Unraveling the Mystery of Dupeguru's Inconsistent Duplicate Detection Results

When it comes to finding duplicate files on your computer, there are various tools available, each with its own strengths and weaknesses. One popular tool is Dupeguru, which uses SHA256 checksums to identify duplicate files. However, some users have reported inconsistent results when using this tool, particularly when comparing the results of multiple runs.

Recently, a user encountered an issue where Dupeguru was not finding duplicates despite running the same set of files through MD5 and obtaining similar results. The user noticed that each time they ran SHA256 against the folder, they were getting slightly different duplicate counts: 19668, 19204, 19671, 19675, 19669, and 19673.

To better understand what could be causing this inconsistency, it's essential to examine the factors involved in Dupeguru's duplicate detection process. One key difference between checksums and other methods of comparing files is that checksums are based on the actual contents of the files, whereas other methods might rely on metadata such as file name, size, or date.

In the case of TreeSize, which uses a SHA256 checksum to detect duplicates, it's possible that the tool is not correctly handling certain types of files. For instance, if you have files with identical names but different contents, Dupeguru may incorrectly identify them as duplicates.

Another factor to consider is the file structure and organization. In this case, the 20,000 files were pooled from multiple backup or archive sets located on different hard drives and are now stored in a single top-level folder. This could potentially cause issues with duplicate detection, particularly if some files have identical names but come from different sources.

The user's system specifications also play a role in the outcome. They are using a Surface Pro 6 i7 with Windows 10 Pro and 8 GB of RAM, which should be more than sufficient for running Dupeguru.

To resolve this issue, it may be helpful to try alternative duplicate detection tools or methods. For example, you could use a tool that uses a different checksum algorithm or one that relies on metadata such as file name, size, and date. Additionally, organizing your files in a more structured manner may help reduce the likelihood of inconsistent results.

In conclusion, while Dupeguru is a powerful tool for detecting duplicate files, it's not immune to inconsistencies. By understanding the factors involved in its duplicate detection process and exploring alternative methods and tools, you can improve the accuracy and reliability of your duplicate detection results.

Dupeguru not finding dupliucates