243 research outputs found
Testing principles, current practices, and effects of change localization
No full textPreprint of a paper presented at: MSR 2013, The 10th Working Conference on Mining Software Repositories, May 18–19, 2013, San Francisco, California, USA.Software TechnologyElectrical Engineering, Mathematics and Computer Scienc
Radiolytic Production of Fluorine Gas from MSR Relevant Fluoride Salts
No full textRadiolytic fluorine gas production at temperatures of 40°C to 60°C was investigated for the fluoride salts LiF, BeF2, UF4, ThF4, and 71.7LiF-16BeF2-12.3UF4 (FliBe-UF4) by gamma irradiation of powdered samples using spent fuel elements from the High Flux Reactor (HFR) Petten as the irradiation source; work of a similar nature was previously performed at Oak Ridge National Laboratory in the period 1965 to 1995. Gamma irradiation was conducted for just over 41 days, with total absorbed gamma dose ranging from ~45 MGy for the lightest salts to ~170 MGy for ThF4 and UF4. By measuring the gas pressure within salt-filled capsules during irradiation, it was possible to quantify radiolytic gas production for all salt samples except UF4. Production rates are reported as the salt G-values, measured as number of fluorine molecules produced per 100 eV of energy absorbed (molecules F2/100 eV). The G-values of the salts were found to be G(LiF) ~0.004, G(BeF2) ~0.009, G(ThF4) ~0.021, and G(FLiBe-UF4) ~0.005.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.RST/Reactor Physics and Nuclear Material
A Panel Data Set of Cryptocurrency Development Activity on GitHub
No full text<p>Contents:</p>
<ul>
<li><strong>all-sorted-recovered-normalized-2018-01-21-to-2019-02-04.csv</strong>: CSV format of all data, sorted by date. This file contains some imputed values for missing data, and all fields across all repositories and normalized to "null". This is the most convenient form to use.</li>
<li><strong>all-sorted-2018-01-21-to-2019-02-04.csv</strong>: CSV format of all, sorted by date. It is the raw data after processing the raw format.</li>
<li><strong>raw-data-2018-01-21-to-2019-02-04.tar.gz</strong>: The raw format of data collected (S-expressions). Contains additional contributor data and CoinMarketCap data not currently in the CSV datasets.</li>
<li><strong>recovered.patch</strong>: The modification on <strong>all-sorted-2018-01-21-to-2019-02-04.csv</strong> after recovering (imputing) data<strong>, </strong>showing what was recovered.</li>
<li><strong>recovered-normalized.patch</strong>: The modification of <strong>all-sorted-2018-01-21-to-2019-02-04.csv </strong>after normalizing the recovered data set. Thus, patching <strong>all-sorted-2018-01-21-to-2019-02-04.csv </strong>with<strong> recovered.patch</strong>, then <strong>recovered-normalized.patch </strong>gives <strong>all-sorted-recovered-normalized-2018-01-21-to-2019-02-04.csv</strong></li>
<li><strong>missing-dates.txt</strong>: Days for which we missed GitHub data collection (partial or completely).</li>
</ul>
<p>Related publications:</p>
<pre><code>@inproceedings{van-tonder-crypto-oss-2019,
title = {{A Panel Data Set of Cryptocurrency Development Activity on GitHub}},
booktitle = "International Conference on Mining Software Repositories",
author = "{van~Tonder}, Rijnard and Trockman, Asher and {Le~Goues}, Claire",
series = {MSR '19},
year = 2019
}
@inproceedings{trockman-striking-gold-2019,
title = {{Striking Gold in Software Repositories? An Econometric Study of Cryptocurrencies on GitHub}},
booktitle = "International Conference on Mining Software Repositories", author = "Trockman, Asher and {van~Tonder}, Rijnard and Vasilescu, Bogdan",
series = {MSR '19},
year = 2019
}</code></pre>
<p>Related code: <a href="https://github.com/rvantonder/CryptOSS">https://github.com/rvantonder/CryptOSS</a></p>
What Are Your Programming Language's Energy-Delay Implications?
No full textMotivation: Even though many studies examine the energy efficiency of hardware and embedded systems, those that investigate the energy consumption of software applications are still limited, and mostly focused on mobile applications. As modern applications become even more complex and heterogeneous a need arises for methods that can accurately assess their energy consumption.
