On the Executability of R Markdown Files
R Markdown files are examples of literate programming documents that combine R code with results and explanations. Such dynamic documents are designed to execute easily and reproduce study results. However, little is known about the executability of R Markdown files which can cause frustration among its users who intend to reuse the document. This paper presents a large-scale study on the executability of R Markdown files collected from GitHub. Results from our study show that a significant number of R Markdown files (64.95%) are not executable, even after our best efforts. To better understand the challenges, we categorize the exceptions encountered while executing the documents into different categories. Finally, we develop a classifier to determine which Markdown files are likely to be executable. Such a classifier can be utilized by search engines in their ranking that help developers to find literate programming documents as learning resources.
Mon 15 AprDisplayed time zone: Lisbon change
14:00 - 15:30 | Software QualityTechnical Papers / Registered Reports / Data and Tool Showcase Track at Grande Auditório Chair(s): Gopi Krishnan Rajbahadur Centre for Software Excellence, Huawei, Canada | ||
14:00 12mTalk | Not all Dockerfile Smells are the Same: An Empirical Evaluation of Hadolint Writing Practices by Experts Technical Papers Giovanni Rosa University of Molise, Simone Scalabrino University of Molise, Gregorio Robles Universidad Rey Juan Carlos, Rocco Oliveto University of Molise | ||
14:12 12mTalk | Supporting High-Level to Low-Level Requirements Coverage Reviewing with Large Language Models Technical Papers Anamaria-Roberta Hartl Johannes Kepler University Linz, Christoph Mayr-Dorn JOHANNES KEPLER UNIVERSITY LINZ, Atif Mashkoor Johannes Kepler University Linz, Alexander Egyed Johannes Kepler University Linz DOI Authorizer link Pre-print | ||
14:24 12mTalk | On the Executability of R Markdown Files Technical Papers Md Anaytul Islam Lakehead University, Muhammad Asaduzzman University of Windsor, Shaowei Wang Department of Computer Science, University of Manitoba, Canada | ||
14:36 12mTalk | APIstic: A Large Collection of OpenAPI Metrics Technical Papers souhaila serbout Software Institute @ USI, Cesare Pautasso Software Institute, Faculty of Informatics, USI Lugano | ||
14:48 6mTalk | Improving Automated Code Reviews: Learning From Experience Technical Papers Hong Yi Lin The University of Melbourne, Patanamon Thongtanunam University of Melbourne, Christoph Treude Singapore Management University, Wachiraphan (Ping) Charoenwet The University of Melbourne | ||
14:55 4mTalk | Multi-faceted Code Smell Detection at Scale using DesigniteJava 2.0 Data and Tool Showcase Track Tushar Sharma Dalhousie University Pre-print | ||
14:59 4mTalk | SATDAUG - A Balanced and Augmented Dataset for Detecting Self-Admitted Technical Debt Data and Tool Showcase Track Edi Sutoyo Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Andrea Capiluppi University of Groningen | ||
15:03 4mTalk | Curated Email-Based Code Reviews Datasets Data and Tool Showcase Track Mingzhao Liang The University of Melbourne, Wachiraphan (Ping) Charoenwet The University of Melbourne, Patanamon Thongtanunam University of Melbourne | ||
15:07 4mTalk | TestDossier: A Dataset of Tested Values Automatically Extracted from Test Execution Data and Tool Showcase Track Andre Hora UFMG Pre-print Media Attached | ||
15:11 4mTalk | Greenlight: Highlighting TensorFlow APIs Energy Footprint Data and Tool Showcase Track Saurabhsingh Rajput Dalhousie University, Maria Kechagia University College London, Federica Sarro University College London, Tushar Sharma Dalhousie University Pre-print | ||
15:15 5mTalk | When Code Smells Meet ML: On the Lifecycle of ML-specific Code Smells in ML-enabled Systems Registered Reports Gilberto Recupito University of Salerno, Giammaria Giordano University of Salerno, Filomena Ferrucci University of Salerno, Dario Di Nucci University of Salerno, Fabio Palomba University of Salerno | ||
15:20 5mTalk | Comparison of Static Analysis Architecture Recovery Tools for Microservice Applications Registered Reports Simon Schneider Hamburg University of Technology, Alexander Bakhtin University of Oulu, Xiaozhou Li University of Oulu, Jacopo Soldani University of Pisa, Italy, Antonio Brogi Università di Pisa, Tomas Cerny University of Arizona, Riccardo Scandariato Hamburg University of Technology, Davide Taibi University of Oulu and Tampere University |