become more common. Existing qualitative software engineering guidelines do not cover the full breadth of qualitative methods and the knowledge on how to use them like in social sciences. The purpose of this study was to extend the software engineering community's current body of knowledge regarding available qualitative methods and their quality assurance frameworks, and to provide recommendations and guidelines for their use. With the support of an epistemological argument and a survey of the literature, we suggest that future research would benefit from (1) utilizing a broader set of research methods, (2) more strongly emphasizing reflexivity, and (3) employing qualitative guidelines and quality criteria. We present an overview of three qualitative methods commonly used in social sciences but rarely seen in software engineering research, namely interpretative phenomenological analysis, narrative analysis, and discourse analysis. Furthermore, we discuss the meaning of reflexivity in relation to the software engineering context and suggest means of fostering it. Our paper will help software engineering researchers better select and then guide the application of a broader set of qualitative research methods.

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.

Lutz Prechelt, Daniel Graziotin, Daniel Méndez Fernández

Context: Pre-publication peer review of scientific articles is considered a key element of the research process in software engineering, yet it is often perceived as not to work fully well. Objective: We aim at understanding the perceptions of and attitudes towards peer review of authors and reviewers at one of software engineering's most prestigious venues, the International Conference on Software Engineering (ICSE). Method: We invited 932 ICSE 2014/15/16 authors and reviewers to participate in a survey with 10 closed and 9 open questions. Results: We present a multitude of results, such as: Respondents perceive only one third of all reviews to be good, yet one third as useless or misleading; they propose double-blind or zero-blind reviewing regimes for improvement; they would like to see showable proofs of (good) reviewing work be introduced; attitude change trends are weak. Conclusion: The perception of the current state of software engineering peer review is fairly negative. Also, we found hardly any trend that suggests reviewing will improve by itself over time; the community will have to make explicit efforts. Fortunately, our (mostly senior) respondents appear more open for trying different peer reviewing regimes than we had expected.

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, 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 the positive side of happiness -- positive emotions and moods -- is an attractive and important endeavor. Scholars in industrial and organizational psychology have suggested that also studying the negative side -- 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, and is mainly expressed in terms of development productivity and software quality. In this paper, we attempt to uncover the experienced consequences of unhappiness among software developers. Using qualitative data analysis of the responses given by 181 questionnaire participants, we identified 49 consequences of unhappiness while doing software development. We found detrimental consequences on developers' mental well-being, the software development process, and the produced artifacts. Our classification scheme, available as open data, will spawn 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.

Jan-Peter Ostberg, Daniel Graziotin, Stefan Wagner et al.

Software development is intellectual, based on collaboration, and performed in a highly demanding economic market. As such, it is dominated by time pressure, stress, and emotional trauma. While studies of affect are emerging and rising in software engineering research, stress has yet to find its place in the literature despite that it is highly related to affect. In this paper, we study stress coping with the affect-laden framework of Salutogenesis, which is a validated psychological framework for enhancing mental health through a feeling of coherence. We propose a controlled experiment for testing our hypotheses that a static analysis tool enhanced with the Salutogenesis model will bring 1) a higher number of fixed quality issues, 2) reduced cognitive load, 3) reduction of the overall stress, and 4) positive affect induction effects to developers. The experiment will make use of validated physiological measurements of stress as proxied by cortisol and alpha-amylase levels in saliva samples, a psychometrically validated measurement of mood and affect disposition, and stress inductors such as a cognitive load task. Our hypotheses, if empirically supported, will lead to the creation of environments, methods, and tools that alleviate stress among developers while enhancing affect on the job and task performance.

Daniel Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.

Recent research in software engineering supports the "happy-productive" thesis, and the desire of flourishing happiness among programmers is often expressed by industry practitioners. Recent literature has suggested that a cost-effective way to foster happiness and productivity among workers could be to limit unhappiness of developers due to its negative impact. However, possible negative effects of unhappiness are still largely unknown in the software development context. In this paper, we present the first results from a study exploring the consequences of the unhappy developers. Using qualitative data analysis of the survey responses given by 181 participants, we identified 49 potential consequences of unhappiness while developing software. These results have several implications. While raising the awareness of the role of moods, emotions and feelings in software development, we foresee that our classification scheme will spawn new happiness studies linking causes and effects, and it can act as a guideline for developers and managers to foster happiness at work.

