Abstract: A computer-implemented method for test case priority selection includes initiating execution of a set of test cases associated with a system under test. Further, the set of test cases are executed according to a first order of execution, and during the execution, at runtime a failing test case, from the set of test cases is determined. Further, at runtime, from the set of test cases, a subset of test cases that are not yet executed is identified. Further, at runtime, a priority value is assigned to each test case from the subset of test cases, the priority value based on a similarity of the test case with the failing test case. Further, at runtime, the set of test cases is reorganized to execute the subset of test cases in a second order of execution based on priority values that are assigned.

Abstract: According to one or more embodiments of the present invention, a computer-implemented method for machine code analysis includes executing a set of test cases associated with a software product. The method further includes determining a failing test case, from the set of test cases. The method further includes identifying a portion of a machine code of the software product, the portion of the machine code corresponding to the failing test case. The method further includes analyzing the portion of the machine code to identify a pattern of machine code causing the failing test case to fail. The method further includes searching the machine code of the software product to find the identified pattern of machine code.

Abstract: A method for assigning test case priority includes analyzing, based on a set of test vectors, one or more test cases from a set of test cases on source code to determine a particular combination of attribute values associated with the one or more analyzed test cases. The method further includes generating a priority value for each attribute in the determined particular combination of attribute values. A priority value for each of the analyzed one or more test cases is generated based on the generated priority values of the particular combination of attribute values associated with the analyzed one or more test cases.

Abstract: A method for assigning test case priority includes analyzing, based on a set of test vectors, one or more test cases from a set of test cases on source code to determine a particular combination of attribute values associated with the one or more analyzed test cases. The method further includes generating a priority value for each attribute in the determined particular combination of attribute values. A priority value for each of the analyzed one or more test cases is generated based on the generated priority values of the particular combination of attribute values associated with the analyzed one or more test cases.

Abstract: According to one or more embodiments of the present invention, a computer-implemented method for machine code analysis includes executing a set of test cases associated with a software product. The method further includes determining a failing test case, from the set of test cases. The method further includes identifying a portion of a machine code of the software product, the portion of the machine code corresponding to the failing test case. The method further includes analyzing the portion of the machine code to identify a pattern of machine code causing the failing test case to fail. The method further includes searching the machine code of the software product to find the identified pattern of machine code.

Abstract: A method for detecting and localizing a fault in a system under test (SUT) includes generating an initial set of test cases using combinatorics test design. The method further includes determining, based at least in part on a first set of execution results, a set of failing test cases. The method further includes determining, based on a machine learning model, a subset of false positives from the failing test cases. The method further includes generating a set of new test cases from a selected failing test case that is not in the subset of false positives. The method further includes executing the set of new test cases to obtain a second set of execution results, and localizing the fault based at least in part on the second set of execution results.

Abstract: A computer-implemented method for test case priority selection includes initiating execution of a set of test cases associated with a system under test. Further, the set of test cases are executed according to a first order of execution, and during the execution, at runtime a failing test case, from the set of test cases is determined. Further, at runtime, from the set of test cases, a subset of test cases that are not yet executed is identified. Further, at runtime, a priority value is assigned to each test case from the subset of test cases, the priority value based on a similarity of the test case with the failing test case. Further, at runtime, the set of test cases is reorganized to execute the subset of test cases in a second order of execution based on priority values that are assigned.

Abstract: A method for detecting and localizing a fault in a system under test (SUT) includes generating an initial set of test cases using combinatorics test design. The method further includes determining, based at least in part on a first set of execution results, a set of failing test cases. The method further includes determining, based on a machine learning model, a subset of false positives from the failing test cases. The method further includes generating a set of new test cases from a selected failing test case that is not in the subset of false positives. The method further includes executing the set of new test cases to obtain a second set of execution results, and localizing the fault based at least in part on the second set of execution results.

Abstract: Methods, systems, and devices for modifying default display configurations for objects in a user interface are described. A system may support automatically drawing objects in a user interface such that the objects do not overlap and are legible to a user. To draw the objects with no overlaps, the system may determine when objects overlap based on a sweep procedure that identifies locations of default positions for each object to be displayed in the user interface. If two objects are identified to overlap in both a first and a second dimension during the sweep procedure, the system may modify one of the objects to prevent the overlap. For example, the system may hide the object or may find a next best location to draw the object such that the objects no longer overlap. Performing the sweep procedure may reduce latency and processing resources needed to identify any overlapping objects.

Abstract: Methods, systems, and devices for modifying default display configurations for objects in a user interface are described. A system may support automatically drawing objects in a user interface such that the objects do not overlap and are legible to a user. To draw the objects with no overlaps, the system may determine when objects overlap based on a sweep procedure that identifies locations of default positions for each object to be displayed in the user interface. If two objects are identified to overlap in both a first and a second dimension during the sweep procedure, the system may modify one of the objects to prevent the overlap. For example, the system may hide the object or may find a next best location to draw the object such that the objects no longer overlap. Performing the sweep procedure may reduce latency and processing resources needed to identify any overlapping objects.

