Abstract: Data structures and methods are described to enable a hardware optimized dynamic string table for accelerating relational database queries. A method comprises retrieving a lookup key for a query against a dynamic string table, the lookup key associated with a key length and a key hash. The method further comprises configuring a formatted lookup key as in-line or out-of-line based on whether the key length exceeds a maximum inline key size. The method further comprises replicating, into a first plurality of single instruction, multiple data (SIMD) lanes, the formatted lookup key. The method further comprises writing a candidate bucket, selected from the dynamic string table based on the key hash, into a second plurality of SIMD lanes. The method further comprises performing a SIMD compare of the first plurality of SIMD lanes and the second plurality of SIMD lanes, and returning an associated code when the lookup key is matched.

Abstract: The present embodiments relate to implementing change data on no-master NoSQL data stores. An optimized node can be identified from a plurality of NoSQL data storage nodes and a specialized node can be connected (e.g., collocated) to the optimized node. The specialized node can maintain change data capture (CDC) data provided by client nodes in a hash map that can be used as a point of truth for coordinating CDC data across the plurality of NoSQL data storage nodes. The plurality of NoSQL data storage nodes can identify and coordinate all read/write data obtained from multiple client devices in a geographically separated large-scale (e.g., planet scale) system to identify change data in a distributed data store. The specialized data can provide read data to devices in the large-scale system to reconcile inconsistencies in change data across nodes in the large-scale system.

Abstract: Techniques for cache invalidation across distributed microservices are disclosed, including: monitoring, by a resource manager, a resource that is available for obtaining by a set of one or more resource utilizers, wherein a resource utilizer in the set of one or more resource utilizers obtains a version of the resource; publishing, by the resource manager, a notification stream including notifications associated with the resource, wherein the resource utilizer subscribes to the notification stream including the notifications associated with the resource; detecting, by the resource manager, a modification of the resource; responsive to detecting the modification of the resource: publishing a notification to the notification stream that indicates the modification to the resource.

Abstract: Techniques are disclosed for aggregating received data from a data stream. Data is received from a particular stream partition to which a device is subscribed, and subsets of the data, from the particular stream partition, are aggregated based on respective keys associated with the subsets of the data. The device determines whether one or more subsets of data, associated with a particular key, meet at least one processing criteria, such as a threshold amount of data, and refraining from processing the aggregated data when the processing criteria is not met. Once additional subset(s) of data associated with the particular key are received, they are aggregated with the one or more subsets of data. When the processing criteria is satisfied, the device processes the aggregated subsets of data associated with the particular key.

Abstract: Techniques for transitioning between message infrastructure platforms are disclosed. A platform manager transmits a data stream using a first message infrastructure platform. A platform monitor monitors transmission characteristics associated with the transmission of the data stream using the first message infrastructure platform. A platform selector selects a second message infrastructure platform based on the transmission characteristics. A platform transitioner transitions from transmitting the data stream using the first message infrastructure platform to transmitting the data stream using the second message infrastructure platform seamlessly.

Abstract: The present disclosure relates generally to techniques for analyzing and improving a bot system, and more particularly to an analytic system integrated with a bot system for monitoring, analyzing, visualizing, diagnosing, and improving the performance of the bot system. For example, an analytic system is integrated with a bot system for monitoring, analyzing, visualizing, and improving the performance of the bot system. The analytic system monitors events occurred in conversations between end users and the bot system, aggregates and analyzes the collected events, and provides information regarding the conversations graphically on a graphic user interface as insights reports at different generalization levels. The insights reports offer developer-oriented analytics to pinpoint issues with skills so a user can address them before they cause problems.

Abstract: Techniques are described for monitoring the health of services in a computing environment such as a data center. More particularly, the present disclosure describes techniques for monitoring the health and availability of capabilities in a computing environment such as a data center by enabling alarms to be associated with the capabilities. A capability refers to a set of resources in a data center. By providing the ability to associate an alarm with a capability, the health or availability of the associated capability can be monitored or ascertained by tracking the state of the alarm associated with the capability. For example, if the alarm associated with a particular capability is triggered, it may indicate that the particular capability and the one or more resources corresponding to the particular capability are not in a healthy state. Accordingly, by monitoring alarms associated with capabilities, the health of the associated capabilities can be ascertained.