Mika Viking Mäntylä, Daniel Graziotin, Miikka Kuutila

Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. We present a computer-assisted literature review, where we utilize both text mining and qualitative coding, and analyze 6,996 papers from Scopus. We find that the roots of sentiment analysis are in the studies on public opinion analysis at the beginning of 20th century and in the text subjectivity analysis performed by the computational linguistics community in 1990's. However, the outbreak of computer-based sentiment analysis only occurred with the availability of subjective texts on the Web. Consequently, 99% of the papers have been published after 2004. Sentiment analysis papers are scattered to multiple publication venues, and the combined number of papers in the top-15 venues only represent ca. 30% of the papers in total. We present the top-20 cited papers from Google Scholar and Scopus and a taxonomy of research topics. In recent years, sentiment analysis has shifted from analyzing online product reviews to social media texts from Twitter and Facebook. Many topics beyond product reviews like stock markets, elections, disasters, medicine, software engineering and cyberbullying extend the utilization of sentiment analysis

Dirk Pflüger, Miriam Mehl, Julian Valentin et al.

Large-scale simulations play a central role in science and the industry. Several challenges occur when building simulation software, because simulations require complex software developed in a dynamic construction process. That is why simulation software engineering (SSE) is emerging lately as a research focus. The dichotomous trade-off between scalability and efficiency (SE) on the one hand and maintainability and portability (MP) on the other hand is one of the core challenges. We report on the SE/MP trade-off in the context of an ongoing systematic literature review (SLR). After characterizing the issue of the SE/MP trade-off using two examples from our own research, we (1) review the 33 identified articles that assess the trade-off, (2) summarize the proposed solutions for the trade-off, and (3) discuss the findings for SSE and future work. Overall, we see evidence for the SE/MP trade-off and first solution approaches. However, a strong empirical foundation has yet to be established; general quantitative metrics and methods supporting software developers in addressing the trade-off have to be developed. We foresee considerable future work in SSE across scientific communities.

Amantia Pano, Daniel Graziotin, Pekka Abrahamsson

The increasing popularity of JavaScript has led to a variety of JavaScript frameworks that aim to help developers to address programming tasks. However, the number of JavaScript frameworks has risen rapidly to thousands of versions. It is challenging for practitioners to identify the frameworks that best fit their needs and to develop new ones which fit such needs. Furthermore, there is a lack of knowledge regarding what drives developers towards the choice. This paper explores the factors and actors that lead to the choice of a JavaScript framework. We conducted a qualitative interpretive study of semi-structured interviews. We interviewed 18 decision makers regarding the JavaScript framework selection, up to reaching theoretical saturation. Through coding the interview responses, we offer a model of desirable JavaScript framework adoption factors. The factors are grouped into categories that are derived via the Unified Theory of Acceptance and Use of Technology. The factors are performance expectancy (performance, size), effort expectancy (automatization, learnability, complexity, understandability), social influence (competitor analysis, collegial advice, community size, community responsiveness), facilitating conditions (suitability, updates, modularity, isolation, extensibility), and price value. A combination of four actors, which are customer, developer, team, and team leader, leads to the choice. Our model contributes to the body of knowledge related to the adoption of technology by software engineers. As a practical implication, our model is useful for decision makers when evaluating JavaScript frameworks, as well as for developers for producing desirable frameworks.

Mika Mäntylä, Bram Adams, Giuseppe Destefanis et al.

Similar to other industries, the software engineering domain is plagued by psychological diseases such as burnout, which lead developers to lose interest, exhibit lower activity and/or feel powerless. Prevention is essential for such diseases, which in turn requires early identification of symptoms. The emotional dimensions of Valence, Arousal and Dominance (VAD) are able to derive a person's interest (attraction), level of activation and perceived level of control for a particular situation from textual communication, such as emails. As an initial step towards identifying symptoms of productivity loss in software engineering, this paper explores the VAD metrics and their properties on 700,000 Jira issue reports containing over 2,000,000 comments, since issue reports keep track of a developer's progress on addressing bugs or new features. Using a general-purpose lexicon of 14,000 English words with known VAD scores, our results show that issue reports of different type (e.g., Feature Request vs. Bug) have a fair variation of Valence, while increase in issue priority (e.g., from Minor to Critical) typically increases Arousal. Furthermore, we show that as an issue's resolution time increases, so does the arousal of the individual the issue is assigned to. Finally, the resolution of an issue increases valence, especially for the issue Reporter and for quickly addressed issues. The existence of such relations between VAD and issue report activities shows promise that text mining in the future could offer an alternative way for work health assessment surveys.

