COMPUTER ENGG DOMAIN
Published July 31, 2025 | Version v1
Journal article Open

Duplicate File Remover with Smart UI

Description

Duplicate files are prevalent in today's computer systems, particularly when users deal with large amounts of data through downloads, backups, file transfers, or content editing. Not only do these duplicates take up precious storage space, but they also clog directories, slow down productivity, and can cause confusion or the use of old files. Identifying and deleting duplicate files manually can be time-consuming, error-prone, and tedious. This project offers a complete solution via a Python application with a smart, intuitive Graphical User Interface (GUI) crafted with Tkinter. The program scans directories efficiently, recursively examines file content via size filters and MD5 hash comparison, and correctly detects duplicates irrespective of filename or metadata. It offers users several management choices such as selective deletion and overall cleanup of duplicate files. Moreover, it also features a lively, user-friendly interface with contemporary UX concepts to make it accessible both for technical and non-technical users. This utility optimizes system performance, enriches data organization, and offers a safe method of conducting digital hygiene with ease.

Files

Duplicate File Remover with Smart UI.pdf

Files (266.6 kB)

Name Size
md5:ae0f686a603bbe1a23212df91f6bfaaf
266.6 kB Preview Download

Additional details

References

  • 1. Efficient duplicate file detection using hashing techniques. (2018). International Journal of Computer Applications, 182(12), July 2018
  • 2. Detection and removal of duplicate files in storage systems: An approach based on file similarity and hash functions. (2020). IEEE Access.
  • 3. Lee, M., & Seo, M. (2023). Secure and efficient deduplication for cloud storage with dynamic ownership management. Applied Sciences, 13(24), 13270. https://doi.org/10.3390/app132413270
  • 4. Joshi, K., & Mamta. (n.d.). Duplicate file detection and elimination. International Journal of Scientific Research in Computer Science, Engineering and Information Technology.
  • 5. Alsulami, B. S., Abulkhair, M. F., & Eassa, F. E. (2012). Near duplicate document detection survey. International Journal of Computer Science & Communication Networks, 2(2), 147–151.
  • 6. Kakariya, G., & Rangdale, S. (2014). A hybrid cloud approach for secure authorized deduplication. International Journal of Computer Engineering and Applications, 8(1), October 2014.