The disclosed technology teaches correctly assembling a sequence of components for interacting with a user, including providing a sequence setup GUI with components that accept inputs and have input chain dependencies and outputs. The GUI supports construction of an executable sequence by connecting at least five of the components in a directed graph and tracing multiple paths through the components in the directed graph, resulting from at least one conditional branch at a first component, as the components are connected in the directed graph. Also taught is testing whether input chain dependencies of components under evaluation are satisfied when the components are invoked following any of the multiple paths and locating at least one error in use of a second component that results from failure to satisfy the input chain dependencies of the second component and reporting the error to a user, before executing the sequence and causing the error.

Methods for intelligent automatic merging of source control queue items are performed by systems and apparatuses. Project changes are submitted in build requests to a gated check-in build queue requiring successful builds to commit changes to a code repository according to source control. Multiple pending build requests in the build queue are intelligently and automatically merged into a single, pending merged request based on risk factor values associated with the build requests. For merged requests successfully built, files in the build requests are committed and the build requests are removed from the queue. Merged requests unsuccessfully built are divided into equal subsets based on updated risk factor values using information from the unsuccessful build. Successful builds of subsets allow for committing of files and removal from the build queue, while unsuccessful builds are further divided and processed until single build requests are processed to identify root cause errors.

The invention relates to a method for testing control software of a control device, the control device providing data streams (12) for evaluation, said method having the steps of: —generating a first and a second tree structure for displaying the data streams (12) in a display region in a table-like arrangement (10) having a plurality of rows (14) and a plurality of columns (16), wherein —the first tree structure comprises a first multidimensional list, —the first multidimensional list comprises a plurality of row element lists, —the row element lists comprise a plurality of elements (20), —each element (20) can be linked in the row element list to a data stream (12), —the element (20) specifies the column (16) in which the data stream (12) to which the element (20) can be linked is displayed; wherein —the second tree structure comprises a second multidimensional list, —the second multidimensional list comprises a plurality of column element lists, —the column element lists comprise the plurality of elements (20), —the element (20) specifies the row (14) in which the data stream (12) to which the element (20) can be linked is displayed; and —displaying the data streams (12) on the basis of the first and second tree structures.

A code development engine can be programmed to evaluate build code that can be representative of program code at an instance of time during or after a software development of the program code to identify and correct coding errors in the build code. A code run-time simulation engine can be programmed to simulate the build code in a modeled program code environment for the program code to identify and correct coding failures in the build code. A build code output module can be programmed to evaluate the build code to determine whether the build code is acceptable for use in a program code environment based on a level of acceptable risk for the build code in response to the coding error and/or coding failure being corrected in the build code.

Indications of a plurality of events whose occurrence is detected in a particular execution of a program are obtained. One or more partitions of a trace object corresponding to the execution are constructed, including a first partition corresponding to a first subset of the events. The first partition comprises a header portion which includes a compressed representation of one or more event chains, and a data portion comprising a compressed events record indicating an occurrence, during the execution, of a particular sequence of events indicated by an event chain. The trace object is stored.

Indications of a plurality of events whose occurrence is detected in a particular execution of a program are obtained. One or more partitions of a trace object corresponding to the execution are constructed, including a first partition corresponding to a first subset of the events. The first partition comprises a header portion which includes a compressed representation of one or more event chains, and a data portion comprising a compressed events record indicating an occurrence, during the execution, of a particular sequence of events indicated by an event chain. The trace object is stored.

A simulation test is run on a first machine learning model trained using first training data historically collected over a time period. The first training data includes a set of training inputs and a set of target outputs. In response to a determination that a result of the simulation test run on the first machine learning model satisfies one or more criteria, a size of the set of target outputs of the first training data is determined. Second training data for training a second machine learning model is obtained. A size of a set of target outputs of the second training data meets or exceeds the size of the target outputs of the first training data. The second machine learning model is trained using the second training data.

A method to a computer program containing instructions and to a module for monitoring a component of a control system for a transport. In a first step, a function call is sent to the component to execute a function used by the component using defined input data. Then a response from the component to the function call is received. The response is subsequently compared with an expected response. Finally, an action is performed in response to a result of the comparison.

Traditionally, when a feature is updated or a new feature is released, the feature undergoes internal testing and validation before external distribution. However, some features may receive proportionately less internal usage than customer usage reflected externally. Low internal usage of features can lead to weak telemetry data, which can allow code regressions (e.g., bugs) to go undetected until the features are released to customers. Accordingly, accelerated internal feature usage is provided to mirror external customer usage. Highly used features are dynamically identified and, any deficiencies in internal feature usage are identified. Tenant sites estimated to generate at least a portion of the deficiency in feature usage are identified. These sites may be migrated or replicated to internal validation rings to generate additional internal feature usage. By increasing internal testing and validation, the stability and reliability of feature releases are increased, thereby improving customer experience and satisfaction with the software product.

Systems and methods are disclosed for automating and monitoring software development operations. The systems may facilitate a user to submit a request to receive information related to a software application development across a development operations (DevOps) pipeline, and to efficiently receive an accurate response to the request. A natural language processing application may use query parameters from the request to form a query. The query may be sent to an artificial intelligence markup language (AIML) interpreter to retrieve the requested information from a database. Alternatively or additionally, the query may be sent to an application associated with an integration of a plurality of DevOps tools in the DevOps pipeline. The application may develop a dynamic response to the request.