Abstract: One or more systems, devices, computer program products and/or computer-implemented methods provided herein relate to data drift detection in an edge device. A system can comprise a memory configured to store computer executable components; and a processor configured to execute the computer executable components stored in the memory, wherein the computer executable components can comprise a verification component that can verify accuracy of a first model and accuracy of a second model to detect data drift associated with an edge device that is deployed without network connectivity; a computation component that can compute at least a first ratio based on the accuracy of the first model and the accuracy of the second model; and an analysis component that can use the at least the first ratio to determine whether performance degradation of at least one of the first model or the second model is a function of the data drift.

Abstract: Aspects include receiving a notification that a value of a data element stored in a source storage location in a source format has been changed to an updated value. The change is replicated to a plurality of target storage locations. The replicating includes, for each of the plurality of target storage locations, determining a target format of the data element in the target storage location. The target format is one of a plurality of different formats, including the source format. Each of the different formats provide a different level of data protection for the data element. In response to determining that the target format is not the same as the source format, the updated value of the data element is converted into the target format, and the updated value of the data element is stored in the target format at the target storage location.

Abstract: Approaches presented herein enable determining an optimal set of machine learning algorithms for use in an artificial neural network. More specifically, a plurality of artificial neural networks is trained using a training data set. Each of the plurality of artificial neural networks has a respective unique architecture that comprises a combination of hidden layers, artificial neurons, and machine learning algorithms. Respective prediction rates of each of the plurality of artificial neural networks are compared. A best predictor artificial neural network of the plurality of artificial neural networks is identified, such that the best predictor artificial neural network has a prediction rate which is the most accurate of the respective prediction rates based on the comparing. A set of one or more machine learning algorithms used in the best predictor artificial neural network is determined.

Abstract: A described method includes receiving, by a database system, an instruction to change a first data element in a table in a database, which includes a first copy and a second copy of the table. A first entry is created in a first change-table. The first entry includes an updated value for a first data element. A second entry is created in a second change-table. Creating the second entry includes, changing the updated value into a ciphertext if the first data element is secured, and storing the ciphertext into the second entry. If the first data element is non-secured, the updated value is stored into the second entry as is. The second copy of the table is modified using the second change-table. The second copy of the table is used to respond to subsequent queries.

Abstract: Aspects of the invention include mutating each neural network of a portion of a first array of neural networks, wherein each neural network of the first array of neural networks is configured to select a respective sequence of test cases for testing a computing infrastructure. Causing each neural network of a second array of neural networks to select a respective sequence of test cases for testing the computing infrastructure. Generating a child neural network by performing a crossover operation between a mutated neural network of the portion of the first array and a neural network of the second array of neural networks, the child neural network generating a new sequence of test cases for testing the computing infrastructure.

Abstract: Techniques for an expertise score vector for software component management are described herein. An aspect includes determining a size and an amount of time corresponding to committed code contributed by a first developer to a first software component. Another aspect includes determining a time per unit of contribution based on the size and amount of time. Another aspect includes updating component mastery metrics corresponding to the first software component in an expertise score vector corresponding to the first developer based on the time per unit of contribution. Another aspect includes assigning the first developer to a developer tier based on the component mastery metrics. Another aspect includes assigning a work item corresponding to the first software component to the first developer based on the developer tier.

Abstract: Aspects of the invention include receiving a notification that a first logical grouping of code segments of a software application is being changed. Comparing the first logical grouping to a second logical grouping of code segments from a change history of the software application, where the first logical grouping and the second logical grouping both relate to resolving a common software application issue, and where the first logical grouping and the second logical grouping include at least one common code segment. Identifying a first code segment of the first logical grouping that is different from a second code segment of the second logical grouping. Determining that given the at least one code segment is changed a probability that the second code segment has been changed is greater than an threshold value. Sending a notification based on the difference in the probabilities being greater than a threshold value.

Abstract: Aspects include receiving a notification that a value of a data element stored in a source storage location in a source format has been changed to an updated value. The change is replicated to a plurality of target storage locations. The replicating includes, for each of the plurality of target storage locations, determining a target format of the data element in the target storage location. The target format is one of a plurality of different formats, including the source format. Each of the different formats provide a different level of data protection for the data element. In response to determining that the target format is not the same as the source format, the updated value of the data element is converted into the target format, and the updated value of the data element is stored in the target format at the target storage location.

