Abstract: Embodiments include methods and systems for configuring a dashboard with a plurality of components. Data sets populated by a plurality of data attributes and associated data attribute values can be received, where the dashboard is configured to display data from the data sets. A plurality of components can be provided on the dashboard including a guided discovery component that displays suggested filters for the dashboard according to one or more of the received data sets. A selection of a filter for the dashboard can be received at one of the components and the components can be dynamically filtered based on the received filter. The suggested filters displayed by the guided discovery component can also be dynamically adjusted based on the received filter, where one or more suggested filters are dynamically hidden and one or more suggested filters are dynamically displayed based on the received filter.

Abstract: Techniques for tracing attributes through queries in a set of nested queries are disclosed. A graphical user interface displays individual sub-queries as separate visual representations. Based on detecting a selection, a system analyzes data underlying the visual representations to identify queries, among the set of nested queries, that are associated with a particular attribute. One selection results in the system analyzing the underlying data to identify an origin query for an attribute, from among the set of nested queries. Another selection results in the system analyzing the underlying data to identify queries, from among the set of nested queries, that use the attribute received from a selected query. Another selection results in the system generating SQL code for a selected subset of queries, among the set of nested queries.

Abstract: Techniques for managing temporal dependencies between sets of foreign resources are disclosed, including: allocating, in a runtime environment, a segment of foreign memory to a first memory session, the runtime environment being configured to use a garbage collector to manage memory in a heap, and the foreign memory including off-heap memory that is not managed by the garbage collector; opening, in the runtime environment, a second memory session that descends from the first memory session; while the second memory session is open, encountering a request to close the first memory session; responsive to encountering the request to close the first memory session, determining that the first memory session has at least one open descendant memory session; responsive to determining that the first memory session has at least one open descendant memory session, declining the request to close the first memory session.

Abstract: In accordance with an embodiment, described herein are systems and methods for use with an analytic applications environment, for automatic generation of asserts in such environments. A data pipeline or process, such as, for example an extract, transform, load (ETL) process, can operate in accordance with an analytic applications schema adapted to address particular analytics use cases or best practices, to receive data from a customer's (tenant's) enterprise software application or data environment, for loading into a data warehouse instance. Each customer (tenant) can additionally be associated with a customer tenancy and a customer schema. During the process of populating a data warehouse instance, the system can automatically generate dynamic data-driven ETL asserts, including determining a list of columns for tables in the data warehouse; determining a data type for each column; generating an assert for each determined data type; validating the generated assert; and maintaining the generated assert.

Abstract: Some embodiments process data as defined by a polymorphic data model. A server may provide the polymorphic data model to a client application from a datastore. The functionality or features of the client application may be controlled as a function of the polymorphic data model. The client application may thus provide different functionalities when provided with different polymorphic data models. Updates to the polymorphic data model may be used to update the client application's functionality without any updates to the client application's executable code.

Abstract: A system and method for supporting identifying experts on arbitrary topics in an enterprise social network. An exemplary method can receive, at a node of a social network application, a plurality of content. The method can store the plurality of content in a database associated with the social network application. The method can index the plurality of content, resulting in an index of content, wherein the index of content includes a plurality of activity signals and a plurality of security values. The method can receive a request for a search for at least one expert on an arbitrary topic. The method can search the index of content for the at least one expert on the arbitrary topic, resulting in a plurality of search results. The method can next assign a weight for each of the plurality of search results based at least on the plurality of activity signals.

Abstract: Operations include determining whether to cache resources accessed by a query based on the execution time of the query. The system identifies a set of executions of a same query. The system determines a cumulative execution time for the set of executions of the same query. If the cumulative execution time exceeds a threshold value, then the system caches a resource used for execution of the query.

Abstract: Systems and methods for dynamically assigning membership in a data partition to an end-port of a requesting host channel adapter. An exemplary embodiment can provide a subnet manager configured to operate within a subnet of a network fabric. The subnet can include a plurality of nodes, and the plurality of nodes can include at least one switch and a plurality of end-nodes, where the subnet manager executes on one of the plurality of nodes. A host channel adapter of a node in the subnet can request membership for an end-port of the host channel adapter. In response to the request, the subnet manager can request data from the data store to confirm that the end-port is a member of an admin partition and that the admin partition is associated with the data partition in which membership was requested.

