The development and maintenance of large-scale critical software systems have become increasingly challenging due to the relentless pace of technological advancement and the growing demand for fault tolerance and resilience. Traditional software testing and maintenance methods often prove inadequate in ensuring the continuous operation of these systems. To address this challenge, this paper proposes a bioinspired approach based on the human immune system for autonomous self-repair in software systems. Using techniques such as probabilistic graph theory, anomaly detection, machine learning, and redundancy mechanisms, the proposed methodology aims to enable computational systems to exhibit self-awareness, damage assessment, and proactive recovery, thus achieving computational immortality. A comprehensive evaluation methodology, including various fault injection scenarios, metrics for damage resilience and perpetual testing, and comparative analyzes against traditional testing approaches, will be employed to assess the practical viability of this bioinspired approach in achieving fault-tolerant and perpetually operational software systems.