Goal: Measure the energy consumption and run-time performance of commonly used programming tasks implemented in different programming languages and executed on a variety of platforms to help developers to choose appropriate implementation platforms.
Method: Obtain measurements to calculate the Energy Delay Product, a weighted function that takes into account a task's energy consumption and run-time performance. We perform our tests by calculating the Energy Delay Product of 25 programming tasks, found in the Rosetta Code Repository, which are implemented in 14 programming languages and run on three different computer platforms, a server, a laptop, and an embedded system.
Results: Compiled programming languages are outperforming the interpreted ones for most, but not for all tasks. C, C#, and JavaScript are on average the best performing compiled, semi-compiled, and interpreted programming languages for the Energy Delay Product, and Rust appears to be well-placed for i/o-intensive operations, such as file handling. We also find that a good behaviour, energy-wise, can be the result of clever optimizations and design choices in seemingly unexpected programming languages
Using Association Rules to Study the Co-evolution of Production & Test Code
No full textPaper accepted for publication in the proceedings of the 6th International Working Conference on Mining Software Repositories (MSR 2009). Unit tests are generally acknowledged as an important aid to produce high quality code, as they provide quick feedback to developers on the correctness of their code. In order to achieve high quality, well-maintained tests are needed. Ideally, tests co-evolve with the production code to test changes as soon as possible. In this paper, we explore an approach based on association rule mining to determine whether production and test code co-evolve synchronously. Through two case studies, one with an open source and another one with an industrial software system, we show that our association rule mining approach allows one to assess the co-evolution of product and test code in a software project and, moreover, to uncover the distribution of programmer effort over pure coding, pure testing, or a more test-driven-like practice.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc
Intrinsic methane steam reforming kinetics on nickel-ceria solid oxide fuel cell anodes
No full textDirect internal reforming in solid oxide fuel cells (SOFCs) is advantageous as it enables to heat and steam from the exothermic hydrogen oxidation reaction in the endothermic steam reforming reaction. However, it may increase potentially deteriorating temperature gradients as well. The temperature and concentration profiles can be accurately simulated with adequate SOFC models and intrinsic methane steam reforming (MSR) kinetics. Therefore, this study aims to derive intrinsic MSR kinetics suitable for control-oriented dynamic SOFC models. The individual influences of the methane, steam and hydrogen partial pressures on the MSR reaction are experimentally studied on functional electrolyte supported cells with nickel-gadolinium doped cerium anodes. A non-proportional dependence of the MSR rate on the methane partial pressure and a slight negative dependence on the steam partial pressure are observed, but the effect of the hydrogen partial pressure seems insignificant. Various kinetic rate equations are parameterised with the experimental data and an ideal plug flow reactor model. An intrinsic Langmuir-Hinshelwood mechanism for a rate determining step between associatively adsorbed methane and dissociatively adsorbed steam on the catalyst surface shows good agreement with the experimental data, and is thermodynamically and physically consistent.Ship Design, Production and OperationsEnergy Technolog
An Exploratory Study of Log Placement Recommendation in an Enterprise System
No full textLogging is a development practice that plays an important role in the operations and monitoring of complex systems. Developers place log statements in the source code and use log data to understand how the system behaves in production. Unfortunately, anticipating where to log during development is challenging. Previous studies show the feasibility of leveraging machine learning to recommend log placement despite the data imbalance since logging is a fraction of the overall code base. However, it remains unknown how those techniques apply to an industry setting, and little is known about the effect of imbalanced data and sampling techniques. In this paper, we study the log placement problem in the code base of Adyen, a large-scale payment company. We analyze 34,526 Java files and 309,527 methods that sum up +2M SLOC. We systematically measure the effectiveness of five models based on code metrics, explore the effect of sampling techniques, understand which features models consider to be relevant for the prediction, and evaluate whether we can exploit 388,086 methods from 29 Apache projects to learn where to log in an industry setting. Our best performing model achieves 79% of balanced accuracy, 81% of precision, 60% of recall. While sampling techniques improve recall, they penalize precision at a prohibitive cost. Experiments with open-source data yield under-performing models over Adyen's test set; nevertheless, they are useful due to their low rate of false positives. Our supporting scripts and tools are available to the community.Accepted author manuscriptSoftware EngineeringSoftware Technolog
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