Abstract: Techniques for transitioning between memory segment views include: instantiating a first memory segment view that confines access to a memory segment to a first thread; receiving a request to transition ownership of the memory segment to a second thread; responsive to receiving the request to transition ownership of the memory segment to the second thread: instantiating a second memory segment view that permits access to the memory segment by the second thread; copying metadata from the first memory segment view to the second memory segment view; terminating the first memory segment view, to prevent access to the memory segment via the first memory segment view.

Abstract: Systems, methods, and other embodiments associated with a machine learning system that monitors and detects health and safety risks in electronic correspondence related to a target field are described. In one embodiment, a method includes monitoring email communications over a network to identify an email associated with a target field. A machine learning classifier is initiated that is configured to classify text from the email with a risk as being related to a safety risk or a non-risk. The machine learning classifier generates a probability risk value that the email is related to a safety risk and labels the email as safety risk or non-risk based at least in part on the probability risk value indicating that the email is a safety risk. An electronic notice is generated and transmitted to a remote device in response to the email being labeled as being safety risk to provide an alert.

Abstract: Systems, methods, and other embodiments associated with branch prediction in workflows are described. In one embodiment, a method includes inputting a workflow and serially progressing through the workflow in a flow sequence and in response to the flow sequence encountering a first decision element in the workflow that includes a plurality of branch paths: (i) executing a prediction that predicts a resulting path of the first decision element to predict a first user interface from the plurality of user interfaces that may be encountered subsequently in the flow sequence as part of a first terminal element; and (ii) pre-building the first user interface that is predicted prior to encountering the first terminal element. In response to the flow sequence reaching the first terminal element, displaying the pre-built first user interface on a display device.

Abstract: Systems, methods, and other embodiments are disclosed that are configured to segment customers using mixed attribute types. In one embodiment, a computerized data structure is read. The computerized data structure has numerical demographic attribute data, categorical demographic attribute data, and target attribute data that is associated with customers and is stored in a computerized memory. The numerical demographic attribute data and the categorical demographic attribute data are converted to a same numerical scale, based at least in part on the target attribute data, to form congruent attribute data in a format that is compatible with performing a cluster analysis on the congruent attribute data. The cluster analysis is performed on the congruent attribute data to generate segmented customer data representing a segmentation of the customers. The segmented customer data may be used to control at least one enterprise function performed by a computerized management system.

Abstract: A computer comprising one or more processors offering vector instructions may implement a direct convolution on a source data set. The source data set may be one-dimensional or multi-dimensional. For a given vector width, w, of the vector instructions, w consecutive data elements of the output data set are computed in parallel using vector instructions. For multi-dimensional data sets, multiple vectors of the output data set are computed for a single load of a set of vectors from the source data set. New vector instructions are disclosed to improve the performance of the convolution and to enable full utilization of the arithmetic logic units within the one or more processors.

Abstract: Techniques for data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes generating a list of values to cover for an entity, selecting utterances from a set of data that have context for the entity, converting the utterances into templates, where each template of the templates comprises a slot that maps to the list of values for the entity, selecting a template from the templates, selecting a value from the list of values based on the mapping between the slot within the selected template and the list of values for the entity; and creating an artificial utterance based on the selected template and the selected value, where the creating the artificial utterance comprises inserting the selected value into the slot of the selected template that maps to the list of values for the entity.

Abstract: Techniques are disclosed for associating environmental condition information with a software component so that the environmental conditions can be automatically verified when a software package containing the software component is deployed. As a result, environmental conditions can be established when a software component is initially developed by the operators who may be best-suited to determine appropriate environmental conditions. Further, environmental condition enforcement can be performed automatically at the time of deployment, without human intervention. For example, when the software component is about to deployed, a deployment system can automatically examine the information about the target environment to verify that target environment satisfies the encoded environmental conditions.

Abstract: A machine-learning recommendation system implemented based on game theory for providing recommendations to a first party based on their requirements while also ensuring the recommendation makes sense to a second party. The system can obtain historical data and train a machine-learning model using the historical data. The training includes playing a game between a first player and a second player. The game is played using a minmax theorem that is evaluated with a loss function comprising a first component that represents error in a prediction of a user and product combination and a second component that represents error in a prediction of a value of a product. The game is played until an equilibrium point has been reached at which a final value corresponding to a product to be recommended is determined and the machine-learning model is adapted to minimize the difference between the final value and ground truth information.

Abstract: Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. An improved approach has been described to automatically generate a log parser by analysis of the line content of a log. In addition, an efficient approach has been described to extract key-value content from the log content.

