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Replication Package of the study "Automated Identification and Qualitative Characterization of Safety Concerns Reported in UAV Software Platforms"

Authors: Andrea Di Sorbo; Fiorella Zampetti; Corrado A. Visaggio; Massimiliano Di Penta; Sebastiano Panichella;

Replication Package of the study "Automated Identification and Qualitative Characterization of Safety Concerns Reported in UAV Software Platforms"

Abstract

Description of the Dataset of the work "Automated Identification and Qualitative Characterization of Safety Concerns Reported in UAV Software Platforms" "1_Safety-Dataset" folder: This folder contains the bugs data and row data of all analyzed projects. Specifically, this folder contains the following relevant entries - "bugs" folder: It contains the bugs of all analyzed projects (PX4-merged.json.gz, dDronin-merged.json.gz, ardupilot-merged.json.gz) - "Manual Validation": It report all row data concerning the manual analysis (validation done by the different evaluators, the reviewers, etc.) of all sentences extracted from the project issues - "Dataset-safety-bugs.csv": For all projects, it contains the raw data of the set of sentences classified as safety and non-safety related. "2_Scripts-and-generated-data (RQ1)" folder: This folder contains the scripts and code used to preprocess and analyze the issue data in the context of RQ1 Specifically, this folder contains the following relevant entries - "main-program.py" file: Main program executing all subscripts generating the data required for RQ1 (detailed in the following line) - "utilities.R" file: (Utility) R script containing relevant functions for pre-processing/indexing text and issue data - "1_Script-to-create-test-dataset.r" file: R script containing simple code for analyzing issue data - "2_MainScript.r" file: Main R program orchestrating the scripts "utilities.R" and "1_Script-to-create-test-dataset.r" execution - "files-setDirectory" folder: Folder where data are generated and stored from the "main-program.py" - "fasttext" folder: Folder where data used as input from fastText (by "main-program.py") are reported - "cross-project-analysis" folder: Folder with data used for the cross-project analysis "3_Results" folder: This folder contains the results, scripts and figures used to discuss results of the study. Specifically, this folder contains the following relevant entries - "RQ1" folder: This folder contains the results, scripts and figures used to discuss results of RQ1. - "RQ2" folder: This folder contains the results, scripts and Tables used to discuss results of RQ2.

ACKNOWLEDGMENTS We gratefully acknowledge the Horizon 2020 (EU Commission) support for the projects COSMOS (DevOps for Complex Cyberphysical Systems), Project No. 957254-COSMOS. CRediT authorship contribution statement: Andrea Di Sorbo. Conceptualization, Methodology, Investigation, Validation, Visualization, Data curation, Writing - original draft, Writing - review & editing, Project administration. Fiorella Zampetti. Conceptualization, Methodology, Investigation, Validation, Data curation, Formal analysis, Writing - original draft, Writing - review & editing. Corrado Aaron Visaggio. Conceptualization, Data Curation, Supervision. Massimiliano Di Penta. Conceptualization, Methodology, Investigation, Validation, Visualization, Data Curation, Formal analysis, Writing - original draft, Writing - review & editing, Supervision. Sebastiano Panichella. Conceptualization, Methodology, Investigation, Validation, Software, Data curation, Writing - original draft, Writing - review & editing, Project administration.

Keywords

Issue Management, Machine learning, Safety Issues, Unmanned Aerial Vehicles, Empirical study

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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