12,407 research outputs found
How Do You Feel, Developer? An Explanatory Theory of the Impact of Affects on Programming Performance
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.Comment: 24 pages, 2 figures. Postprin
Happiness and the productivity of software engineers
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.Comment: 12 pages, 2 figures. To appear in Rethinking Productivity in Software
Engineering, edited by Caitlin Sadowski and Thomas Zimmermann. arXiv admin
note: text overlap with arXiv:1707.0043
Consequences of Unhappiness While Developing Software
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.Comment: 6 pages. To be presented at the Second International Workshop on
Emotion Awareness in Software Engineering, colocated with the 39th
International Conference on Software Engineering (ICSE'17). Extended version
of arXiv:1701.02952v2 [cs.SE
An Exploratory Study of Patient Falls
Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body
Measuring affective states from technical debt: A psychoempirical software engineering experiment
Software engineering is a human activity. Despite this, human aspects are
under-represented in technical debt research, perhaps because they are
challenging to evaluate.
This study's objective was to investigate the relationship between technical
debt and affective states (feelings, emotions, and moods) from software
practitioners. Forty participants (N = 40) from twelve companies took part in a
mixed-methods design, consisting of a repeated-measures (r = 5) experiment (n =
200), a survey employing a questionnaire, and semi-structured interviews.
The statistical analysis shows that different design smells negatively or
positively impact affective states. From the qualitative data, it is clear that
technical debt activates a substantial portion of the emotional spectrum and is
psychologically taxing. Further, the practitioner's reactions to technical debt
appear to fall in different levels of maturity.
We argue that human aspects in technical debt are important factors to
consider, as they may result in, e.g., procrastination, apprehension, and
burnout.Comment: 48 pages, 11 figures, submitted to Empirical Software Engineerin
The Intuitive Appeal of Explainable Machines
Algorithmic decision-making has become synonymous with inexplicable decision-making, but what makes algorithms so difficult to explain? This Article examines what sets machine learning apart from other ways of developing rules for decision-making and the problem these properties pose for explanation. We show that machine learning models can be both inscrutable and nonintuitive and that these are related, but distinct, properties. Calls for explanation have treated these problems as one and the same, but disentangling the two reveals that they demand very different responses. Dealing with inscrutability requires providing a sensible description of the rules; addressing nonintuitiveness requires providing a satisfying explanation for why the rules are what they are. Existing laws like the Fair Credit Reporting Act (FCRA), the Equal Credit Opportunity Act (ECOA), and the General Data Protection Regulation (GDPR), as well as techniques within machine learning, are focused almost entirely on the problem of inscrutability. While such techniques could allow a machine learning system to comply with existing law, doing so may not help if the goal is to assess whether the basis for decision-making is normatively defensible. In most cases, intuition serves as the unacknowledged bridge between a descriptive account and a normative evaluation. But because machine learning is often valued for its ability to uncover statistical relationships that defy intuition, relying on intuition is not a satisfying approach. This Article thus argues for other mechanisms for normative evaluation. To know why the rules are what they are, one must seek explanations of the process behind a model’s development, not just explanations of the model itself
Towards a Theory of Software Development Expertise
Software development includes diverse tasks such as implementing new
features, analyzing requirements, and fixing bugs. Being an expert in those
tasks requires a certain set of skills, knowledge, and experience. Several
studies investigated individual aspects of software development expertise, but
what is missing is a comprehensive theory. We present a first conceptual theory
of software development expertise that is grounded in data from a mixed-methods
survey with 335 software developers and in literature on expertise and expert
performance. Our theory currently focuses on programming, but already provides
valuable insights for researchers, developers, and employers. The theory
describes important properties of software development expertise and which
factors foster or hinder its formation, including how developers' performance
may decline over time. Moreover, our quantitative results show that developers'
expertise self-assessments are context-dependent and that experience is not
necessarily related to expertise.Comment: 14 pages, 5 figures, 26th ACM Joint European Software Engineering
Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE
2018), ACM, 201
Minds Online: The Interface between Web Science, Cognitive Science, and the Philosophy of Mind
Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis they place on forces and factors that reside at the level of agent–world interactions. In particular, by adopting a situated or ecological approach to cognition, we are able to assess the significance of the Web from the perspective of research into embodied, extended, embedded, social and collective cognition. The results of this analysis help to reshape the interdisciplinary configuration of Web Science, expanding its theoretical and empirical remit to include the disciplines of both cognitive science and the philosophy of mind
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