Abstract: Discussed herein is a framework that provisions for customized processing for different classes of traffic. A network device in a communication path between a source host machine and a destination host machine extracts a tag from a packet received by the network device. The packet originates at a source executing on the source host machine and whose destination is the destination host machine. The tag set by the source and indicative of a first traffic class to be associated with the packet, the first traffic class being selected by the source from a plurality of traffic classes. The network device determines, based on the tag, that the first traffic class corresponds to a bandwidth sensitive traffic and processes the packet using one or more settings configured at the network device for processing packets associated with the first traffic class.

Abstract: Discussed herein is a framework that provisions for customized processing for different classes of traffic. A network device in a communication path between a source host machine and 5 a destination host machine extracts a tag from a packet received by the network device. The packet originates at a source executing on the source host machine and whose destination is the destination host machine. The tag set by the source and indicative of a first traffic class to be associated with the packet, the first traffic class being selected by the source from a plurality of traffic classes. The network device determines the first traffic class based on the tag extracted from the packet and 10 processes the packet based on the first traffic class.

Abstract: Techniques for digital messaging with rule-driven attachments are disclosed, including: obtaining a message assembly rule including a set of one or more message attachment criteria; encountering an instance of a set of one or more message transmission triggers being satisfied; responsive to encountering the instance of the set of one or more message transmission triggers being satisfied: querying a data repository to identify multiple attachable data items that satisfy the set of one or more message attachment criteria; generating a message including the attachable data items; transmitting the message to a recipient.

Abstract: Navigating text using an extended discourse tree. In an example, a method accesses an extended discourse tree that includes a first discourse tree for a first document and a second discourse tree for a second document. The method determines a first elementary discourse unit that is responsive to a query from a user device and a corresponding first position. The method further determines a set of navigation options including a first rhetorical relationship between the first elementary discourse unit and a second elementary discourse unit of the first discourse tree and a second rhetorical relationship between the first elementary discourse unit and a third elementary discourse unit of the second discourse tree. The method presents the rhetorical relationships to a user device. Responsive to receiving, from a user device, a selection of a rhetorical relationship, the method presents a corresponding elementary discourse unit to the user device.

Abstract: Disclosed systems relate to propagating tracing across a distributed software application. In an example, an application logs tracing data for a web page from an original server. The application determines, at the web browser, that the web page from the original server requires a request to an external server outside a domain of the original server. The application interrogates the external server to determine whether the external server allows tracing headers in requests. The application updates an allow list, at the web browser, to indicate that the external server allows tracing headers in requests from the original server. The application injects a tracing header in the request based on a result of the interrogation. The application sends, from the web browser to the external server, the request with the tracing header. The external server is configured to log tracing data based on the tracing header.

Abstract: Discussed herein is a technique for replication of keys across regions of a cloud infrastructure. A first vault is created in a first region. The first vault stores a plurality of records, each of which is associated with a key and corresponding metadata. A second region, different from the first region, is selected where replication of the plurality of records is desired. A second vault is created in the second region. The plurality of records are relayed from the first vault to the second vault, so that each of the plurality of records is replicated in the second vault based on an entropy value of the record. A mutation operation executed with respect to the first vault is stored as a new record in the first vault. The new record is transmitted to the second vault, which is updated to reflect the mutation operation performed on the first vault.

Abstract: Embodiments generate random walks through a directed graph that is represented in a relational database table. Each row of the graph table represents a directed edge in the graph and includes a source vertex and a destination vertex. Each row is further augmented to (a) indicate the number of outbound edges starting from the destination vertex in the row and (b) include an identifier that distinguishes the edge from other outbound edges starting from the same source vertex. An SQL query may be executed on the augmented graph table. Starting from a source vertex (starting vertex or the destination vertex of the previously selected hop) the query randomly selects a row of the graph table representing one of the outbound edges from the source vertex and adds the selected outbound edge as a row in a random walk table that represents the next hop in the random walk.

Abstract: An anomaly service receives log data from nodes in a computing environment, which includes a sequence of information indicative of log messages produced by the nodes. The anomaly service identifies dominant patterns in the sequence of information that are representative of non-anomalous blocks of the log messages. Having identified the dominant patterns, the service is able to extract the non-anomalous blocks from the log data to reveal anomalous blocks that do not fit the dominant patterns. The service may then generate anomaly vectors based on the anomalous blocks, which can be distributed to the nodes to detect anomalies.

