The present disclosure relates to a verification apparatus for a vehicle-mounted control apparatus having a first program processing unit that executes a current program, based on an output of a sensor and outputs a processing result to an actuator unit. Because the verification apparatus has a second program processing unit that executes the current program and outputs a processing result, a third program processing unit that shares the output of the sensor unit with the second program processing unit and that executes a new program and outputs a processing result, and a comparison determination unit that compares the respective outputs, it is made possible to perform a regression test effective for the new program at low cost, without affecting operation of the vehicle-mounted control apparatus.

A method for validation and runtime estimation of a quantum algorithm includes receiving a quantum algorithm and simulating the quantum algorithm, the quantum algorithm forming a set of quantum gates. The method further includes analyzing a first set of parameters of the set of quantum gates and analyzing a second set of parameters of a set of qubits performing the set of quantum gates. The method further includes transforming, in response to determining at least one of the first set of parameters or the second set of parameters meets an acceptability criterion, the quantum algorithm into a second set of quantum gates.

A method for detecting a defect may include extracting, from application code and using a framework support specification corresponding to a framework, a framework interaction between the application code and the framework. The framework interaction specifies an object used by the application code and managed by the framework. The method may further include performing, using the framework interaction, a dynamic analysis of the application code to obtain a heap snapshot, performing, using the heap snapshot and the framework interaction, a static analysis of the application code, and detecting, by the static analysis, the defect.

A computer-implemented method, computer program product and computing system for receiving a complex task; processing the complex task to define a plurality of discrete tasks each having a discrete goal; executing the plurality of discrete tasks on a plurality of machine-accessible public computing platforms; determining if any of the plurality of discrete tasks failed to achieve its discrete goal; and if a specific discrete task failed to achieve its discrete goal, defining a substitute discrete task having a substitute discrete goal.

A monitoring and alerting system backed by a machine learning engine for anomaly detection and prediction of time series data indicative of health of an application, a system, an environment, or a person. Using any data of interest that is modeled into a time series known as times and values; comparing input data against learned previous patterns; predicting data; identifying anomalies; generating notifications or an alert identifying the deviation, and communicating the alert to users, applications, or devices, applying the action or health functions logic using the significance of the issue to modify/start/stop components of the system or application. The data is received via a metrics server and is cleaned into a unified format and passed through via streaming or push/pull mechanisms. Planned deviations are configured to prevent false positives. A variety of machine learning methods is used and the system has dual function components and disaster recovery.

Program analysis is provided. An intermediate representation of a program is generated. A set of structured inputs is provided to the program. The set of structured inputs are derived from the intermediate representation. The program is executed using the set of structured inputs. A set of action steps is performed in response to observing a violation of a policy during execution of the program using the structured inputs.

Disclosed are various embodiments for anti-pattern detection in extraction and deployment of a microservice. A software modernization service is executed to analyze a computing application to identify various applications. When one or more of the application components are specified to be extracted as an independently deployable subunit, anti-patterns associated with deployment of the independently deployable subunit are determined prior to extraction. Anti-patterns may include increases in execution time, bandwidth, network latency, central processing unit (CPU) usage, and memory usage among other anti-patterns. The independently deployable subunit is selectively deployed separate from the computing application based on the identified anti-patterns.

Techniques are disclosed for generating an execution plan for performing functional tests in a cloud-computing environment. Infrastructure resources and capabilities (e.g., system requirements) may be defined within an infrastructure object (e.g., a resource of a declarative infrastructure provisioner) that stores a code segment that implements the resource or capability. Metadata may be maintained that indicates what particular capabilities are applicable to each infrastructure resource. Using the metadata, the system can generate an execution plan by combining code segments for each resource with code segments defining each capability in accordance with the metadata. The execution plan may include programmatic instructions that, when executed, generate a set of test results. The system can execute instructions that cause the set of test results to be presented at a user device.

A computer-implemented method includes downloading respective instances of an enterprise mobile application to a plurality of mobile devices. The instances of the enterprise mobile applications, while executing on respective mobile devices, capture, for each session, a session log that includes indications of ordered user actions occurring during the session, and optionally time intervals between user actions and/or user attributes. Captured session logs stored at and are mined by one or more servers to discover a particular pattern or sequence of user actions that occurred across multiple, different user sessions. If the number and/or rate of occurrences of the particular pattern is greater than a threshold, a new test case corresponding to the pattern is automatically generated and added to a suite of test cases for the UI functionality of the enterprise mobile application. The updated test suite may be automatically executed on a test version of the enterprise mobile application.

Described is a computer-implemented method of reordering condition checks. Two or more condition checks in computer code that may be reordered within the code are identified. It is determined that the execution frequency of a later one of the condition checks is satisfied at a greater frequency than a preceding one of the condition checks. It is determined that there is an absence of side effects in the two or more condition checks. The values of the condition checks are propagated and abstract interpretation is performed on the values that are propagated. It is determined that the condition checks are exclusive of each other, and the condition checks are reordered within the computer code.