180,505 research outputs found
Why Software Projects need Heroes (Lessons Learned from 1000+ Projects)
A "hero" project is one where 80% or more of the contributions are made by
the 20% of the developers. Those developers are called "hero" developers. In
the literature, heroes projects are deprecated since they might cause
bottlenecks in development and communication. However, there is little
empirical evidence on this matter. Further, recent studies show that such hero
projects are very prevalent. Accordingly, this paper explores the effect of
having heroes in project, from a code quality perspective by analyzing 1000+
open source GitHub projects. Based on the analysis, this study finds that (a)
majority of the projects are hero projects; and (b)the commits from "hero
developers" (who contribute most to the code) result in far fewer bugs than
other developers. That is, contrary to the literature, heroes are standard and
very useful part of modern open source projects.Comment: 12 pages, 11 figures, 3 tables, IEEE Transactions on Software
Engineerin
Empirical Big Data Research: A Systematic Literature Mapping
Background: Big Data is a relatively new field of research and technology,
and literature reports a wide variety of concepts labeled with Big Data. The
maturity of a research field can be measured in the number of publications
containing empirical results. In this paper we present the current status of
empirical research in Big Data. Method: We employed a systematic mapping method
with which we mapped the collected research according to the labels Variety,
Volume and Velocity. In addition, we addressed the application areas of Big
Data. Results: We found that 151 of the assessed 1778 contributions contain a
form of empirical result and can be mapped to one or more of the 3 V's and 59
address an application area. Conclusions: The share of publications containing
empirical results is well below the average compared to computer science
research as a whole. In order to mature the research on Big Data, we recommend
applying empirical methods to strengthen the confidence in the reported
results. Based on our trend analysis we consider Volume and Variety to be the
most promising uncharted area in Big Data.Comment: Submitted to Springer journal Data Science and Engineerin
Haptic Assembly and Prototyping: An Expository Review
An important application of haptic technology to digital product development
is in virtual prototyping (VP), part of which deals with interactive planning,
simulation, and verification of assembly-related activities, collectively
called virtual assembly (VA). In spite of numerous research and development
efforts over the last two decades, the industrial adoption of haptic-assisted
VP/VA has been slower than expected. Putting hardware limitations aside, the
main roadblocks faced in software development can be traced to the lack of
effective and efficient computational models of haptic feedback. Such models
must 1) accommodate the inherent geometric complexities faced when assembling
objects of arbitrary shape; and 2) conform to the computation time limitation
imposed by the notorious frame rate requirements---namely, 1 kHz for haptic
feedback compared to the more manageable 30-60 Hz for graphic rendering. The
simultaneous fulfillment of these competing objectives is far from trivial.
This survey presents some of the conceptual and computational challenges and
opportunities as well as promising future directions in haptic-assisted VP/VA,
with a focus on haptic assembly from a geometric modeling and spatial reasoning
perspective. The main focus is on revisiting definitions and classifications of
different methods used to handle the constrained multibody simulation in
real-time, ranging from physics-based and geometry-based to hybrid and unified
approaches using a variety of auxiliary computational devices to specify,
impose, and solve assembly constraints. Particular attention is given to the
newly developed 'analytic methods' inherited from motion planning and protein
docking that have shown great promise as an alternative paradigm to the more
popular combinatorial methods.Comment: Technical Report, University of Connecticut, 201
Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey
Topic modeling is one of the most powerful techniques in text mining for data
mining, latent data discovery, and finding relationships among data, text
documents. Researchers have published many articles in the field of topic
modeling and applied in various fields such as software engineering, political
science, medical and linguistic science, etc. There are various methods for
topic modeling, which Latent Dirichlet allocation (LDA) is one of the most
popular methods in this field. Researchers have proposed various models based
on the LDA in topic modeling. According to previous work, this paper can be
very useful and valuable for introducing LDA approaches in topic modeling. In
this paper, we investigated scholarly articles highly (between 2003 to 2016)
related to Topic Modeling based on LDA to discover the research development,
current trends and intellectual structure of topic modeling. Also, we summarize
challenges and introduce famous tools and datasets in topic modeling based on
LDA.Comment: arXiv admin note: text overlap with arXiv:1505.07302 by other author
Data Management in Industry 4.0: State of the Art and Open Challenges
Information and communication technologies are permeating all aspects of
industrial and manufacturing systems, expediting the generation of large
volumes of industrial data. This article surveys the recent literature on data
management as it applies to networked industrial environments and identifies
several open research challenges for the future. As a first step, we extract
important data properties (volume, variety, traffic, criticality) and identify
the corresponding data enabling technologies of diverse fundamental industrial
use cases, based on practical applications. Secondly, we provide a detailed
outline of recent industrial architectural designs with respect to their data
management philosophy (data presence, data coordination, data computation) and
the extent of their distributiveness. Then, we conduct a holistic survey of the
recent literature from which we derive a taxonomy of the latest advances on
industrial data enabling technologies and data centric services, spanning all
the way from the field level deep in the physical deployments, up to the cloud
and applications level. Finally, motivated by the rich conclusions of this
critical analysis, we identify interesting open challenges for future research.
