Robust distributed systems commonly employ high-level recovery mechanisms enabling the system to recover from a wide variety of problematic environmental conditions such as node failures, packet drops and link disconnections. Unfortunately, these recovery mechanisms also effectively mask additional serious design and implementation errors, disguising them as latent performance bugs that severely degrade end-to-end system performance. These bugs typically go unnoticed due to the challenge of distinguishing between a bug and an intermittent environmental condition that must be tolerated by the system. We present techniques that can automatically pinpoint latent performance bugs in systems implementations, in the spirit of recent advances in model checking by systematic state space exploration. The techniques proceed by automating the process of conducting random simulations, identifying performance anomalies, and analyzing anomalous executions to pinpoint the circumstances leading to performance degradation.By focusing our implementation on the MACE toolkit, MACEPC can be used to test our implementations directly, without modification. We have applied MACEPC to five thoroughly tested and trusted distributed systems implementations. MACEPC was able to find significant, previously unknown, long-standing performance bugs in each of the systems, and led to fixes that significantly improved the end-to-end performance of the systems.

Abstract.Recently, there has been much interest in multi-party session types (MPSTs) as a means of rigorously specifying protocols for interaction among multiple distributed participants. By capturing distributed interaction as series of typed interactions, MPSTs allow for the static verification of compliance of corresponding distributed object programs. We observe that explicit control flow information manifested by MPST opens intriguing avenues also for performance enhancements. In this paper, we present a session type assisted performance enhancement framework for distributed object interaction in Java. Experimental evaluation within our distributed runtime infrastructure illustrates the costs and benefits of our composable enhancement strategies.

No abstract

No abstract

No abstract