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232 results for “smell”
[Replication Package] Impact of Architectural Smells on Software Performance
<p>Replication Package of the paper "Impact of Architectural Smells on Software Performance: an Exploratory Study" accepted for presentation to the 27th International Conference on Evaluation and Assessment in Software Engineering (EASE) 2023.</p>
Trusted Code Smells Dataset
<p>This code smells dataset collected from Git history of top-100 Java projects. It contains 5912 samples of smelly code with fixing it by developers themselves. Collected code smell types are: Complex Method, Long Method and God Class.</p>
Microservice Anti-Patterns and Bad Smells: A Tertiary Study
<p>This dataset contains the search and classification processes of anti-patterns and bad smells catalog tertiary study.</p>
Code and Data for the paper "Active smelling in the American cockroach"
<p>Code and Data used in the paper "Active smelling in the american cockroach" by Antoine Hoffmann and Einat Couzin-Fuchs.<br> Code author: Antoine Hoffmann<br> The file structure indicated in the R scripts needs to be replicated for the code to work as is.</p>
Smell in Covid-19 and Efficacy of Nasal Theophylline
ClinicalTrials.gov study NCT04789499. IPD Sharing: Not stated. Countries: 1. Publications: 46.
Smell in COVID-19 and Efficacy of Nasal Theophylline (SCENT 3)
ClinicalTrials.gov study NCT05947643. IPD Sharing: NO. Countries: 1. Publications: 62.
Validation of a Rapid Quantitative Test for Loss of Smell in COVID-19 Subjects
ClinicalTrials.gov study NCT04431908. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Visual-OLfactory Training in Participants With COVID-19 Resultant Loss of Smell
ClinicalTrials.gov study NCT04710394. IPD Sharing: YES. Countries: 1. Publications: 39.
The Effects of Smell on Mood and Physical Responses
ClinicalTrials.gov study NCT00097253. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Evaluation of Smell and Taste in Fibromyalgia
ClinicalTrials.gov study NCT03823937. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Data from: Insectivorous birds can see and smell systemically herbivore‐induced pines
Open the record for dataset details and reuse information.
The size of a smell: assessment of rival’s size from femoral secretions in the common wall lizards
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Data from: What smells? Developing in-field methods to characterize the chemical composition of wild mammalian scent cues
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Data from: What's that smell? Hummingbirds avoid foraging on resources with defensive insect compounds
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Community smells
<p>This repository is a companion page for our submission "On the Detection of Community Smells using Genetic Programming-based Ensemble Classifier Chain".</p> <p>It contains all the material required to replicate our analysis, including (i) the raw input data (ii) the list of studied projects, and (iii) the features for each smell instance. Some additional data are not included in the paper due to space limitations, are also provided.</p>
MLCQ: Industry-relevant code smell data set
<p>The MLCQ data set with nearly 15000 code samples was created by software developers with professional experience who reviewed industry-relevant, contemporary Java open source projects. </p> <p>We expect that this data set should stay relevant for a longer time than data sets that base on code released years ago and, additionally, will enable researchers to investigate the relationship between developers' background and code smells' perception.</p> <p><strong>If you use this data set please cite the following paper:</strong></p> <p>Lech Madeyski and Tomasz Lewowski. MLCQ: Industry-relevant code smell data set. In <em>Evaluation and Assessment in Software Engineering (EASE2020)</em>, April 15–17, 2020, Trondheim, Norway.ACM, New York, NY, USA, 6 pages, DOI: <a href="https://doi.org/10.1145/3383219.3383264">3383219.3383264</a> URL: https://doi.org/10.1145/3383219.3383264</p> <p>Note: Pre-print should be available soon from <a href="http://madeyski.e-informatyka.pl">http://madeyski.e-informatyka.pl</a></p>
Building on challenges hindering practical use of smell concept: a systematic review (80 primary studies from 2002-2019)
<p>Data set of the research: Extending a systematic review on code smell effect: outlining catalogues, investigated smells and building on tool-related bias (80 primary studies from 2002-2019)</p>
Recommending Composite Refactorings for Smell Removal: Heuristics and Evaluation
