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1,034 results for “Empirical”
Replication Package for the Paper: "An Empirical Analysis of the Manual Detection of Code Smells via Code Review"
<p>This repository contains the data and results from the paper "An Empirical Analysis of the Manual Detection of Code Smells via Code Review" submitted to SANER 2021.</p> <p> </p> <p><strong>1. "data.zip" contains the following three folders: </strong></p> <p> </p> <p><strong>1). data folder</strong></p> <p>The data folder contains the retrieved 1,174 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell, Code Smell Discussion, and Source Code URL.</p> <p> </p> <p><strong>2). scripts folder</strong></p> <p>The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms.</p> <ul> <li><em>keywords.txt</em> contains the keywords associated with code smells, such as "smell, duplication, and dead".</li> <li><em>get_changes.py</em> is used for getting code changes from OpenStack.</li> <li><em>get_comments.py</em> is used for getting review comments for each code change.</li> <li><em>keywords_search.py</em> is used for searching review comments that contain at least one keyword.</li> <li><em>keywords_improve.py</em> is used for improving the keyword-based mining approach.</li> <li><em>tools.py</em> is used for supporting the process of keywords improving.</li> </ul> <p> </p> <p><strong>3). project folder</strong></p> <p>The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p> <ul> <li><em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool.</li> <li><em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.</li> </ul> <p> </p> <p><strong>2. Keywords associated with code smells.pdf</strong></p> <p>This file contains the final set of keywords associated with code smells that we identified by following the systematic approach proposed by Bosu and his colleagues in their paper: Identifying the Characteristics of Vulnerable Code Changes: An Empirical Study, FSE 2014.</p>
Replication Package for the Paper: "An Empirical Analysis of the Manual Detection of Code Smells via Code Review"
<p>This repository contains the data and results from the paper "An Empirical Analysis of the Manual Detection of Code Smells via Code Review" submitted to SANER 2021.</p> <p> </p> <p><strong>1. "data.zip" contains the following three folders: </strong></p> <p> </p> <p><strong>1). data folder</strong></p> <p>The data folder contains the retrieved 1,174 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell, Code Smell Discussion, and Source Code URL.</p> <p> </p> <p><strong>2). scripts folder</strong></p> <p>The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms.</p> <ul> <li><em>keywords.txt</em> contains the keywords keywords asociated with code smells, such as "smell, duplication, and dead".</li> <li><em>get_changes.py</em> is used for getting code changes from OpenStack.</li> <li><em>get_comments.py</em> is used for getting review comments for each code change.</li> <li><em>keywords_search.py</em> is used for searching review comments that contain at least one keyword.</li> <li>keywords_improve.py is used for improving the keyword-based mining approach.</li> <li>tools.py is used for supporting the process of keywords improving.</li> </ul> <p> </p> <p><strong>3). project folder</strong></p> <p>The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p> <ul> <li><em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool.</li> <li><em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.</li> </ul> <p> </p> <p><strong>2. Keywords associated with code smells.pdf</strong></p> <p>This file contains the final set of keywords asociated with code smells that we identified by following the systematic approach proposed by Bosu and his colleagues in their paper: Identifying the Characteristics of Vulnerable Code Changes: An Empirical Study, FSE 2014.</p>
Replication Package for the Paper: "An Empirical Analysis of the Manual Detection of Code Smells via Code Review"
<p>This repository contains the data and results from the paper "An Empirical Analysis of the Manual Detection of Code Smells via Code Review" submitted to SANER 2021.</p> <p> </p> <p><strong>1. "data.zip" file contains the following three folders: </strong></p> <p> </p> <p><strong>1). data folder</strong></p> <p>The data folder contains the retrieved 1,174 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell, Code Smell Discussion, and Source Code URL.</p> <p> </p> <p><strong>2). scripts folder</strong></p> <p>The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms.</p> <ul> <li><em>keywords.txt</em> contains the keywords keywords asociated with code smells, such as "smell, duplication, and dead".</li> <li><em>get_changes.py</em> is used for getting code changes from OpenStack.</li> <li><em>get_comments.py</em> is used for getting review comments for each code change.</li> <li><em>keywords_search.py</em> is used for searching review comments that contain at least one keyword.</li> <li>keywords_improve.py is used for improving the keyword-based mining approach.</li> <li>tools.py is used for supporting the process of keywords improving.</li> </ul> <p> </p> <p><strong>3). project folder</strong></p> <p>The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download.</p> <ul> <li><em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool.</li> <li><em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.</li> </ul> <p> </p> <p><strong>2. Keywords associated with code smells.pdf</strong></p> <p>This file contains the final set of keywords asociated with code smells that we identified by following the systematic approach proposed by Bosu and his colleagues in their paper: Identifying the Characteristics of Vulnerable Code Changes: An Empirical Study, FSE 2014.</p>
Research on the impact of the digital economy on narrowing the gap between urban and rural areas—An empirical analysis based on provincial panel data
Open the record for dataset details and reuse information.
