Abstract: A storage device controller includes drive controller circuitry configured to control writing and fetching of data from a storage medium, read data channel circuitry for interfacing between the drive controller circuitry and the storage medium, test controller circuitry configured to test the read data channel circuitry by issuing test commands simulating the writing and fetching of data from the storage medium, and selector circuitry configured to switchably couple the read data channel circuitry to the drive controller circuitry in an operating mode and to the test controller circuitry in a testing mode. The storage device controller may include a pattern generator configured to output the test commands. Processor circuitry may be configured to store test results in memory, to compute performance metrics from the stored test results, and communicate the performance metrics to a host device.

Abstract: Provided herein is a rapid lateral flow device for detection of a target analyte in a liquid biological sample comprising a membrane strip, the membrane strip including: a matrix; a conjugate pad having at least one reporter vitrified into the matrix; one or more test sites including a covalently or electrostatically bound capture agent vitrified into or onto the matrix; and, optionally, a control line including one or more capture agents vitrified into or onto the matrix. Also provided are methods of rapid detection of a target analyte in a liquid biological sample.

Abstract: A method and system are provided. The method includes performing, by a logs-to-time-series converter, a logs-to-time-series conversion by transforming a plurality of heterogeneous logs into a set of time series. Each of the heterogeneous logs includes a time stamp and text portion with one or more fields. The method further includes performing, by a time-series-to-sequential-pattern converter, a time-series-to-sequential-pattern conversion by mining invariant relationships between the set of time series, and discovering sequential message patterns and association rules in the plurality of heterogeneous logs using the invariant relationships. The method also includes executing, by a processor, a set of log management applications, based on the sequential message patterns and the association rules.

Abstract: Systems and methods are disclosed for detecting error in a cloud infrastructure by running a plurality of training tasks on the cloud infrastructure and generating training execution logs; generating a model miner with the training execution logs to represent one or more correct task executions in the cloud infrastructure; after training, running a plurality of tasks on the cloud infrastructure and capturing live execution logs; and from the live execution logs, if a current task deviates from the correct task execution, indicating an execution error for correction in real-time.

Abstract: Systems and methods are disclosed for detecting error in a cloud infrastructure by running a plurality of training tasks on the cloud infrastructure and generating training execution logs; generating a model miner with the training execution logs to represent one or more correct task executions in the cloud infrastructure; after training, running a plurality of tasks on the cloud infrastructure and capturing live execution logs; and from the live execution logs, if a current task deviates from the correct task execution, indicating an execution error for correction in real-time.

Abstract: A method and system are provided. The method includes performing, by a logs-to-time-series converter, a logs-to-time-series conversion by transforming a plurality of heterogeneous logs into a set of time series. Each of the heterogeneous logs includes a time stamp and text portion with one or more fields. The method further includes performing, by a time-series-to-sequential-pattern converter, a time-series-to-sequential-pattern conversion by mining invariant relationships between the set of time series, and discovering sequential message patterns and association rules in the plurality of heterogeneous logs using the invariant relationships. The method also includes executing, by a processor, a set of log management applications, based on the sequential message patterns and the association rules.

Abstract: Disclosed are a testing framework—SETSUD ?—that uses perturbation-based exploration for robustness testing of modern scalable distributed systems. In sharp contrast to existing testing techniques and tools that are limited in that they are typically based on black-box approaches or they focus mostly on failure recovery testing, SETSUD ? is a flexible framework to exercise various perturbations to create stressful scenarios. SETSUD ? is built on an underlying instrumentation infrastructure that provides abstractions of internal states of the system as labeled entities. Both novice and advanced testers can use these labeled entities to specify scenarios of interest at the high level, in the form of a declarative style test policy. SETSUD ? automatically generates perturbation sequences and applies them to system-level implementations, without burdening the tester with low-level details.