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Traditional serialized software systems (SerialSWs) process tasks sequentially, creating bottlenecks in throughput, fault tolerance, and scalability. This paper reviews modern alternatives, including event-driven architectures, actor-based concurrency, serverless computing, and dataflow programming. We analyze performance metrics, use cases, and migration strategies, concluding that while SerialSWs remain simple for linear workflows, new paradigms offer significant advantages for distributed, real-time applications. This paper reviews modern alternatives

| Limitation | Description | |------------|-------------| | Low concurrency | One operation blocks all others | | Scalability ceiling | Vertical scaling only (bigger servers) | | Fault propagation | One failed task halts the chain | | Resource underutilization | Idle cores waiting on serial dependencies |