The Impact of Continuous Integration into Test Code Evolution: An Empirical Study
<p>The set of datasets used during the study</p>
INTERLEAVE : An Empirically Faster Symbolic Algorithm for Maximal End Component Decomposition of MDPs -- Evaluation
<p>Please refer to the updated artifact for our CAV 2025 paper - https://zenodo.org/records/15220239.</p>
Database article Developing Sustainable Career Paths for Preuniversity Teachers. An Empirical Analysis of Central Dimensions of Job Readiness
<p>The quality of teacher training is highly likely to influence the quality of learning outcomes. In this view, the present paper aimed to develop a pre-service teachers’ job readiness model integrating individual variables associated with teacher professionalism. The study followed an exploratory cross-sectional research design. A sample of 312 Romanian pre-service STEM (Science, Technology, Engineering, and Mathematics) teachers was selected based on availability criteria. A pre-tested self-administered questionnaire using a 5-point Likert scale was applied during the data collection process. Data analysis was based on a combination of descriptive and inferential statistics, a blending factor analysis and structural equations modeling. A conceptual model of teaching readiness from the teacher professionalism perspective was developed and tested using empirical data. The results suggest that professional knowledge, professional practice, professional engagement and self-management could be considered central dimensions of teacher professionalism, being highly relevant in assessing pre-service teacher job readiness. Moreover, professional knowledge has a strong and positive influence on teaching practice and professional engagement. In relation to the professional knowledge latent variable, the ability to conduct didactic transposition is the most influential. Following the same line of analysis, the most significant vectors of the professional practice variable were found to be the ability to design effective evaluation tools and to analyze and interpret learning outcomes. The research revealed the presence of vulnerable or sensitive areas of teacher training that could be a result of curriculum design. With respect to managing disruptive behaviours, the customization of learning and emotional self-regulation are considered weak areas of teaching readiness. The results could be useful for policymakers and teacher training practitioners in order to improve overall job readiness and teacher professionalism.</p>
Replication Package for the Paper:Empirical Research on Secure Development in Agile Methods: A Systematic Literature Review
Open the record for dataset details and reuse information.
Gardening for biodiversity: an empirical exploration of garden owner's barriers, attitudes, and gardening behaviors - DATASET
<p>Correspondance author: Oriol García-Antúnez. University of Copenhagen, Department of Geosciences and Natural Resource Management, Rolighedsvej 23, 1958 Frederiksberg C, Denmark. e-mail: oga@ign.ku.dk</p> <p> </p>
MRO CRISM TARGETED EMPIRICAL RECORD V1.0
This volume contains the CRISM Targeted Empirical Record (TER) archive, a collection of multiband image cubes derived from targeted (gimbaled) observations of Mars' surface acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instrument on the Mars Reconnaissance Orbiter (MRO) spacecraft. Post-processing attempts to represent the spectrum the instrument would have measured looking at the surface of Mars at a standard illumination geometry, in the absence of atmospheric gases, with aerosol scattering normalized to that at the geometry within the observation that is closest to nadir, in the absence of instrument artifacts. A series of value added products represent spatial variability in signatures of minerals of interest. The data are still in sensor space, allowing map projection using terrain models of the Martian surface that are of better accuracy or spatial resolution than was used to generate the companion Map-projected Targeted Reduced Data Record (MTR) archive.
Results for the empirical determinacy manuscript in .RData format
<p>Results for the empirical determinacy manuscript for the 8 schools, RTI and simulation studies in .RData format</p>
pull request id for the dataset of "Pull Request Latency Explained: An Empirical Overview"
<p>This is used for research, which includes the pull request id.</p> <p>Researchers need to request the access.</p>
Dataset of An Empirical Study of Concurrency Vulnerabilities in Linux
<p>Dataset of An Empirical Study of Concurrency Vulnerabilities in Linux</p>
An Empirical Study of Embedded WebAssembly Virtual Machine
<p>This contains all the experimental code, data sets, and result files for our experiments.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.