Daniel Graziotin

For more than thirty years, it has been claimed that a way to improve software developers' productivity and software quality is to focus on people. The underlying assumption seems to be that "happy and satisfied software developers perform better". More specifically, affects-emotions and moods-have an impact on cognitive activities and the working performance of individuals. Development tasks are undertaken heavily through cognitive processes, yet software engineering research (SE) lacks theory on affects and their impact on software development activities. This PhD dissertation supports the advocates of studying the human and social aspects of SE and the psychology of programming. This dissertation aims to theorize on the link between affects and software development performance. A mixed method approach was employed, which comprises studies of the literature in psychology and SE, quantitative experiments, and a qualitative study, for constructing a multifaceted theory of the link between affects and programming performance. The theory explicates the linkage between affects and analytical problem-solving performance of developers, their software development task productivity, and the process behind the linkage. The results are novel in the domains of SE and psychology, and they fill an important lack that had been raised by both previous research and by practitioners. The implications of this PhD lie in setting out the basic building blocks for researching and understanding the affect of software developers, and how it is related to software development performance. Overall, the evidence hints that happy software developers perform better in analytic problem solving, are more productive while developing software, are prone to share their feelings in order to let researchers and managers understand them, and are susceptible to interventions for enhancing their affects on the job.

Ilona Kuzmickaja, Xiaofeng Wang, Daniel Graziotin et al.

It is well acknowledged that innovation is a key success factor in mobile service domain. Having creative ideas is the first critical step in the innovation process. Many studies suggest that customers are a valuable source of creative ideas. However, the literature also shows that adults may be constrained by existing technology frames, which are known to hinder creativity. Instead young children (aged 7-12) are considered digital natives yet are free from existing technology frames. This led us to study them as a potential source for creative mobile service ideas. A set of 41,000 mobile ideas obtained from a research project in 2006 granted us a unique opportunity to study the mobile service ideas from young children. We randomly selected two samples of ideas (N=400 each), one contained the ideas from young children, the other from adults (aged 17-50). These ideas were evaluated by several evaluators using an existing creativity framework. The results show that the mobile service ideas from the young children are significantly more original, transformational, implementable, and relevant than those from the adults. Therefore, this study shows that young children are better sources of novel and quality ideas than adults in the mobile services domain. This study bears significant contributions to the creativity and innovation research. It also indicates a new and valuable source for the companies that seek for creative ideas for innovative products and services.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

Affects---emotions and moods---have an impact on cognitive processing activities and the working performance of individuals. It has been established that software development tasks are undertaken through cognitive processing activities. Therefore, we have proposed to employ psychology theory and measurements in software engineering (SE) research. We have called it "psychoempirical software engineering". However, we found out that existing SE research has often fallen into misconceptions about the affect of developers, lacking in background theory and how to successfully employ psychological measurements in studies. The contribution of this paper is threefold. (1) It highlights the challenges to conduct proper affect-related studies with psychology; (2) it provides a comprehensive literature review in affect theory; and (3) it proposes guidelines for conducting psychoempirical 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.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

Background: software engineering research (SE) lacks theory and methodologies for addressing human aspects in software development. Development tasks are undertaken through cognitive processing activities. Affects (emotions, moods, feelings) have a linkage to cognitive processing activities and the productivity of individuals. SE research needs to incorporate affect measurements to valorize human factors and to enhance management styles. Objective: analyze the affects dimensions of valence, arousal, and dominance of software developers and their real-time correlation with their self-assessed productivity (sPR). Method: repeated measurements design with 8 participants (4 students, 4 professionals), conveniently sampled and studied individually over 90 minutes of programming. The analysis was performed by fitting a linear mixed- effects (LME) model. Results: valence and dominance are positively correlated with the sPR. The model was able to express about 38% of deviance from the sPR. Many lessons were learned when employing psychological measurements in SE and for fitting LME. Conclusion: this article demonstrates the value of applying psychological tests in SE and echoes a call to valorize the human, individualized aspects of software developers. It reports a body of knowledge about affects, their classification, their measurement, and the best practices to perform psychological measurements in SE with LME models.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

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

Xiaofeng Wang, Daniel Graziotin, Juha Rikkilä et al.