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: Embodiments upsell a hotel room selection by generating a first hierarchical prediction model corresponding to a first hotel chain, the first hierarchical prediction model receiving reservation data from one or more corresponding first hotel properties, and generating a second hierarchical prediction model corresponding to a second hotel chain, the second hierarchical prediction model receiving reservation data from one or more corresponding second hotel properties. At each of the first hierarchical prediction model and the second hierarchical prediction model, embodiments generate corresponding model parameters. At a horizontal federated server, embodiments receive the corresponding model parameters and average the model parameters to be used as a new probability distribution, and distribute the new probability distribution to the first hotel properties and the second hotel properties.

Abstract: Consistent External Table Access maintains transactional consistency for queries that access external tables stored in a DBFS. This ability is achieved by bypassing the OS. One or more database processes executing a query that access an external table stored in a DBFS access the database-file table like other database tables in the DBMS that can be accessed to execute a query. Based on metadata stored in the DBMS regarding how an external table is stored in a DBFS, a DBMS is able to marshal database processes that access database-file tables directly to execute a query.

Abstract: Techniques are provided for implementing a pluggable database monitoring system that groups running processes for the pluggable database into a grouping and monitors resource usage for the grouping to determine whether to migrate the pluggable database to another container. A system identifies a set of running processes associated with a pluggable database. The pluggable database is hosted on a container DBMS, which is hosted on a virtual machine. The system generates a first grouping that contains the set of running processes. The system monitors, in real-time, aggregated resource usage of the first grouping to determine if the aggregated resource usage exceeds a first threshold. In response to the aggregated resource usage of the first grouping exceeding the first threshold, the system migrates the first pluggable database to a second container DBMS.

Abstract: Techniques support graph pattern matching queries inside a relational database management system (RDBMS) that supports SQL execution. The techniques compile a graph pattern matching query that includes a bounded recursive pattern query into a SQL query that can then be executed by the relational engine. As a result, techniques enable execution of graph pattern matching queries that include bounded recursive patterns on top of the relational engine by avoiding any change in the existing SQL engine.

Abstract: Techniques are described for identifying root cause anomalies in time series. Information to be used for root cause analysis (RCA) is obtained from a graph neural network (GNN) and is used to construct a dependency graph having nodes corresponding to each time series and directed edges corresponding to dependencies between the time series. Nodes corresponding to time series that do not contain anomalies may be removed from this dependency graph, as well as edges connected to these nodes. This edge and node removal may result in the creation of one or more sub-graphs from the dependency graph. A root cause analysis algorithm may be run on these one or more sub-graphs to create a root cause graph for each sub-graph. These root cause graphs may then be used to identify root cause anomalies within the multiple time series, as well as sequences of anomalies within the multiple time series.

Abstract: A method for avoiding sending duplicate notifications for overlapping subscriptions includes, at a network function (NF) repository function (NRF), detecting an event relating to an NF. The method further includes identifying a plurality of subscriptions having a subscription condition corresponding to the event. The method further includes generating a list of the plurality of subscriptions having a subscription condition corresponding to the event. The method further includes iterating through the list of subscriptions and identifying overlapping subscriptions. The method further includes removing the overlapping subscriptions from the list. The method further includes sending notification messages to NFs corresponding to subscriptions remaining in the list.

Abstract: Techniques are disclosed for augmenting data sets used for training machine learning models and for generating predictions by trained machine learning models. These techniques may increase a number and diversity of examples within an initial training dataset of sentences by extracting a subset of words from the existing training dataset of sentences. The techniques may conserve scarce sample data in few-shot situations by training a data generation model using general data obtained from a general data source.

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: A method for error information propagation from an SCP to a NF to support a circuit breaker design at the consumer NF includes receiving, at the SCP and from the consumer NF, a first SBI service request message. The method further includes attempting, by the SCP, to forward the first SBI service request to N producer NF instances. The method further includes detecting, by the SCP, an error involving the N producer NF instances. The method further includes performing, by the SCP, successful alternate routing of the first SBI service request message to an (N+1) th producer NF instance. The method further includes receiving, by the SCP, a success response message from the (N+1) th producer NF instance. The method further includes propagating, by the SCP, with the success response message and to the consumer NF, error information regarding the N producer NF instances.

Abstract: Techniques are disclosed for dynamically managing access to cross-cloud services. Provided are access control mechanisms for controlling and/or managing access to cross-cloud services offered by and between one or more cloud service providers. The techniques include detecting that a request for a cloud service has been received by a first component of a first cloud environment of a first cloud service provider and receiving an indication that deployment of the cloud service is permitted. In response to receiving the indication, a second component of the first cloud environment generates an instruction for implementing the cloud service within a second cloud environment and causes deployment of the cloud service within the second cloud environment based on the instruction.

