Improving Systems Reliability Through Record/Replay

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Software bugs significantly hamper software reliability leading to service outages, data loss, and security vulnerabilities. Unfortunately, most production software failures go undiagnosed. This occurs for two reasons. First, the sheer number of crashes in widely used software for example, Microsoft reported seeing over a million crashes a day in one recent publication and staff at Mozilla reported to us they see tens of thousands of crashes a day. Second, current crash reporting technologies, such as core dumps and stack traces, provide very little context. Consequently, automatically grouping (i.e., the set of crashes caused by the same bug), diagnosing (i.e., this is a concurrency bug, buffer overflow, etc.), and prioritizing bugs (i.e., whether a bug is potentially exploitable) has been impractical.To address this, we have been building a toolchain that allows developers to record and replay production applications, called Castor. Castor has several goals. First, we are attempting to provide a platform for application record/replay with low enough performance and space overhead to make it practical to leave on by default in production, capturing bugs when they occur. In prior work, we have shown that it is possible to record even the most demanding multi-core scientific and server workloads with CPU overheads of a few percent. Moving forward, we hope to demonstrate new techniques to achieve this with modest space overheads and explore new approaches to bug triage and diagnosis that this can enable.The primary objective of this research proposal is to improve developer tools such that no crash is left undiagnosed. We want to continue building on our record/replay work, improving its core capabilities in terms of usability, performance and space efficiency, and to use it in conjunction with dynamic analysis, program slicing, and other techniques to develop better tools for grouping, diagnosing and prioritizing bugs automatically.A secondary objective is to explore alternative uses of record/replay. First, we will study techniques to generate a cycle-accurate replay good enough for any performance analysis tools. Second, we want to investigate helping developers automatically create fault tolerant processes that support tolerating non-fail-stop errors. Related to this we can extend the ideas to make fault tolerant software robust to exploits with little to no overhead.This research program will contribute to my broader research goal of improving systems reliability in a world ever more dependent on computers. We will have the opportunity to make an impact in the way software is developed and maintained. It will also provide a rich training ground for HQP in a field that is in high demand in Canada.