75,500 research outputs found
A literature review of expert problem solving using analogy
We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction
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Potential applications of simulation modelling techniques in healthcare: lessons learned from aerospace and military
The Aerospace and Military areas are to do with complex missions and situations. Modelling and Simulation (M&S) has been applied in many areas of defence ranging from space sciences, satellite engineering to multi-warfare (air warfare, undersea warfare), air & missile defence, acquisition, tactical military trainings & exercises, national security analysis and strategic decision making & planning, etc. The application of simulation modelling techniques in healthcare would improve the provision of healthcare services; however, their application has been much relatively feeble in the healthcare sector as compared to the defence sector. This paper presents results from a systematic literature survey on applications of modelling simulation techniques in the Aerospace & Military. The knowledge gained or lessons learned from the survey were finally used to analyze the potential applications of the simulation modelling techniques to the healthcare sector. Results show that in the defence sector, Distributed Simulation has now become a widely adopted technique. However, System Dynamics (SD) and Discrete Event Simulation (DSE) have also gained relative attention. From this survey it becomes clear that various simulation modelling techniques are useful for specific purposes and have potential applications in the healthcare sector
Naming the Pain in Requirements Engineering: A Design for a Global Family of Surveys and First Results from Germany
For many years, we have observed industry struggling in defining a high
quality requirements engineering (RE) and researchers trying to understand
industrial expectations and problems. Although we are investigating the
discipline with a plethora of empirical studies, they still do not allow for
empirical generalisations. To lay an empirical and externally valid foundation
about the state of the practice in RE, we aim at a series of open and
reproducible surveys that allow us to steer future research in a problem-driven
manner. We designed a globally distributed family of surveys in joint
collaborations with different researchers and completed the first run in
Germany. The instrument is based on a theory in the form of a set of hypotheses
inferred from our experiences and available studies. We test each hypothesis in
our theory and identify further candidates to extend the theory by correlation
and Grounded Theory analysis. In this article, we report on the design of the
family of surveys, its underlying theory, and the full results obtained from
Germany with participants from 58 companies. The results reveal, for example, a
tendency to improve RE via internally defined qualitative methods rather than
relying on normative approaches like CMMI. We also discovered various RE
problems that are statistically significant in practice. For instance, we could
corroborate communication flaws or moving targets as problems in practice. Our
results are not yet fully representative but already give first insights into
current practices and problems in RE, and they allow us to draw lessons learnt
for future replications. Our results obtained from this first run in Germany
make us confident that the survey design and instrument are well-suited to be
replicated and, thereby, to create a generalisable empirical basis of RE in
practice
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
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
Technical Debt Prioritization: State of the Art. A Systematic Literature Review
Background. Software companies need to manage and refactor Technical Debt
issues. Therefore, it is necessary to understand if and when refactoring
Technical Debt should be prioritized with respect to developing features or
fixing bugs. Objective. The goal of this study is to investigate the existing
body of knowledge in software engineering to understand what Technical Debt
prioritization approaches have been proposed in research and industry. Method.
We conducted a Systematic Literature Review among 384 unique papers published
until 2018, following a consolidated methodology applied in Software
Engineering. We included 38 primary studies. Results. Different approaches have
been proposed for Technical Debt prioritization, all having different goals and
optimizing on different criteria. The proposed measures capture only a small
part of the plethora of factors used to prioritize Technical Debt qualitatively
in practice. We report an impact map of such factors. However, there is a lack
of empirical and validated set of tools. Conclusion. We observed that technical
Debt prioritization research is preliminary and there is no consensus on what
are the important factors and how to measure them. Consequently, we cannot
consider current research conclusive and in this paper, we outline different
directions for necessary future investigations
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