📝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.
📝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.
BY کانال مکتبخانه DDD
Warning: Undefined variable $i in /var/www/tg-me/post.php on line 283
The Singapore stock market has alternated between positive and negative finishes through the last five trading days since the end of the two-day winning streak in which it had added more than a dozen points or 0.4 percent. The Straits Times Index now sits just above the 3,060-point plateau and it's likely to see a narrow trading range on Monday.
Dump Scam in Leaked Telegram Chat
A leaked Telegram discussion by 50 so-called crypto influencers has exposed the extraordinary steps they take in order to profit on the back off unsuspecting defi investors. According to a leaked screenshot of the chat, an elaborate plan to defraud defi investors using the worthless “$Few” tokens had been hatched. $Few tokens would be airdropped to some of the influencers who in turn promoted these to unsuspecting followers on Twitter.