Group brainstorming is a well-known idea generation technique, which plays a key role in software development processes. Despite this, the relevant literature has had little to offer in advancing our understanding of the effectiveness of group brainstorming sessions. In this paper we present a research-in-progress on brainstorming while walking, which is a practice built upon the relationship between thinking and walking. The objective is to better understand how to conduct group brainstorming effectively. We compared two brainstorming sessions, one performed during a mountain walk, the other traditionally in a room. Three preliminary findings are obtained: walking can lead to an effective idea generation session; brainstorming while walking can encourage team members to participate in and contribute to the session in an equal manner; and it can help a team to maintain sustainable mental energy. Our study opens up an avenue for future exploration of effective group brainstorming practices.

Daniel Graziotin, Xiaofeng Wang, Pekka Abrahamsson

This article is a contribution towards an understanding of Open Access (OA) publishing. It proposes an analysis framework of 18 core attributes, divided into the areas of Bibliographic information, Activity metrics, Economics, Accessibility, and Predatory issues of OA journals. The framework has been employed in a systematic analysis of 30 OA journals in software engineering (SE) and information systems (IS), which were selected among 386 OA journals in Computer Science from the Directory of OA Journals. An analysis is performed on the sample of the journals, to provide an overview of the current situation of OA journals in the fields of SE and IS. The journals are then compared between-group, according to the presence of a publication fee. A within-group analysis is performed on the journals requesting publication charges to authors, in order to understand what is the value added according to different price ranges. This article offers several contributions. It presents an overview of OA definitions and models. It provides an analysis framework born from the observation of data and the literature. It raises the need to study OA in the fields of SE and IS while offering a first analysis. Finally, it provides recommendations to readers of OA journals. This paper highlights several concerns still threatening OA publishing in the fields of SE and IS. Among them, it is shown that high publication fees are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.

Daniel Graziotin, Pekka Abrahamsson

As opposed to more mature subjects, software engineering lacks general theories to establish its foundations as a discipline. The Essence Theory of software engineering (Essence) has been proposed by the Software Engineering Methods and Theory (SEMAT) initiative. Essence goal is to develop a theoretically sound basis for software engineering practice and its wide adoption. Essence is yet far from reaching academic and industry adoption. Reasons include a struggle to foresee its utilization potential and the lack of tools implementing it. SEMAT Accelerator (SematAcc) is a Web-positioning tool for a software engineering endeavor, which implements the SEMAT's Essence kernel. SematAcc allows using Essence, thus helping to understand it. The tool enables teaching, adopting, and researching Essence in controlled experiments and case studies.

Daniel Graziotin, Pekka Abrahamsson

The field of Web development is entering the HTML5 and CSS3 era and JavaScript is becoming increasingly influential. A large number of JavaScript frameworks have been recently promoted. Practitioners applying the latest technologies need to choose a suitable JavaScript framework (JSF) in order to abstract the frustrating and complicated coding steps and to provide a cross-browser compatibility. Apart from benchmark suites and recommendation from experts, there is little research helping practitioners to select the most suitable JSF to a given situation. The few proposals employ software metrics on the JSF, but practitioners are driven by different concerns when choosing a JSF. As an answer to the critical needs, this paper is a call for action. It proposes a re-search design towards a comparative analysis framework of JSF, which merges researcher needs and practitioner needs.

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.

Daniel Graziotin

Software is primarily developed for people by people and human factors must be studied in all software engineering phases. Creativity is the source to improvise solutions to problems for dominating complex systems such as software development. However, there is a lack of knowledge in what creativity is in software development and what its dynamics are. This study describes the current state of the research plan towards a theory on creativity in software development. More specifically, it (1) states the motivation for studying creativity in software development under a multidisciplinary view; it (2) provides a first review of the literature identifying the shortcomings in the field; it (3) proposes a research design, which includes rarely employed methods in software engineering. To understand creativity in software development will provide a better knowledge of the software construction process and how individuals intellectually contribute to the creation of better, innovative products.