24,796 research outputs found
Software evolution prediction using seasonal time analysis: a comparative study
Prediction models of software change requests are useful for supporting rational and timely resource allocation to the evolution process. In this paper we use a time series forecasting model to predict software maintenance and evolution requests in an open source software project (Eclipse), as an example of projects with seasonal release cycles. We build an ARIMA model based on data collected from Eclipse’s change request tracking system since the project’s start. A change request may refer to defects found in the software, but also to suggested improvements in the system under scrutiny. Our model includes the identification of seasonal patterns and tendencies, and is validated through the forecast of the change requests evolution for the next 12 months. The usage of seasonal information significantly improves the estimation ability of this model, when compared to other ARIMA models found in the literature, and does so for a much longer estimation period. Being able to accurately forecast the change requests’ evolution over a fairly long time period is an important ability for enabling adequate process control in maintenance activities, and facilitates effort estimation and timely resources allocation. The approach presented in this paper is suitable for projects with a relatively long history, as the model building process relies on historic data
Surface inspection: Research and development
Surface inspection techniques are used for process learning, quality verification, and postmortem analysis in manufacturing for a spectrum of disciplines. First, trends in surface analysis are summarized for integrated circuits, high density interconnection boards, and magnetic disks, emphasizing on-line applications as opposed to off-line or development techniques. Then, a closer look is taken at microcontamination detection from both a patterned defect and a particulate inspection point of view
A 3D Framework for Characterizing Microstructure Evolution of Li-Ion Batteries
Lithium-ion batteries are commonly found in many modern consumer devices, ranging from portable computers and mobile phones to hybrid- and fully-electric vehicles. While improving efficiencies and increasing reliabilities are of critical importance for increasing market adoption of the technology, research on these topics is, to date, largely restricted to empirical observations and computational simulations. In the present study, it is proposed to use the modern technique of X-ray microscopy to characterize a sample of commercial 18650 cylindrical Li-ion batteries in both their pristine and aged states. By coupling this approach with 3D and 4D data analysis techniques, the present study aimed to create a research framework for characterizing the microstructure evolution leading to capacity fade in a commercial battery. The results indicated the unique capabilities of the microscopy technique to observe the evolution of these batteries under aging conditions, successfully developing a workflow for future research studies
Classifying Web Exploits with Topic Modeling
This short empirical paper investigates how well topic modeling and database
meta-data characteristics can classify web and other proof-of-concept (PoC)
exploits for publicly disclosed software vulnerabilities. By using a dataset
comprised of over 36 thousand PoC exploits, near a 0.9 accuracy rate is
obtained in the empirical experiment. Text mining and topic modeling are a
significant boost factor behind this classification performance. In addition to
these empirical results, the paper contributes to the research tradition of
enhancing software vulnerability information with text mining, providing also a
few scholarly observations about the potential for semi-automatic
classification of exploits in the existing tracking infrastructures.Comment: Proceedings of the 2017 28th International Workshop on Database and
Expert Systems Applications (DEXA).
http://ieeexplore.ieee.org/abstract/document/8049693
Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development
Mobile devices and platforms have become an established target for modern
software developers due to performant hardware and a large and growing user
base numbering in the billions. Despite their popularity, the software
development process for mobile apps comes with a set of unique, domain-specific
challenges rooted in program comprehension. Many of these challenges stem from
developer difficulties in reasoning about different representations of a
program, a phenomenon we define as a "language dichotomy". In this paper, we
reflect upon the various language dichotomies that contribute to open problems
in program comprehension and development for mobile apps. Furthermore, to help
guide the research community towards effective solutions for these problems, we
provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference
on Program Comprehension (ICPC'18
Dynamic instability of cooperation due to diverse activity patterns in evolutionary social dilemmas
Individuals might abstain from participating in an instance of an
evolutionary game for various reasons, ranging from lack of interest to risk
aversion. In order to understand the consequences of such diverse activity
patterns on the evolution of cooperation, we study a weak prisoner's dilemma
where each player's participation is probabilistic rather than certain. Players
that do not participate get a null payoff and are unable to replicate. We show
that inactivity introduces cascading failures of cooperation, which are
particularly severe on scale-free networks with frequently inactive hubs. The
drops in the fraction of cooperators are sudden, while the spatiotemporal
reorganization of compact cooperative clusters, and thus the recovery, takes
time. Nevertheless, if the activity of players is directly proportional to
their degree, or if the interaction network is not strongly heterogeneous, the
overall evolution of cooperation is not impaired. This is because inactivity
negatively affects the potency of low-degree defectors, who are hence unable to
utilize on their inherent evolutionary advantage. Between cascading failures,
the fraction of cooperators is therefore higher than usual, which lastly
balances out the asymmetric dynamic instabilities that emerge due to
intermittent blackouts of cooperative hubs.Comment: 6 two-column pages, 6 figures; accepted for publication in
Europhysics Letter
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