<p>Short presentation for the paper entitled "Recommending Composite Refactorings for Smell Removal: Heuristics and Evaluation.</p> <p><strong>Abstract.</strong> Structural degradation is the process in which quality attributes of a system are negatively impacted. When due attention is not paid to structural degradation, the source code may also become difficult to change. Code smells are recurring structures in the source code that may represent structural degradation. Hence, there are many catalogs and techniques for supporting the removal of code smells through refactoring recommendations, such as a Move Method or a Extract Method. Such recommendations usually consist of single refactorings. However, single refactorings are often not enough for completely removing certain smell occurrences. Moreover, recent studies show that developers most often apply composite refactorings -- i.e., sequences of two or more refactorings -- for removing code smells. Despite showing the importance of performing composite refactorings, existing studies do not provide information on which composite refactoring patterns are recurrent in practice. Therefore, in this work, we conducted an empirical study to extract data from multiple open source systems regarding the composite refactoring practice. This data helped us to find 35 recurring patterns that are effective in removing certain types of code smells. Based on such patterns, we propose a suite of new recommendation heuristics to help developers in applying effective composite refactorings. These heuristics are intended to remove three code smell types, namely Complex Class, Feature Envy, and God Class. After designing the heuristics, we evaluated their effectiveness through a quasi-experiment. This evaluation was conducted with 12 software developers and 9 smelly Java classes. Results indicate that developers considered our heuristics effective or partially effective in more than 93% of the cases. In addition, the evaluation helped us to identify multiple factors that contribute to the acceptance or rejection of the refactoring recommendations. Based on these factors we define new guidelines for the effective recommendation of smell-removal composite refactorings.</p>
Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels
<p>Dataset accompanying "Ryan Brate, Paul Groth and Marieke van Erp (2020) Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels. LaTeCH-CLfL 2020. Barcelona, December 2020."</p> <p>Abstract:</p> <p>Environmental factors determine the smells we perceive, but societal factors factors shape the importance, sentiment and biases we give to them. Descriptions of smells in text, or as we call them `smell experiences', offer a window into these factors, but they must first be identified. To the best of our knowledge, no tool exists to extract references to smell experiences from text. In this paper, we present two variations on a semi-supervised approach to identify smell experiences in English literature. The combined set of patterns from both implementations offer significantly better performance than a keyword-based baseline.</p>
Data from: I smell where you walked – how chemical cues influence movement decisions in ants
Interactions between animals are not restricted to direct encounters. Frequently, individuals detect the proximity of others through cues unintentionally left by others, such as prey species assessing predation risk based on indirect predator cues. However, while the importance of indirect cues in predator–prey interactions has been intensely studied, their role in interactions among competitors, and their consequences for community structure, are little known to date. Ant communities are usually structured by aggressive interactions between competing species. Responding to cues of others should be useful to avoid competitors or discover food sources. In ants and other insects, such cues include chemical footprints, which they leave while walking. Here, we investigated how different ant species respond to footprints of others. Ant colonies were confronted with footprints of other colonies or species, and the workers chose between cue-bearing and cue-free areas. Moreover, we determined the chemical composition of footprints, and compared the absolute quantities of footprint and cuticular hydrocarbons. Ants of the species Lasius niger avoided footprints of non-nestmate conspecifics, and tended to avoid footprints of two other species. We suggest that they avoided encounters with competitors to reduce costly fights. In contrast, three other ant species approached allospecific footprints, which may represent eavesdropping to find resources discovered by others. Three of the four ant species responded differently to nestmates and non-nestmate footprints either through footprint-following or antennation behavior. The chemical composition of footprints was species-specific and largely congruent to cuticular hydrocarbons. Footprint quantities left by single workers represented 1/170 to 1/64 of the quantity of their cuticular hydrocarbons. We showed that chemical footprints represent an important cue for behavioral decisions in ants. The ability to identify and respond to chemical footprints may represent an important strategy for insects to cope with competing species or colonies in their habitat.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.