66,130 research outputs found
Misaligned Values in Software Engineering Organizations
The values of software organizations are crucial for achieving high
performance; in particular, agile development approaches emphasize their
importance. Researchers have thus far often assumed that a specific set of
values, compatible with the development methodologies, must be adopted
homogeneously throughout the company. It is not clear, however, to what extent
such assumptions are accurate.
Preliminary findings have highlighted the misalignment of values between
groups as a source of problems when engineers discuss their challenges.
Therefore, in this study, we examine how discrepancies in values between groups
affect software companies' performance.
To meet our objectives, we chose a mixed method research design. First, we
collected qualitative data by interviewing fourteen (\textit{N} = 14) employees
working in four different organizations and processed it using thematic
analysis. We then surveyed seven organizations (\textit{N} = 184). Our analysis
indicated that value misalignment between groups is related to organizational
performance. The aligned companies were more effective, more satisfied, had
higher trust, and fewer conflicts.
Our efforts provide encouraging findings in a critical software engineering
research area. They can help to explain why some companies are more efficient
than others and, thus, point the way to interventions to address organizational
challenges.Comment: accepted for publication in Journal of Software: Evolution and
Proces
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Scientists' political behaviors are not driven by individual-level government benefits.
Is it appropriate for scientists to engage in political advocacy? Some political critics of scientists argue that scientists have become partisan political actors with self-serving financial agendas. However, most scientists strongly reject this view. While social scientists have explored the effects of science politicization on public trust in science, little empirical work directly examines the drivers of scientists' interest in and willingness to engage in political advocacy. Using a natural experiment involving the U.S. National Science Foundation Graduate Research Fellowship (NSF-GRF), we causally estimate for the first time whether scientists who have received federal science funding are more likely to engage in both science-related and non-science-related political behaviors. Comparing otherwise similar individuals who received or did not receive NSF support, we find that scientists' preferences for political advocacy are not shaped by receiving government benefits. Government funding did not impact scientists' support of the 2017 March for Science nor did it shape the likelihood that scientists donated to either Republican or Democratic political groups. Our results offer empirical evidence that scientists' political behaviors are not motivated by self-serving financial agendas. They also highlight the limited capacity of even generous government support programs to increase civic participation by their beneficiaries
On relating functional modeling approaches: abstracting functional models from behavioral models
This paper presents a survey of functional modeling approaches and describes a strategy to establish functional knowledge exchange between them. This survey is focused on a comparison of function meanings and representations. It is argued that functions represented as input-output flow transformations correspond to behaviors in the approaches that characterize functions as intended behaviors. Based on this result a strategy is presented to relate the different meanings of function between the approaches, establishing functional knowledge exchange between them. It is shown that this strategy is able to preserve more functional information than the functional knowledge exchange methodology of Kitamura, Mizoguchi, and co-workers. The strategy proposed here consists of two steps. In step one, operation-on-flow functions are translated into behaviors. In step two, intended behavior functions are derived from behaviors. The two-step strategy and its benefits are demonstrated by relating functional models of a power screwdriver between methodologies
Subject: Human Resource Management
Compiled by Susan LaCette.HumanResourceManagement.pdf: 5527 downloads, before Oct. 1, 2020
Self-tuning routine alarm analysis of vibration signals in steam turbine generators
This paper presents a self-tuning framework for knowledge-based diagnosis of routine alarms in steam turbine generators. The techniques provide a novel basis for initialising and updating time series feature extraction parameters used in the automated decision support of vibration events due to operational transients. The data-driven nature of the algorithms allows for machine specific characteristics of individual turbines to be learned and reasoned about. The paper provides a case study illustrating the routine alarm paradigm and the applicability of systems using such techniques
Qualitative software engineering research -- reflections and guidelines
Researchers are increasingly recognizing the importance of human aspects in
software development and since qualitative methods are used to, in-depth,
explore human behavior, we believe that studies using such techniques will
become more common.
Existing qualitative software engineering guidelines do not cover the full
breadth of qualitative methods and knowledge on using them found in the social
sciences. The aim of this study was thus to extend the software engineering
research community's current body of knowledge regarding available qualitative
methods and provide recommendations and guidelines for their use.
With the support of an epistemological argument and a literature review, 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.Comment: 30 page
Psychological Safety and Norm Clarity in Software Engineering Teams
In the software engineering industry today, companies primarily conduct their
work in teams. To increase organizational productivity, it is thus crucial to
know the factors that affect team effectiveness. Two team-related concepts that
have gained prominence lately are psychological safety and team norms. Still,
few studies exist that explore these in a software engineering context.
Therefore, with the aim of extending the knowledge of these concepts, we
examined if psychological safety and team norm clarity associate positively
with software developers' self-assessed team performance and job satisfaction,
two important elements of effectiveness.
We collected industry survey data from practitioners (N = 217) in 38
development teams working for five different organizations. The result of
multiple linear regression analyses indicates that both psychological safety
and team norm clarity predict team members' self-assessed performance and job
satisfaction. The findings also suggest that clarity of norms is a stronger
(30\% and 71\% stronger, respectively) predictor than psychological safety.
This research highlights the need to examine, in more detail, the
relationship between social norms and software development. The findings of
this study could serve as an empirical baseline for such, future work.Comment: Submitted to CHASE'201
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