Abstract: Aspects of the invention include receiving a new problem record. A corpus of existing problem records that were previously assigned to problem record owners and grouped into documents based on their assigned problem record owners is accessed. Each document in the corpus has an assigned problem record owner. A document in the corpus that is most similar to the new problem record is identified. The identifying includes comparing text in the new problem record to text in the documents. The new problem record is assigned to the problem record owner that is assigned to the identified document.

Abstract: A described method includes receiving, by a database system, an instruction to change a first data element in a table in a database, which includes a first copy and a second copy of the table. A first entry is created in a first change-table. The first entry includes an updated value for a first data element. A second entry is created in a second change-table. Creating the second entry includes, changing the updated value into a ciphertext if the first data element is secured, and storing the ciphertext into the second entry. If the first data element is non-secured, the updated value is stored into the second entry as is. The second copy of the table is modified using the second change-table. The second copy of the table is used to respond to subsequent queries.

Abstract: Aspects of the invention include receiving, by a processor, a request to copy a code from a source file and receiving, by the processor, a request to paste the code into a destination file. Aspects also include creating, by the processor based at least in part on the request to paste the code, an entry in a database, the entry having an identification of the source file, an identification of the destination file, a location of the code in the source file, and a location of the code in the destination file.

Abstract: Aspects of the invention include receiving system data associated with a software application running on a first system, the system data comprising system environment data captured during execution of the software application on the first system, determining one or more hidden inputs of an environment of the first system during execution of the software application, the determining based at least in part on the system environment data, and re-creating the environment of the first system during execution of the software application on a second system, the re-creating based at least in part on the one or more hidden inputs.

Abstract: Aspects of the invention include receiving, by a processor, a request to copy a code from a source file and receiving, by the processor, a request to paste the code into a destination file. Aspects also include creating, by the processor based at least in part on the request to paste the code, an entry in a database, the entry having an identification of the source file, an identification of the destination file, a location of the code in the source file, and a location of the code in the destination file.

Abstract: Techniques for an expertise score vector for software component management are described herein. An aspect includes determining a size and an amount of time corresponding to committed code contributed by a first developer to a first software component. Another aspect includes determining a time per unit of contribution based on the size and amount of time. Another aspect includes updating component mastery metrics corresponding to the first software component in an expertise score vector corresponding to the first developer based on the time per unit of contribution. Another aspect includes assigning the first developer to a developer tier based on the component mastery metrics. Another aspect includes assigning a work item corresponding to the first software component to the first developer based on the developer tier.

Abstract: Techniques for problem record management using an expertise score vector for software component management are described herein. An aspect includes receiving a problem record associated with a first work item of a software component, the first work item being associated with a first developer. Another aspect includes creating a second work item corresponding to the problem record. Another aspect includes assigning the second work item to a second developer. Another aspect includes determining that computer code from the second developer resolves the problem record. Another aspect includes, based on determining that the problem record is resolved, increasing an expertise score of the second developer.

Abstract: Techniques for an expertise score vector for software component management are described herein. An aspect includes maintaining a plurality of metrics in an expertise score vector corresponding to a developer. Another aspect includes identifying a subset of the plurality of metrics that are relevant to a work item corresponding to a software component. Another aspect includes applying respective weights to the subset of the plurality of metrics. Another aspect includes determining an expertise score for the developer based on the weighted subset of the plurality of metrics, wherein determining the expertise score comprises determining a magnitude of a vector comprising the weighted subset of the plurality of metrics. Another aspect includes assigning the work item to the developer based on the expertise score.

Abstract: Techniques for expertise score vector based work item assignment for software component management are described herein. An aspect includes receiving a problem record corresponding to a software component. Another aspect includes determining a work item corresponding to the problem record. Another aspect includes assigning the work item to a developer based on an expertise score vector of the developer.

Abstract: Aspects of the invention include receiving a new problem record. A corpus of existing problem records that were previously assigned to problem record owners and grouped into documents based on their assigned problem record owners is accessed. Each document in the corpus has an assigned problem record owner. A document in the corpus that is most similar to the new problem record is identified. The identifying includes comparing text in the new problem record to text in the documents. The new problem record is assigned to the problem record owner that is assigned to the identified document.