Abstract: The present disclosure relates to manufacturing training data by leveraging an automated pipeline that manufactures visualization training datasets to train a machine learning model to convert a natural language utterance into meaning representation language logical form that includes one or more visualization actions. Aspects are directed towards accessing an original training dataset, a visualization query dataset, an incremental visualization dataset, a manipulation visualization dataset, or any combination thereof. One or more visualization training datasets are generated by: (i) modifying examples in the original training dataset, the visualization query dataset, or both to include visualization actions, (ii) generating examples, using the incremental visualization dataset, the manipulation visualization dataset, or both, that include visualization actions, or (iii) both (i) and (ii).

Abstract: A flow graph of a first compilation unit of the program is expanded. The first corresponding parameter states of statements of the first compilation unit are marked as empty. The statements of the first compilation unit are processed to update the first corresponding parameter states with an exact type and a value set. Processing the statements include tracking a control flow predicate of a block in the first compilation unit, wherein the block comprises a first subset of the statements. Only after the control flow predicate indicates that the block is executable, the method includes processing an invocation statement in the first subset of the first statements, and expanding, responsive to the invocation statement, the flow graph for a second compilation unit of the program that is identified by the invocation statement.

Abstract: An architecture for offering a service of a first cloud service provider via a second cloud service provider is disclosed. A first cloud service provider infrastructure includes a first infrastructure and a second infrastructure. The first infrastructure is physically connected to a third infrastructure of a second cloud service provider infrastructure based on a first protocol. The first infrastructure is also physically connected to the second infrastructure based on a second protocol that is different from the first protocol. Using the first and second infrastructures, low latency high-bandwidth cross-cloud services can be provisioned and managed between private clouds of different cloud service providers.

Abstract: Techniques are disclosed for provisioning and managing resources within a cloud infrastructure of a first cloud service provider for cloud services offered by a second cloud service provider. Cross-cloud services can be provisioned and managed by and between private clouds of cloud service providers. The techniques include receiving a request for a cloud service by a component of a first private cloud within a first cloud environment and from a component of a second private cloud within a second cloud environment. The techniques further include the component of the first private cloud performing one or more operations to establish network connectivity prerequisites for network connectivity between the first private cloud and the second private cloud and causing one or more components of the first private cloud to provision the cloud service in the second private cloud.

Abstract: Operations include: receiving a first request for a first dataset of a plurality of datasets stored in a particular database instance; obtaining an encrypted version of the first dataset; obtaining an encrypted version of the first DEK; requesting decryption of the encrypted version of the first DEK; receiving a decrypted version of the first DEK; applying the first DEK to the encrypted version of the first dataset to obtain a decrypted version of the first dataset; and transmitting the decrypted version of the first dataset. The first dataset is encrypted by a first DEK associated with a first tenant. A second dataset is encrypted by a second DEK associated with a second tenant. The decrypted version of the first DEK is generated by applying a first MEK of the first tenant to the encrypted version of the first DEK.

Abstract: In some implementations, the techniques may include receiving an accuracy target for one or more machine learning models. In addition, the techniques may include training the models on a labeled training set of labeled data. The techniques may include, until the accuracy of the models satisfies the accuracy target: sampling, a set of unlabeled data to obtain a random training set of unlabeled data; labeling the random training set of unlabeled data using the models to produce a pseudo labeled training set; correcting the labels on a random subset of the pseudo labeled training set; training the models on the labeled training set, the corrected random subset, and the pseudo labeled training set; and evaluating the accuracy of the models using an evaluation set of labeled data. The one or more models can be deployed based at least in part on the models satisfying the accuracy target.

Abstract: Techniques are described for partitioning B-tree keys of file systems into key ranges for parallel processing in delta generation during file storage replications between file systems in different cloud infrastructure regions. In certain embodiments, a delta generation processing for cross-region replication may utilize a key-range splitting mechanism involving a recursive algorithm that partitions B-tree keys of a source file system into roughly equal-size key ranges. All the partitioned key ranges may be processed in parallel and concurrently by different processing threads, one thread per key range, to improve the performance of the delta generation and achieve scalability.

Abstract: Techniques are disclosed for provisioning a cloud service of a first cloud service provider using a control plane of a second cloud service provider. The techniques include detecting that a request for a cloud service provided by the first cloud service provider has been received from the second cloud environment of a second cloud service provider different from the first cloud service provider. The techniques further include, after detecting that the request for the cloud service has been received, provisioning a first set of resources within the first cloud environment and linking the first set of resources to a second set of resources within the second cloud environment. Linking the first set of resources to the second set of resources enables data pertaining to the cloud service to be transferred from the second cloud environment to the first cloud environment.

