Microsoft Technology Licensing, LLC

Jean-Philippe Martin

Manuel Costa

Miguel Castro

Marcus Peinado

Michael Isard

Richard John Black

Austin N Donnelly

Paul Barham

Christopher John Rossbach

Periklis Akritidis

Computations are performed on shared datasets in a distributed computing cluster using aggressive speculation and a distributed runtime that executes code transactionally. Speculative transactions are conducted with currently available data on the assumption that no dependencies exist that will render the input data invalid. For those specific instances where this assumption is found to be incorrect&#x2014;that the input data did indeed have a dependency (thereby impacting the correctness of the speculated transaction)&#x2014;the speculated transaction is aborted and its results (and all transactions that relied on its results) are rolled-back accordingly for re-computation using updated input data. In operation, shared state data is read and written using only the system's data access API which ensures that computations can be rolled-back when conflicts stemming from later-determined dependencies are detected.

Transactional computation on clusters

Software fault isolation methods using byte-granularity memory protection are described. In an embodiment, untrusted drivers or other extensions to a software system are run in a separate domain from the host portion of the software system, but share the same address space as the host portion. Calls between domains are mediated using an interposition library and access control data is maintained for substantially each byte of relevant virtual address space. Instrumentation added to the untrusted extension at compile-time, before load-time, or at runtime and added by the interposition library enforces the isolation between domains, for example by adding access right checks before any writes or indirect calls and by redirecting function calls to call wrappers in the interposition library. The instrumentation also updates the access control data to grant and revoke access rights on a fine granularity according to the semantics of the operation being invoked.

Software fault isolation using byte-granularity memory protection

Methods and apparatus for generating error reports with enhanced privacy are described. In an embodiment the error is triggered by an input to a software program. An error report is generated by identifying conditions on an input to the program which ensure that, for any input which satisfies the conditions, the software program will follow the same execution path such that the error can be reproduced. The error report may include these conditions or may include a new input generated using the conditions.

Privacy enhanced error reports

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Mountain View, WA, United States of America

Jean-Philippe Martin