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Self-Admitted Technical Debt (SATD) is a form of Technical Debt where developers document the debt using source code comments (SATD-C) or issues (SATD-I). However, it is still unclear the circumstances that drive developers to choose one or another. In this paper, we survey authors of both types of debts using a large-scale dataset containing 74K SATD-C and 20K SATD-I instances, extracted from 190 GitHub projects. As a result, we provide 13 guidelines to support developers to decide when to use comments or issues to report Technical Debt.
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This dataset is a Verilog-a implementation of a dynamic compact model of ferroelectric capacitance. It can be run with a SPICE-type circuit simulator.
Researchers using this dataset should cite it as follows: Ning Feng, Hao Li, Chang Su, Lining Zhang, Qianqian Huang,Runsheng Wang, and Ru Huang, A Dynamic Compact Model for Ferroelectric Capacitance, IEEE Electron Device Letters, DOI: 10.1109/LED.2022.3141413
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We have long known that the characterization of protein three-dimensional structure is key to obtaining a detailed understanding of protein function. Computational approaches to protein structure characterization have largely addressed a narrow formulation of the problem, where the goal is the determination of one structure, also known as the native structure, from a given protein amino-acid sequence. However, many researchers over the years have argued for broadening our view of proteins to account for the multiplicity of native structures.
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Any work using this dataset should cite the following paper:
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Any work using this dataset should cite the following paper:
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The attached txt file “cir_bis.txt” is the netlist of the SPICE subcircuit of an EMI filter for dc or single-phase ac applications, valid up to 100 MHz. It can be used in a SPICE-compatible solver (e.g., LTSPICE) for frequency-domain or time-domain simulations. It is a passive black-box macromodel obtained as described in the following paper: S. Negri, G. Spadacini, F. Grassi, and S. A.
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This dataset contains world news and also the news article's available metadata.
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Data accompanying the publication "Robotic Elytra: Insect-inspired Protective Wings for Resilient and Multi-modal Drones".
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