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used for the website content itself. Please consult the terms and conditions of use for the website
directly.

GENERAL INFORMATION

1. Title of website:
	Github

2. Contributor information:
	Janaka Senanayake (Robert Gordon University; University of Kelaniya)
	Harsha Kalutarage (Robert Gordon University)
	Mhd Omar Al-Kadri (Birmingham City University)
	Luca Piras (Middlesex University)
	Andrei Petrovski (Robert Gordon University)
	
3. Date on which website first launched:
	2022-09-02
	

ACCESS INFORMATION

1. Access Links:
	Github: 
	https://github.com/softwaresec-labs/LVDAndro
	
	Internet Archive (Version dated 23.09.07):
	https://web.archive.org/web/20230907100039/https://github.com/softwaresec-labs/LVDAndro
	
	
2. Recommended citation:
	SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PIRAS, L. and PETROVSKI, A. 2023. Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models [LINK ONLY]. Hosted on GitHub (online). Available from: https://github.com/softwaresec-labs/LVDAndro
		
	
CONTEXTUAL INFORMATION

1. Abstract:
	Many of the Android apps get published without appropriate security considerations, possibly due to not verifying code or not identifying vulnerabilities at the early stages of development. This can be overcome by using an AI based model trained on a properlly labeled dataset. Hence, LVDAndro provides a dataset for Android source code vulnerabilities, labelled based on Common Weakness Enumeration (CWE). The dataset has been generated using code lines scanned from real-world Android apps containing a large amount of distinct source code samples. The dataset can be downloaded from the Dataset directory. There are 3 dataset folders and each contains a readme file with important details and links to download dataset stored in a Google Drive.