The concepts presented in this article thematically cover the largest part of
the industrial automation pyramid layers. Our approach is multidisciplinary, as
the selected publications were drawn from two fields; the communications,
networking and computation field as well as the industrial, manufacturing and
automation field. The article can help the readers to deeply understand how
data management is currently applied in networked industrial environments, and
select interesting open research opportunities to pursue
Performance and Programming Effort Trade-offs of Android Persistence Frameworks
A fundamental building block of a mobile application is the ability to
persist program data between different invocations. Referred to as
\emph{persistence}, this functionality is commonly implemented by means of
persistence frameworks. Without a clear understanding of the energy
consumption, execution time, and programming effort of popular Android
persistence frameworks, mobile developers lack guidelines for selecting
frameworks for their applications. To bridge this knowledge gap, we report on
the results of a systematic study of the performance and programming effort
trade-offs of eight Android persistence frameworks, and provide practical
recommendations for mobile application developers.Comment: Preprint version of Journal of Systems and Software submissio
A Review on the Application of Blockchain for the Next Generation of Cybersecure Industry 4.0 Smart Factories
Industry 4.0 is a concept devised for improving the way modern factories
operate through the use of some of the latest technologies, like the ones used
for creating Industrial Internet of Things (IIoT), robotics or Big Data
applications. One of such technologies is blockchain, which is able to add
trust, security and decentralization to different industrial fields. This
article focuses on analyzing the benefits and challenges that arise when using
blockchain and smart contracts to develop Industry 4.0 applications. In
addition, this paper presents a thorough review on the most relevant
blockchain-based applications for Industry 4.0 technologies. Thus, its aim is
to provide a detailed guide for future Industry 4.0 developers that allows for
determining how blockchain can enhance the next generation of cybersecure
industrial applications
Mathematical Software: Past, Present, and Future
This paper provides some reflections on the field of mathematical software on
the occasion of John Rice's 65th birthday. I describe some of the common themes
of research in this field and recall some significant events in its evolution.
Finally, I raise a number of issues that are of concern to future developments.Comment: To appear in the Proceedings of the International Symposium on
Computational Sciences, Purdue University, May 21-22, 1999. 20 page
Performance-oriented DevOps: A Research Agenda
DevOps is a trend towards a tighter integration between development (Dev) and
operations (Ops) teams. The need for such an integration is driven by the
requirement to continuously adapt enterprise applications (EAs) to changes in
the business environment. As of today, DevOps concepts have been primarily
introduced to ensure a constant flow of features and bug fixes into new
releases from a functional perspective. In order to integrate a non-functional
perspective into these DevOps concepts this report focuses on tools,
activities, and processes to ensure one of the most important quality
attributes of a software system, namely performance.
Performance describes system properties concerning its timeliness and use of
resources. Common metrics are response time, throughput, and resource
utilization. Performance goals for EAs are typically defined by setting upper
and/or lower bounds for these metrics and specific business transactions. In
order to ensure that such performance goals can be met, several activities are
required during development and operation of these systems as well as during
the transition from Dev to Ops. Activities during development are typically
summarized by the term Software Performance Engineering (SPE), whereas
activities during operations are called Application Performance Management
(APM). SPE and APM were historically tackled independently from each other, but
the newly emerging DevOps concepts require and enable a tighter integration
between both activity streams. This report presents existing solutions to
support this integration as well as open research challenges in this area
A Fast Volume Integral Equation Solver with Linear Basis Functions for the Accurate Computation of Electromagnetic Fields in MRI
A stable volume integral equation (VIE) solver based on
polarization/magnetization currents is presented, for the accurate and
efficient computation of the electromagnetic scattering from highly
inhomogeneous and high contrast objects.We employ the Galerkin Method of
Moments to discretize the formulation with discontinuous piecewise linear basis
functions on uniform voxelized grids, allowing for the acceleration of the
associated matrix-vector products in an iterative solver, with the help of FFT.
Numerical results illustrate the superior accuracy and more stable convergence
properties of the proposed framework, when compared against standard low order
(piecewise constant) discretization schemes and a more conventional VIE
formulation based on electric flux densities. Finally, the developed solver is
applied to analyze complex geometries, including realistic human body models,
typically used in modeling the interactions between electromagnetic waves and
biological tissue.Comment: 13 pages, 6 figures, 8 Table
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