Microsoft Technology Licensing, LLC

Venkatesh-Prasad Ranganath

Ganesan Ramalingam

Kapil Vaswani

Pradip Harindran Vallathol

Randall Edward Aull

Sriram Kottarakurichi Rajamani

Piyush Goyal

Robert E Harris, Jr

Pankaj Bharti Gupta

David Lo

Jane Evguenia Lawrence

A 'Compatibility Tester' extracts observable behaviors from different system implementations (e.g., software, operating systems, device drivers, hardware interfaces, etc.), then performs compatibility testing via comparisons of the extracted behaviors. Traces (e.g., bus level signals between controllers and hardware devices or commands between software components) representing observable behaviors of different implementations of a system are captured. Temporal and structural rules are then mined from these traces. The mined rules (or a model constructed from those rules) are used by a 'Rule Checking' process that determines whether reference rules (mined from a known compatible system) are compatible with rules mined from test traces of a second system. Invalid rules are flagged as behavioral compatibility bugs. Alternately, the mined rules are used by a &#x201c;Rule Diffing&#x201d; process that performs set differencing of the behavioral and structural rules mined from the different system implementations, with differences between the systems flagged as behavioral compatibility bugs.

Compatibility testing using traces, linear temporal rules, and behavioral models

A temporal rule-based feature extraction system and method for extracting features from temporal-based rules satisfied by a trace. Once a temporal-based rule is found that is satisfied by the trace, then embodiments of the temporal rule-based feature extraction system and method leverage that rule to either use as a feature or to extract additional features. The extracted feature then is used to characterize the trace. Embodiments of the system include a feature definition module, which defines features based on the temporal-based rules satisfied by a trace, and a similarity measure module, which defines a similarity measure for the defined features. The defined features include both extrinsic features, which are based on extrinsic properties of the rule, and intrinsic features, which are based on intrinsic properties of the rule. The similarity module generates similarity measures that indicate the similarity of two traces.

Temporal rule-based feature definition and extraction

An event is described herein as being representable by a quantified abstraction of the event. The event includes at least one predicate, and the at least one predicate has at least one constant symbol corresponding thereto. An instance of the constant symbol corresponding to the event is identified, and the instance of the constant symbol is replaced by a free variable to obtain an abstracted predicate. Thus, a quantified abstraction of the event is composed as a pair: the abstracted predicate and a mapping between the free variable and an instance of the constant symbol that corresponds to the predicate. A data mining algorithm is executed over abstracted, quantified events to ascertain a correlation between the event and another event.

Abstracting events for data mining

Locks are used to protect variables. All variables protected by a lock are allocated on a page associated with a lock. When a thread (called the owner) acquires the lock, a local copy of the memory page containing the variable is created, the original memory page is protected, and all access of the variable in the owner thread is directed to the local copy. Upon releasing the lock, the changes from the local copy are carried over to the memory page and the memory page is unprotected. Any concurrent access of the variable by non-owner threads triggers an exception handler (due to the protection mechanism) and delays such an access until after the owner thread has finished accessing the variable.

System to reduce interference in concurrent programs

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Karnataka, India

Venkatesh-Prasad Ranganath