Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
12
datasets available to search
ShareScore release 0.9.0
Dataset results
12 results for “Anti-Pattern”
Cataloging Dependency Injection Anti-Patterns in Software Systems
<p><strong>Background</strong> Dependency Injection (DI) is a commonly applied mechanism to decouple classes from their dependencies in order to provide better modularization of software. In the context of Java, the availability of a DI specification and popular frameworks, such as Spring, facilitate DI usage in software projects. However, bad DI implementation practices can have negative consequences, such as increasing coupling, hindering the achievement of DI's main goal. Even though the literature suggests the existence of DI anti-patterns, there is no detailed documentation of such bad practices. Moreover, there is no evidence on their occurrence and perceived usefulness from the developer's point of view. </p> <p><strong>Aims</strong> Our goal is to review the reported DI anti-patterns in order to analyze their completeness and to propose and evaluate a novel catalog of Java DI anti-patterns. </p> <p><strong>Method</strong> We propose a catalog containing twelve Java DI anti-patterns. We selected four open-source and two closed-source software projects that adopt a DI framework and developed a tool to statically analyze the occurrence of the candidate DI anti-patterns within their source code. Also, we conducted a survey through face to face interviews with three experienced developers that regularly apply DI. We extended the survey in order to gather the perception of a set of fifteen expert and novice developers through an online questionnaire. </p> <p><strong>Results</strong> At least nine different DI anti-patterns appeared frequently in the analyzed projects. In addition, the feedback received from the developers confirmed the relevance of the catalog. Besides, the respondents expressed their willingness to refactor instances of anti-patterns from source code.</p> <p><strong>Conclusions</strong> The catalog contains Java DI anti-patterns that occur in practice and are useful. Sharing it with practitioners may help them to avoid such anti-patterns.</p>
Supplementary material for "can you tell me if it smells? A study on how developers discuss code smells and anti-patterns in Stack Overflow"
<p>This dataset contains all data and results from the "Can you tell me if it smells? A study on how developers discuss code smells and anti-patterns in Stack Overflow" paper that was accepted at the 22nd International Conference on Evaluation andAssessment in Software Engineering (EASE), Christchurch, New Zealand.</p>
Replication Package for "Automated Reporting of Anti-Patterns and Decay in Continuous Integration"
<p>This is the replication package for the paper "Automated Reporting of Anti-Patterns and Decay in Continuous Integration" accepted for publication at <a href="https://2019.icse-conferences.org/track/icse-2019-Technical-Papers#event-overview">ICSE 2019 (Technical Track)</a>.</p> <p>We include all the artifacts necessary to replicate the results obtained in our paper. Specifically, we provide (i) all the scripts used to conduct our statistical tests and to process the data obtained from our surveys, (ii) the queries used to perform the project selection, (iii) and a runnable version of our CI anti-patterns detection tool along with the external source code used to quantify the presence of CI anti-patterns in our dataset.<br> Furthermore, we provide raw and processed data from our surveys and data (build logs and repositories) that can be used as input to our detection pipeline. We also include a Docker container image with a working environment containing the artifacts.</p> <p>Preprint of corresponding paper is available <a href="http://doi.org/10.5281/zenodo.2578271">here</a>.</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>
[GAS 2022] Software Project Management Anti-Patterns for Video Game Development
<p>This dataset contains an analysis of 440 project management problems described in game postmortems from gamedeveloper.com (formerly Gamasutra). We grouped these problems into candidate anti-patterns, an then we link these candidates with anti-patterns documented in the Software Engineering literature. Specifically, we aim to answer the following research question how video game anti-pattern fits into the software anti-patterns literature? </p>
DrAsync: Identifying and Visualizing Anti-Patterns inAsynchronous JavaScript [Anonymous Experimental Data]
