Software defects that most likely will turn into system and/or business failures are termed critical by most stakeholders. Thus, having some warnings of the most probable location of such critical defects in a software system is crucial. Software complexity (e.g. coupling) has long been established to be associated with the number of defects. However, what is really challenging is not in the number but identifying the most severe defects that impact reliability. (Research Goal) Do cyclic related components account for a clear majority of the critical defects in software systems? (Approach) We have empirically evaluated two non-trivial systems. One commercial Smart Grid system developed with C# and an open source messaging and integrated pattern server developed with Java. By using cycle metrics, we mined the components into cyclic-related and non-cyclic related groups. Lastly, we evaluated the statistical significance of critical defects and severe defect-prone components (SDCs) in both groups. (Results) In these two systems, results demonstrated convincingly, that components in cyclic relationships account for a significant and the most critical defects and SDCs. (Discussion and Conclusion) We further identified a segment of a system with cyclic complexity that consist almost all of the critical defects and SDCs that impact on system's reliability. Such critical defects and the affected components should be focused for increased testing and refactoring possibilities.