Abstract: We describe a system that performs prognostic-surveillance operations based on an inferential model that dynamically adapts to evolving operational characteristics of a monitored asset. During a surveillance mode, the system receives a set of time-series signals gathered from sensors in the monitored asset. Next, the system uses an inferential model to generate estimated values for the set of time-series signals, and then performs a pairwise differencing operation between actual values and the estimated values for the set of time-series signals to produce residuals. Next, the system performs a sequential probability ratio test (SPRT) on the residuals to produce SPRT alarms. When a tripping frequency of the SPRT alarms exceeds a threshold value, which is indicative of an incipient anomaly in the monitored asset, the system triggers an alert. While the prognostic-surveillance system is operating in the surveillance mode, the system incrementally updates the inferential model based on the time-series signals.

Abstract: A machine-learning model may be previously trained with a supervised learning algorithm to identify whether a pair of labels provided as input are similar. A locality sensitive hashing forest (LSH) may be generated for the set of candidate labels. When a user later identifies an input label (e.g., by search query, by interface selection, etc.) the input label may be used to query the LSH forest to identify a subset of the candidate labels. This subset may be used to generate respective pairs comprising the input label, one of the subset candidate labels, and a corresponding feature set generated for the pair. This data may be provided to the model to identify a degree to which the pair of labels are similar. The user may be provided one or more recommendations including similar terms identified from the model's output.

Abstract: Techniques described herein propose a ROWID Elimination Rewrite that uses functional dependencies to substitute and/or eliminate ROWID pseudo-columns referenced in a query in order to reduce memory pressure and speed up processing.

Abstract: Systems, methods, and other embodiments associated with a REST API parser for test automation are described. In one embodiment, a method for automating REST API testing includes parsing a test case to extract values for parts of a REST API request and a value for at least one validation parameter; automatically composing the REST API request at least in part from the extracted values for the parts of the REST API request; automatically submitting the REST API request for execution by an application; retrieving a value of a result of the execution of the REST API request from the application; determining that the value for the validation parameter(s) and the value of the result are a match; and generating an indication that the REST API is valid for the test case.

Abstract: In accordance with an embodiment, described are systems and methods for real time data aggregation in a virtual cube in a multidimensional database. A method can provide, at a computer that includes one or more microprocessors, a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one multidimensional cube, a data source associated with the multidimensional cube, and at least one source of real-time data accessible by the data source. The method can query, by the multidimensional cube, the data source, the query comprising an identification of the at least one source of real-time data. The method can provide, by the data source, on-demand access to the multidimensional cube to the at least one source of real-time data. The method can use targeted data from the at least one source of real-time data within the multidimensional cube without being stored therein.

Abstract: Fast modern interconnects may be exploited to control when garbage collection is performed on the nodes (e.g., virtual machines, such as JVMs) of a distributed system in which the individual processes communicate with each other and in which the heap memory is not shared. A garbage collection coordination mechanism (a coordinator implemented by a dedicated process on a single node or distributed across the nodes) may obtain or receive state information from each of the nodes and apply one of multiple supported garbage collection coordination policies to reduce the impact of garbage collection pauses, dependent on that information. For example, if the information indicates that a node is about to collect, the coordinator may trigger a collection on all of the other nodes (e.g., synchronizing collection pauses for batch-mode applications where throughput is important) or may steer requests to other nodes (e.g., for interactive applications where request latencies are important).

Abstract: Techniques are described herein for simulating triggers in a database. A database server receives a query that targets a database managed by the database server. The database server is registered with a plugin that determines whether the query is a particular type of query. If so, plugin sends a message to an external process that includes features of the query. The database server can also execute the query regardless of whether the particular type of query is detected.

Abstract: Techniques for component-based software engineering, and more particularly, to techniques for enhancing component based development systems by making components self-aware with respect to the applications that they may be consumed in or other peer components within the applications. An exemplary technique includes determining an addition of one or more components to an interface of an application; identifying an asset definition within metadata of a component of the one or more components added to the interface of the application, where the asset definition provides self-wiring or self-configuring instructions for an asset that needs to be created for the component within a predefined scope when the component is added to the interface; and creating the asset for the component based on the asset definition.

Abstract: A system and method is described for use with a multidimensional database computing environment to provide support for parallel calculation of multidimensional slices. Users are able to specify a set of slices and a number of parallel threads to employ. The multidimensional database environment generates tasks that include calculations and/or aggregations, which are able to be executed by the system in parallel. Also described herein are mechanisms of utilizing variables within the calculations performed by respective threads, and combining thread variables after execution.

