A sizeable empirical investigation of bug attributes in Blockchain structures

Blockchain systems' credibility is severely damaged by flaws. A thorough understanding of blockchain vulnerabilities is crucial for developing effective methods for preventing, detecting, and remediating them. In this study, we employ statistical methods to compare the bug populations of eight popular public blockchain projects. The first step is a human review of 500 bug reports to see what sorts of problems have been reported. Second, we utilize card sorting to divide the reported problems into seven distinct categories that can all be found in blockchain-based software. Here, we take a look at the many causes of errors in software development and programming. As a last step, we look at how different problems have different average timeframes to fix. The findings show that (1) conceptual defects are the most common type of real-time issue, (2) bug frequency distributions follow consistent patterns across applications and languages, (3) fixing security vulnerabilities takes the longest median time, and (37.33%) fixing performance bugs takes longer than a year.