Microsoft Technology Licensing, LLC

International Business Machines Corporation

Sebastian Burckhardt

Madanlal S Musuvathi

Daniel Johannes Pieter Leijen

Craig Raymond Walters

Vesselina K Papazova

Arthur J O'Neill

Nikolai Tillmann

Jun Kato

Manuel Alfred Fahndrich

Jonathan Paul De Halleux

Michal J Moskal

Christopher William Dern

Roy Patrick Tan

Sean C McDirmid

Benjamin Paul Wood

Manuel A Faehndrich

Alexandro Baldassin

Pravesh Kumar Kothari

Santosh Ganapati Nagarakatte

An 'Eventually Consistent Sharing Model' provides various techniques for using 'revision diagrams' to determine both arbitration and visibility of changes or updates to shared data (e.g., data, databases, lists, etc.) without requiring a causally consistent partial order for visibility, and without requiring change or update timestamps for arbitration. In particular, the Eventually Consistent Sharing Model provides fork-join automata based on revision diagrams to track the forking and joining of data versions, thereby tracking updates made to replicas of that data by one or more sources. &#x201c;Cloud types&#x201d; are used to define a structure of the shared data that enables fully automatic conflict resolution when updating the shared data. These concepts enable mobile devices (or other computing devices that may periodically go &#x201c;offline&#x201d;) to share structured data in cloud-based environments in a manner that provides local data replicas for offline operation while guaranteeing eventually consistent convergence of the data replicas.

Eventually consistent storage and transactions in cloud based environment

Some implementations provide techniques and arrangements for interactive user interface operation and development. For instance, some implementations may generate a user interface data structure representing a user interface, the user interface data structure being generated based at least in part on state data and imperative programming code. Then, in response to a change in one of the imperative programming code or the state data, some implementations may update the user interface data structure and render an updated interactive graphical user interface based on the updated user interface data structure.

Interface development and operation

A 'Concurrent Sharing Model' provides a programming model based on revisions and isolation types for concurrent revisions of states, data, or variables shared between two or more concurrent tasks or programs. This model enables revisions of shared states, data, or variables to maintain determinacy despite nondeterministic scheduling between concurrent tasks or programs. More specifically, the Concurrent Sharing Model provides various techniques wherein shared states, data, or variables are conceptually replicated on forks, and only copied or written if necessary, then deterministically merged on joins such that concurrent tasks or programs can work with independent local copies of the shared states, data, or variables while ensuring automated conflict resolution. This model is applicable to a wide variety of system architectures, including applications that execute tasks on a CPU or GPU, applications that run, in full or in part, on multi-core processors without full shared-memory guarantees, and applications that run within cloud computing environments.

Deterministic sharing of data among concurrent tasks using pre-defined deterministic conflict resolution policies

Described is a probabilistic concurrency testing mechanism for testing a concurrent software program that provides a probabilistic guarantee of finding any concurrent software bug at or below a bug depth (that corresponds to a complexity level for finding the bug). A scheduler/algorithm inserts priority lowering points into the code and runs the highest priority thread based upon initially randomly distributed priorities. When that thread reaches a priority lowering point, its priority is lowered to a value associated (e.g., by random distribution) with that priority lowering point, whereby a different thread now has the currently highest priority. That thread is run until its priority is similarly lowered, and so on, whereby all schedules needed to find a concurrency bug are run.

Concurrency software testing with probabilistic bounds on finding bugs

A checking system is described for determining whether a component is thread safe in the course of interacting with two or threads in a client environment. The checking system uses a manual, automatic, or semi-automatic technique to generate a test. The checking system then defines a set of coarse-grained observations for the test, in which the component is assumed to exhibit linearizability when interacting with threads. The set of coarse-grained observations may include both complete and 'stuck' histories. The checking system then generates a set of fine-grained observations for the tests; here, the checking system makes no assumptions as to the linearizability of the component. The checking system identifies potential linearizability errors as those entries in the set of fine-grained observations that have no counterpart entries in the set of coarse-grained observations. The checking system may rely on a stateless model checking module to perform its functions.

Testing components for thread safety

A system and method capable of finding relaxed memory-model vulnerabilities in a computer program caused by running on a machine having a relaxed memory model. A relaxed memory model vulnerability in a computer program includes the presence of program executions that are not sequentially consistent. In one embodiment, non-sequentially consistent executions are detected by exploring sequentially consistent executions.

Technique for finding relaxed memory model vulnerabilities

A method and apparatus in which the observability of cross-invalidates requests within remote nodes is controlled at the time of a partial response generation, when a remote request initially checks/snoops the directory state of the remote node, but before such the time that the cross-invalidate request is actually sent to the processors on a given node. If all of the remote nodes in the system indicate that the cross-invalidates could be sent during an initial directory snoop, the requesting node is able to return full exclusivity to a given cache line to a requesting processor at the time when it receives all of the partial responses, instead of having to wait for the final responses from each of the remote nodes within the system.

Method and process for expediting the return of line exclusivity to a given processor through enhanced inter-node communications

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Sammamish, WA, United States of America

Sebastian Burckhardt