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📝 State/Status Segregation (S3) Pattern
Making Systems More Predictable by Separating Lifecycle from Context

🔍 In complex systems, mixing up state and status often leads to bloated models, fragile logic, and unpredictable behavior.

This paper, written by Masoud Bahrami, introduces the State/Status Segregation (S3) pattern, a modeling principle that cleanly separates lifecycle control (state) from contextual signals and side conditions (status).

❇️ By applying S3, you can design systems with clearer APIs, more predictable behavior, and codebases that are easier to test, evolve, and reason about.



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📝 State/Status Segregation (S3) Pattern
Making Systems More Predictable by Separating Lifecycle from Context

🔍 In complex systems, mixing up state and status often leads to bloated models, fragile logic, and unpredictable behavior.

This paper, written by Masoud Bahrami, introduces the State/Status Segregation (S3) pattern, a modeling principle that cleanly separates lifecycle control (state) from contextual signals and side conditions (status).

❇️ By applying S3, you can design systems with clearer APIs, more predictable behavior, and codebases that are easier to test, evolve, and reason about.

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