531,570 research outputs found
Ethical Issues in Empirical Studies of Software Engineering
The popularity of empirical methods in software engineering research is on the rise. Surveys,
experiments, metrics, case studies, and field studies are examples of empirical methods used to
investigate both software engineering processes and products. The increased application of
empirical methods has also brought about an increase in discussions about adapting these
methods to the peculiarities of software engineering. In contrast, the ethical issues raised by
empirical methods have received little, if any, attention in the software engineering literature. This
article is intended to introduce the ethical issues raised by empirical research to the software
engineering research community, and to stimulate discussion of how best to deal with these ethical
issues. Through a review of the ethical codes of several fields that commonly employ humans and
artifacts as research subjects, we have identified major ethical issues relevant to empirical studies
of software engineering. These issues are illustrated with real empirical studies of software
engineering
On Integrating Student Empirical Software Engineering Studies with Research and Teaching Goals
Background: Many empirical software engineering studies use students as subjects and are conducted as part of university courses. Aim: We aim at reporting our experiences with using guidelines for integrating empirical studies with our research and teaching goals. Method: We document our experience from conducting three studies with graduate students in two software architecture courses. Results: Our results show some problems that we faced when following the guidelines and deviations we made from the original guidelines. Conclusions: Based on our results we propose recommendations for empirical software engineering studies that are integrated in university courses.
Model-driven performance evaluation for service engineering
Service engineering and service-oriented architecture as an
integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of
measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised
for the empirical performance evaluation of model-driven developed service systems
Happy software developers solve problems better: psychological measurements in empirical software engineering
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.Comment: 33 pages, 11 figures, published at Peer
How reliable are systematic reviews in empirical software engineering?
BACKGROUND – the systematic review is becoming a more commonly employed research instrument in
empirical software engineering. Before undue reliance is placed on the outcomes of such reviews it would seem useful to consider the robustness of the approach in this particular research context.
OBJECTIVE – the aim of this study is to assess the reliability of systematic reviews as a research instrument. In particular we wish to investigate the consistency of process and the stability of outcomes.
METHOD – we compare the results of two independent reviews under taken with a common research question.
RESULTS – the two reviews find similar answers to the research question, although the means of arriving at those answers vary.
CONCLUSIONS – in addressing a well-bounded research question, groups of researchers with similar domain experience can arrive at the same review outcomes, even though they may do so in different ways.
This provides evidence that, in this context at least, the systematic review is a robust research method
Standards of Validity and the Validity of Standards in Behavioral Software Engineering Research: The Perspective of Psychological Test Theory
Background. There are some publications in software engineering research that
aim at guiding researchers in assessing validity threats to their studies.
Still, many researchers fail to address many aspects of validity that are
essential to quantitative research on human factors. Goal. This paper has the
goal of triggering a change of mindset in what types of studies are the most
valuable to the behavioral software engineering field, and also provide more
details of what construct validity is. Method. The approach is based on
psychological test theory and draws upon methods used in psychology in relation
to construct validity. Results. In this paper, I suggest a different approach
to validity threats than what is commonplace in behavioral software engineering
research. Conclusions. While this paper focuses on behavioral software
engineering, I believe other types of software engineering research might also
benefit from an increased focus on construct validity.Comment: ACM/IEEE International Symposium on Empirical Software Engineering
and Measurement (ESEM), Oulu, Finland, October 11-12, 2018. 4 page
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New ideas and emerging research: evaluating prediction system accuracy
BACKGROUND: Prediction e.g. of project cost is an important concern in software engineering. PROBLEM: Although many empirical validations of software engineering prediction systems have been published, no one approach dominates and sense-making of conflicting empirical results is proving challenging. METHOD: We propose a new approach to evaluating competing prediction systems based upon an unbiased statistic (Standardised Accuracy), analysis of results relative to the baseline technique of guessing and calculation of effect sizes. RESULTS: Two empirical studies are revisited and the published results are shown to be misleading when re-analysed using our new approach. CONCLUSION: Biased statistics such as MMRE are deprecated. By contrast our approach leads to valid results. Such steps will greatly assist in performing future meta-analyses
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