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Creators/Authors contains: "Parikesit, Dimas"

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  1. ; (, ACM)
    Cloud systems constantly experience changes. Unfortunately, these changes often introduce regression failures, breaking the same features or functionalities repeatedly. Such failures disrupt cloud availability and waste developers' efforts in re-investigating similar incidents. In this position paper, we argue that regression failures can be effectively prevented by enforcing low-level semantics, a new class of intermediate rules empirically inferred from past incidents, yet capable of offering partial correctness guarantees. Our experience shows that such rules are valuable to strengthen system correctness guarantees and expose new bugs. 
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    Free, publicly-accessible full text available November 17, 2026
  2. ; ; ; ; ; ; ; ; ; (, 19th USENIX Symposium on Operating Systems Design and Implementation)
    Production distributed systems provide rich features, but various defects can cause a system to silently violate its semantics without explicit errors. Such failures cause serious consequences. Yet, they are extremely challenging to detect, as it requires deep domain knowledge and substantial manual efforts to write good checkers. In this paper, we explore a novel approach that directly derives semantic checkers from system test code. We first present a large-scale study on existing system test cases. Guided by the study findings, we develop T2C, a framework that uses static and dynamic analysis to transform and generalize a test into a runtime checker. We apply T2C on four large, popular distributed systems and successfully derive tens to hundreds of checkers. These checkers detect 15 out of 20 real-world silent failures we reproduce and incur small runtime overhead. 
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    Free, publicly-accessible full text available July 7, 2026
  3. ; ; ; ; ; ; ; ; ; (, 19th USENIX Symposium on Operating Systems Design and Implementation)
    Production distributed systems provide rich features, but various defects can cause a system to silently violate its semantics without explicit errors. Such failures cause serious consequences. Yet, they are extremely challenging to detect, as it requires deep domain knowledge and substantial manual efforts to write good checkers. In this paper, we explore a novel approach that directly derives semantic checkers from system test code. We first present a large-scale study on existing system test cases. Guided by the study findings, we develop T2C, a framework that uses static and dynamic analysis to transform and generalize a test into a runtime checker. We apply T2C on four large, popular distributed systems and successfully derive tens to hundreds of checkers. These checkers detect 15 out of 20 real-world silent failures we reproduce and incur small runtime overhead. 
    more » « less
    Free, publicly-accessible full text available July 7, 2026