Abstract: An anomaly service receives log data from nodes in a computing environment, which includes a sequence of information indicative of log messages produced by the nodes. The anomaly service identifies dominant patterns in the sequence of information that are representative of non-anomalous blocks of the log messages. Having identified the dominant patterns, the service is able to extract the non-anomalous blocks from the log data to reveal anomalous blocks that do not fit the dominant patterns. The service may then generate anomaly vectors based on the anomalous blocks, which can be distributed to the nodes to detect anomalies.

Abstract: Permissions on a resource hierarchy of a process are propagated. The resource hierarchy of the process is accessed. The resource hierarchy includes multiple nodes arranged in level and each of the nodes is associated with a separate resource from a plurality of resources. A permission for a user is propagate from a first node to one or more lower nodes arranged below the first node in the resource hierarchy. The user is enabled to interact with each resource associated with the first node and the one or more of the lower nodes based on the propagated permission.

Abstract: Disclosed herein are techniques related to automated generation of regular expressions. In some embodiments, a regular expression generator may receive input data comprising one or more character sequences. The regular expression generator may convert character sequences into a sets of regular expression codes and/or span data structures. The regular expression generator may identify a longest common subsequence shared by the sets of regular expression codes and/or spans, and may generate a regular expression based upon the longest common subsequence.

Abstract: The present invention relates to hash join acceleration. In an embodiment, a computer receives a request to join build data rows with probe data rows. Each data row is associated with a respective join key value. From multiple buckets of a hash table, a bucket is selected that contains entries of multiple respective join key values in respective locations within the bucket. Whether or not the bucket contains an entry of the join key value of a build data row is detected. While building, multiple locations within the bucket are concurrently inspected to find an empty location in which to store the entry of the join key value of the build data row. The bucket is concurrently probed to detect whether or not the entries in the bucket include an entry of a join key value of a probe data row. For the join request, a response is sent that is based on the concurrent probing of the bucket.

Abstract: A custom client authenticator is installed on non-server entity. The custom client authenticator authorizes communication between a client application of a client and requested entities of a server. A native authentication technology for the client is different than a native authentication technology for the server. The custom client authenticator is registered in a descriptor file that is accessible by the server. The custom client authenticator generates an authorization token for the client. The authorization token is transmitted as part of a request message for the client application to the server. The custom client authenticator validates the authorization token on behalf of the server. The request message is forwarded to the requested entities executing on the server based on the validating.

Abstract: The present disclosure relates generally to a data integration system that integrate an object based data integration tool, such a GUI-based data integration tools, with version control systems using a relational database repository for persistence. Examples of distributed version control systems include Git, Mercurial, and Bazaar, and examples of centralized version control systems include Subversion, CVS etc. in centralized or distributed environments.

Abstract: Information about a set of maintenance tasks and time windows includes a cost value per task per time window. Based on the information, a data model generator generates a data model, including task elements; time elements; cost elements; a total cost element; a constraint that requires each task element be assigned a time window from a respective domain, such that each time element is assigned a task count from a respective domain; a constraint that requires each cost element be assigned a cost value associated with a time window assigned (or to be assigned) to a task element corresponding to the cost element; and a constraint that requires the total cost element be assigned a total cost value that is a sum of the cost values assigned (or to be assigned) to the cost elements. Based on the data model, a CP solver determines a proposed maintenance schedule.

Abstract: The present disclosure relates to system and techniques for prediction of failures in resources deployed in a data plane of a cloud based infrastructure. The resource are selected from a plurality of cloud based resources arranged in a hierarchical manner and allocated to a client device. A predictor employs a first prediction model to obtain a first prediction of a failure of a resource, and a second prediction model to obtain a second prediction of the failure of the resource. Weights are assigned to the first prediction and second prediction based at least in part on a criterion. The predictor computes an overall prediction of the failure of the resource based at least in part on at least one of the first prediction, the second prediction or the respective weights assigned to the predictions. The overall prediction is utilized for restoring the failure of the resource.

