An official website of the United States government
To train future engineers and to equip them with necessary tools and skills for real-world problem solving, it is important to provide exposure to real-world problem solving by incorporating a software lab module while teaching engineering courses such as Computational Fluid Dynamics (CFD) and/or related Fluids courses. High cost of commercial software packages and limited number of licenses available for course instruction creates several challenges in incorporating commercial software packages in the instructional workflow. To circumvent such limitations, open-source software packages could be a good alternative as open-source software packages can be downloaded and used free of cost and thus provides a wider accessibility to students and practitioners. With the same motivation, in this contribution, an outline for implementing a two-week course module by incorporating open-source software in the instructional workflow is proposed and demonstrated by considering an example of wind flow around a building. The course module outlined in this work can also be extended to formulate a full-fledged CFD course for instructional purposes. Besides the information provided in this paper, authors have also shared an extended report based on current work and the relevant case files via Github repository (https://github.com/rpsuark/ASEE21-OpenFOAM-Introduction) for a hands on learning experience. With the help of information contained in this paper along with the extended report and uploaded case files, readers can install the open-source software packages - ‘OpenFOAM’ and ‘ParaView’, make their own simple case files, run simulations, and visualize the simulated results.
more »
« less
Predicting Licenses for Changed Source Code
Open source software licenses regulate the circumstances under which software can be redistributed, reused and modified. Ensuring license compatibility and preventing license restriction conflicts among source code during software changes are the key to protect their commercial use. However, selecting the appropriate licenses for software changes requires lots of experience and manual effort that involve examining, assimilating and comparing various licenses as well as understanding their relationships with software changes. Worse still, there is no state-of-the-art methodology to provide this capability. Motivated by this observation, we propose in this paper Automatic License Prediction (ALP), a novel learning-based method and tool for predicting licenses as software changes. An extensive evaluation of ALP on predicting licenses in 700 open source projects demonstrate its effectiveness: ALP can achieve not only a high overall prediction accuracy (92.5% in micro F1 score) but also high accuracies across all license types.
more »
« less
- Award ID(s):
- 1848608
- PAR ID:
- 10289100
- Date Published:
- Journal Name:
- Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering
- Page Range / eLocation ID:
- 686 - 697
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This work focuses on forecasting future license usage for high-performance computing environments and using such predictions to improve the effectiveness of job scheduling. Specifically, we propose a model that carries out both short-term and long-term license usage forecasting and a method of using forecasts to improve job scheduling. Our long-term forecasting model achieves a Mean Absolute Percentage Error (MAPE) as low as 0.26 for a 12-month forecast of daily peak license usage. Our job scheduling experimental results also indicate that wasted work from jobs with insufficient licenses can be reduced by up to 92% without increasing the average license-using job completion times, during periods of high license usage, with our proposed license-aware scheduler.more » « less
-
null (Ed.)This article describes the motivation, design, and progress of the Journal of Open Source Software (JOSS). JOSS is a free and open-access journal that publishes articles describing research software. It has the dual goals of improving the quality of the software submitted and providing a mechanism for research software developers to receive credit. While designed to work within the current merit system of science, JOSS addresses the dearth of rewards for key contributions to science made in the form of software. JOSS publishes articles that encapsulate scholarship contained in the software itself, and its rigorous peer review targets the software components: functionality, documentation, tests, continuous integration, and the license. A JOSS article contains an abstract describing the purpose and functionality of the software, references, and a link to the software archive. The article is the entry point of a JOSS submission, which encompasses the full set of software artifacts. Submission and review proceed in the open, on GitHub. Editors, reviewers, and authors work collaboratively and openly. Unlike other journals, JOSS does not reject articles requiring major revision; while not yet accepted, articles remain visible and under review until the authors make adequate changes (or withdraw, if unable to meet requirements). Once an article is accepted, JOSS gives it a digital object identifier (DOI), deposits its metadata in Crossref, and the article can begin collecting citations on indexers like Google Scholar and other services. Authors retain copyright of their JOSS article, releasing it under a Creative Commons Attribution 4.0 International License. In its first year, starting in May 2016, JOSS published 111 articles, with more than 40 additional articles under review. JOSS is a sponsored project of the nonprofit organization NumFOCUS and is an affiliate of the Open Source Initiative (OSI).more » « less
-
Vidick, T. (Ed.)We study auctions for carbon licenses, a policy tool used to control the social cost of pollution. Each identical license grants the right to produce a unit of pollution. Each buyer (i.e., firm that pollutes during the manufacturing process) enjoys a decreasing marginal value for licenses, but society suffers an increasing marginal cost for each license distributed. The seller (i.e., the government) can choose a number of licenses to put up for auction, and wishes to maximize the societal welfare: the total economic value of the buyers minus the social cost. Motivated by emission license markets deployed in practice, we focus on uniform price auctions with a price floor and/or price ceiling. The seller has distributional information about the market, and their goal is to tune the auction parameters to maximize expected welfare. The target benchmark is the maximum expected welfare achievable by any such auction under truth-telling behavior. Unfortunately, the uniform price auction is not truthful, and strategic behavior can significantly reduce (even below zero) the welfare of a given auction configuration. We describe a subclass of “safe-price” auctions for which the welfare at any Bayes-Nash equilibrium will approximate the welfare under truth-telling behavior. We then show that the better of a safeprice auction, or a truthful auction that allocates licenses to only a single buyer, will approximate the target benchmark. In particular, we show how to choose a number of licenses and a price floor so that the worst-case welfare, at any equilibrium, is a constant approximation to the best achievable welfare under truth-telling after excluding the welfare contribution of a single buyer.more » « less
-
Barnard, Daron (Ed.)Open educational resources, or OER, are teaching materials that reside in the public domain and are available under an open license. While the creation of high-quality materials and cyberinfrastructure to share these resources is important, OER are much more than static resource repositories. Vibrant OER communities function as collaboration hubs and often include librarians, instructional technologists, instructors, education researchers, funders, open-source software developers, and college administrators. Together, these individuals work as a community to respond to changes in the education landscape, support student learning impacts both in terms of cost savings and student retention, and solve issues related to broadly sharing open resources on the web. This essay provides general information about OER, describes communities developing OER for science, technology, engineering, and mathematics education, and presents insights about sustainability challenges. The sustainability challenges are organized according to multiple dimensions: cultural and social, economic and financial, and technological and environmental. In addition, OER provide important opportunities to address and promote social justice and open and accessible education philosophies. Knowing more about the OER landscape, sustainability challenges, and educational justice opportunities can help instructors use and contribute to this growing movement to reshape the landscape of undergraduate education.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ASE.2019.00070