<p>////////////////////////////////////<br> //</p> <p>This directory contains the raw data used to compute aggregate numbers in the paper.<br> There are five files, and 2 subdirectories:</p> <p>(1) apply_run_times: has the raw execution times of various calls to apply throughout vuepress' tests;</p> <p>(2) cpdir_run_times: has the raw execution times of calling cpDir on a large directory as part of the cpDir case study;</p> <p>(3) eleventy_test_executions: contains 50 run times x 2 (before, after refactoring) for eleventy's test suite;</p> <p>(4) promise_resolve_then_case_study: contains execution times for the code fragment from strapi's evaluate function;</p> <p>(5) vuepress_test_executions: contains 50 run times x 2 (before, after refactoring) for vuepress' test suite.</p> <p>For the subdirectories:</p> <p>(1) DynamicAndExecutedAntiPatterns: for each of 20 subject applications x for each of 8 anti-patterns, contains the number<br> of static occurences of anti-patterns which are executed, as well as how often.</p> <p>(2) StaticAntiPatterns: for each of 20 subject applications x for each of 8 anti-patterns, contains the number of static<br> occurrences of the anti-pattern. We further filtered this by discounting anti-patterns appearing<br> in test, generated, build, etc. directories with a separate command.</p> <p>////////////////////////////////////<br> //</p> <p>CodeQL queries for the anti-patterns are given in supplemental material (available on the submission form). <br> We will make the code for the visualization tool available as part of the artifact submission process if this paper is accepted.</p>
Detection of the Fire Drill anti-pattern: 15 real-world projects with ground truth, issue-tracking data, source code density, models and code
<p>This package contains artifacts for <strong>15</strong> real-world software projects. The data is supposed to aid the detection of the presence of the Fire Drill anti-pattern. We include original data, ground truth, code (experimental setups and models), and notebooks. The data supports two distinct methods of detecting the AP: a) through issue-tracking data, and b) through the underlying source code. This version of the dataset corresponds to <strong>v8</strong> of the <a href="https://arxiv.org/abs/2104.15090v8">technical report</a> and the <a href="https://github.com/MrShoenel/anti-pattern-models/releases/tag/arxiv-v8">GitHub repository</a>. The package includes the following:</p> <p>Original data:</p> <ul> <li>For each project, its <strong>original</strong> artifacts (e.g., wikis, meeting minutes, mentor's notes, etc.)</li> <li>Evaluation of raters' notes by the assessor</li> </ul> <p>Fire Drill in issue-tracking data:</p> <ul> <li><strong>Ground truth</strong> for whether and how strong each project exhibits the Fire Drill AP, on a scale from [0,10]. This was determined by two individual raters, who also reached a consensus.</li> <li>Coefficients for indicators for the first method, per project.</li> <li>Detailed issue-tracing data for each project: what occurred and when.</li> <li>Time logs for each project.</li> </ul> <p>Fire Drill in source-code data:</p> <ul> <li><strong>Four</strong> technical reports that document the developed method of how to translate a description into a detectable pattern, and to use the pattern to detect the presence and to score it (similar to the rating). Also includes a report for how activities were assigned to individual commits.</li> <li>Source code density data (metrics) for each commit in each of the nine projects as a separate dataset.</li> <li>Code: a snapshot of the repository that holds all code, models, notebooks, and pre-computed results, for utmost reproducibility (the code is written in R).</li> </ul>
Detecting microservice anti-patterns using interactive service call graphs: Effort Assessment
<p>Supplemental Figures for <em>Detecting microservice anti-patterns using interactive service call graphs: Effort Assessment</em></p>
Detecting microservice anti-patterns using interactive service call graphs: Effort Assessment
<p>Case Study Results for <em>Detecting microservice anti-patterns using interactive service call graphs: Effort Assessment</em></p>
A Large Scale Empirical Study of the Impact of Spaghetti Code and Blob Anti-patterns on Program Comprehension
<p>Dataset and scripts used for the paper.</p>
Principle-Driven Continuous Integration: Simplifying Failure Discovery and Raising Anti-Pattern Awareness (Appendix)
<p>Appendix to my thesis</p>
Effective Teaching through Code Reviews: Patterns and Anti-Patterns
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.