Abstract: Implementations generally relate to software testing system and method for automatically generating, deploying, and monitoring software tests employed to test software applications and/or software process flows. In implementations, a system generates software application tests and varies such tests used based on several criteria including monitoring a software application processing defined inputs and outputs to determine which parts of the application are being tested, which parts of the software application are not being tested, user interactions, metadata, type of software application, use computing environment, etc. The system may be configured to adapt testing, either pre or post production, to allow, user interactions of one or more running software applications to be used to provide feedback on which additional tests to add and/or subtract automatically to testing sequences.

Abstract: Techniques described herein provide a handshake mechanism and protocol for notifying an operating system whether system hardware supports persistent cache flushing. System firmware may determine whether the hardware is capable of supporting a full flush of processor caches and volatile memory buffers in the event of a power outage or asynchronous reset. If the hardware is capable, then persistent cache flushing may be selectively enabled and advertised to the operating system. Once persistent cache flushing is enabled, the operating system and applications may treat data committed to volatile processor caches as persistent. If disabled or not supported by system hardware, then the platform may not advertise support for persistent cache flushing to the operating system.

Abstract: Techniques for managing maximum request rates to shared system resources are disclosed. A system applies a machine learning model, such as a long short-term memory (LSTM) recurrent neural network (RNN) type model to historical maximum request rate data to determine a target maximum request rate for a particular client and a particular period of time. The system obtains the historical maximum request rate data from a distributed ledger, such as a blockchain. System clients may record modifications to their maximum request rates in the blockchain. The system modifies the maximum request rates associated with the system clients authorized to access shared resources based on the modified maximum request rates contained in the new blocks added to the blockchain.

Abstract: The present disclosure relates to systems and methods for an adaptive pipelining composition service that can identify and incorporate one or more new models into the machine learning application. The machine learning application with the new model can be tested off-line with the results being compared with ground truth data. If the machine learning application with the new model outperforms the previously used model, the machine learning application can be upgraded and auto-promoted to production. One or more parameters may also be discovered. The new parameters may be incorporated into the existing model in an off-line mode. The machine learning application with the new parameters can be tested off-line and the results can be compared with previous results with existing parameters. If the new parameters outperform the existing parameters as compared with ground-truth data, the machine learning application can be auto-promoted to production.

Abstract: A computer system may receive one or more requests for access to one or more cloud services and may store the one or more requests in a request log. The computer system may receive one or more access rules applicable to cloud service access rights. The computer system may aggregate the one or more requests of the request log to determine access requirements for a container, the container being configured to store one or more applications. The computer system may generate and store container access policies that define access of a container and the one or more cloud services, the container access policies based at least in part on the aggregated one or more requests and the one or more access rules. The computer system may send the container access policies to a request forwarder of a compute instance in a production environment.

Abstract: A secure, modular multi-tenant machine learning platform is configured to: receive untrusted code supplied by a first tenant; perform a security scan of the untrusted code to determine whether the untrusted code satisfies a set of one or more security requirements; responsive to determining that the untrusted code satisfies the security requirement(s): deploy the untrusted code to a runtime execution environment; deploy a machine learning model associated with the first tenant to the runtime execution environment, the untrusted code being configured to perform one or more functions using the machine learning model; receive a set of untrusted code supplied by a second tenant; perform a security scan of the untrusted code to determine whether the untrusted code satisfies the security requirement(s); and responsive to determining that the untrusted code does not satisfy the security requirement(s): refraining from deploying the untrusted code to a runtime execution environment.

Abstract: The present disclosure relates generally to an integrated machine learning platform. The machine learning platform can convert machine learning models with different schemas into machine learning models that share a common schema, organize the machine learning models into model groups based on certain criteria, and perform pre-deployment evaluation of the machine learning models. The machine learning models in a model group can be evaluated or used individually or as a group. The machine learning platform can be used to deploy a model group and a selector in a production environment, and the selector may learn to dynamically select the model(s) from the model group in the production environment in different contexts or for different input data, based on a score determined using certain scoring metrics, such as certain business goals.

Abstract: Techniques for on-the-fly adaptation of remembered set data structures are disclosed. Operations include initiating execution of an application thread and a garbage collection process for a heap memory including a first plurality of logical partitions, wherein each logical partition of the first plurality of logical partitions is associated with a remembered set data structure. While the application thread and the garbage collection process are executing, the system determines a set of characteristics. Based on the set of characteristics meeting threshold criteria for adjusting a first remembered set data structure corresponding to a first logical partition, the system identifies a first remembered set configuration corresponding to the first remembered set data structure, creates a replacement remembered set data structure based on the first remembered set configuration, and associates the replacement remembered set data structure with the first logical partition.