Abstract: Systems, methods and computer program products, implementing techniques for automatic data acquisition and the real-time display of automatically acquired data. A system implementing the techniques includes one or more automatic data acquisition devices that emit data; and a data integration system that receives data from the automatic data acquisition devices and processes the data. The data integration system includes a display system for displaying the data to a user. The display system is operable to generate a graphical display and to update the graphical display automatically and only when new data from the automatic data acquisition devices is available. The display system is operable to update only affected parts of the graphical display but not necessarily the entire display.

Abstract: A system for generating an e-seal for a container includes a sensor to detect a condition associated with the container and to generate a sensor reading based on the condition, and a processing device to generate the e-seal based on the sensor reading. The sensor reading may include first and second readings from the sensor, where the first reading is recorded at a first time and the second reading is recorded at a second time.

Abstract: A service repository is used to store at least one service in association with service metadata describing service requirements of the service. The service repository also may store one or more platform-specific service executables. A service mapper is used to determine device metadata associated with each of a plurality of devices, where the device metadata provides device characteristics of the devices. The service mapper may thus map the service to a selected device of the plurality of devices for deployment thereon, based on a matching of corresponding elements of the service requirements and the device characteristics. The service mapper also may re-map the service between devices to maintain a quality and reliability of the service.

Abstract: A service repository is used to store at least one service in association with service metadata describing service requirements of the service. The service repository also may store one or more platform-specific service executables. A service mapper is used to determine device metadata associated with each of a plurality of devices, where the device metadata provides device characteristics of the devices. The service mapper may thus map the service to a selected device of the plurality of devices for deployment thereon, based on a matching of corresponding elements of the service requirements and the device characteristics. The service mapper also may re-map the service between devices to maintain a quality and reliability of the service.

Abstract: A trenched field effect transistor is provided that includes (a) a semiconductor substrate, (b) a trench extending a predetermined depth into the semiconductor substrate, (c) a pair of doped source junctions, positioned on opposite sides of the trench, (d) a doped heavy body positioned adjacent each source junction on the opposite side of the source junction from the trench, the deepest portion of the heavy body extending less deeply into said semiconductor substrate than the predetermined depth of the trench, and (e) a doped well surrounding the heavy body beneath the heavy body.

Abstract: An auto-identification system is described that includes a plurality of distributed auto-id nodes that are operable to track physical objects as they move through an operation of an enterprise, such as, for example, a supply chain network or a sales network. The auto-id nodes are distributed across sites of the network, and are in communication with enterprise application systems and/or data acquisition systems such as RFID readers or sensor devices. By focusing on their respective sites, the auto-id nodes minimize the amount of data tracked by their respective enterprise applications. Further, the auto-id nodes include rules governing operations on the physical object(s). When an auto-id node receives information regarding a tracking event experienced by the physical object, then the rules may be executed to access known data regarding the physical object, and thereby determine whether the tracking event matches an event that was expected to occur as a result of the operation of the enterprise.

Abstract: Systems, methods and computer program products for generic device integration within an auto-id system. The system includes an auto-id node operable to collect data emitted by one or more automatic data acquisition devices, process the data, and make the data available to one or more enterprise applications, user interfaces, or other auto-id nodes. The auto-id node includes a device integration layer that is operable to handle communication between the auto-id node and different types of automatic data acquisition devices, device controllers, or device management systems.

Abstract: There are methods and apparatus, including computer program products, for sensor node management. The methods and apparatus may include the ability to receive a message indicating that a sensor node is active, determine the type of data generated by the sensor node, and designate a location to store the type of data. The methods and apparatus may also include the ability to determine a transformation for generating a seal condition based on the type of data.

Abstract: A method of graphically representing management of goods in a supply chain includes receiving goods management data in a computer system from participants in a supply chain, the goods management data being sent upon the participants managing individual goods, and generating a graph in the computer system using the goods management data, the graph showing the management of the individual goods over time. A computer-implemented tool may generate a display area that shows the management of individual goods over time by the participants. The goods management may be graphically represented as cumulative curves. Curves may be shifted, cleansed or predicted. The tool may identify problems in the supply chain.

Abstract: Methods and apparatus, including computer program products, for processing, at a sensor node within a sensor network, a set of sensor readings to determine whether an event has occurred, the set of sensor readings including one or more sensor readings for corresponding environmental conditions. The processing includes determining whether a sensor reading exceeds its corresponding threshold value for an environmental condition, and if so, comparing the set of sensor readings with a history log file to determine whether a false alarm event has occurred. The history log file includes one or more sets of historic sensor readings for corresponding environmental conditions, each set being associated with an environmental situation.