Abstract: Techniques are disclosed for providing a scalable multi-tenant serve pool for chatbot systems. A query serving system (QSS) receives a request to serve a query for a skillbot. The QSS includes: (i) a plurality of deployments in a serving pool, and (ii) a plurality of deployments in a free pool. The QSS determines whether a first deployment from the plurality of deployments in the serving pool can serve the query based on an identifier of the skillbot. In response to determining that the first deployment cannot serve the query, the QSS selects a second deployment from the plurality of deployments in the free pool to be assigned to the skillbot, and loads a machine-learning model associated with the skillbot into the second deployment, wherein the machine-learning model is trained to serve the query for the skillbot. The query is served using the machine-learning model loaded into the second deployment.

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: Techniques are disclosed for provisioning and managing resources within a cloud infrastructure of a first cloud service provider for a cloud service offered by a second cloud service provider. Cross-cloud services can be provisioned and managed by and between private clouds of cloud service providers. The techniques include receiving a request for a cloud service by a component of a first private cloud within a first cloud environment and from a component of a second private cloud within a second cloud environment. The techniques further include the component of the first private cloud performing one or more operations to establish network connectivity prerequisites for network connectivity between the first private cloud and the second private cloud and causing one or more components of the first private cloud to provision the cloud service in the second private cloud.

Abstract: Techniques for generating a retail forecasting model from product-cluster-based estimated elasticity values to forecast the effects of price changes on the demand for a set of products are disclosed. A system generates cluster-based price-elasticity values for a set of products by applying a set of regressive elasticity-estimation algorithms to a set of product data and clustering products based on product descriptions and estimated price-elasticity values. The system uses the cluster-based price-elasticity values for the products to generate the retail forecasting model.

Abstract: Techniques are disclosed for providing services based on infrastructure distributed between multiple cloud service providers. Low-latency high-bandwidth cross-cloud services can be provisioned and managed by and between private clouds of cloud service providers. The techniques include forming a cloud network between a first set of compute resources of a first infrastructure of a first cloud environment and a second set of compute resources of a second infrastructure of a second cloud environment. The first cloud environment is provided by a first cloud service provider and the second cloud environment is provided by a second cloud service provider different from the first cloud service provider.

Abstract: Techniques are disclosed herein for transforming natural language conversations into a visual output. In one aspect, a computer-implement method includes generating an input string by concatenating a natural language utterance with a schema representation comprising a set of entities for visualization actions, generating, by a first encoder of a machine learning model, one or more embeddings of the input string, encoding, by a second encoder of the machine learning model, relations between elements in the schema representation and words in the natural language utterance based on the one or more embeddings, generating, by a grammar-based decoder of the machine learning model and based on the encoded relations and the one or more embeddings, an intermediate logical form that represents at least the query, the one or more visualization actions, or the combination thereof, and generating, based on the intermediate logical form, a command for a computing system.

Abstract: Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

Abstract: A method includes obtaining initial transcription for input natural speech; performing segmentation of initial transcription into text portions, based on punctuation marks in initial transcription; determining segment-level timestamps for text portions based on the input natural speech; performing audio segmentation on input natural speech, by cutting input natural speech based on segment-level timestamps, to obtain audio chunks; generating transcription portions for each of the audio chunks; merging transcription portions to form re-transcription; determining word-level timestamps for re-transcription, by aligning input natural speech against re-transcription; calculating silence time periods, each corresponding to silence between each two adjacent words of input natural speech, based on word-level timestamps; performing a final segmentation on input natural speech and re-transcription, based on silence time periods, to generate final audio segments and corresponding final transcription portions.

Abstract: The present disclosure relates to chatbot systems, and more particularly, to batching techniques for handling unbalanced training data when training a model such that bias is removed from the trained machine learning model when performing inference. In an embodiment, a plurality of raw utterances is obtained. A bias eliminating distribution is determined and a subset of the plurality of raw utterances is batched according to the bias-reducing distribution. The resulting unbiased training data may be input into a prediction model for training the prediction model. The trained prediction model may be obtained and utilized to predict unbiased results from new inputs received by the trained prediction model.

Abstract: A system and method for secure generation and distribution of digital encryption keys is disclosed. The system may also be used to protect and distribute other types of secure information, including digital, audio, video, or analog data, or physical objects. The system may include a tamper-respondent secure token device, which may be configured to destroy or disable access to the secure information contained therein in response to attempts to physically or electronically breach the device. Outputs may be provided in a secure manner through various interfaces without using electricity (wires) or electromagnetic radiation. Inputs may be provided in a secure manner, including through the use of a gesture-based input interface. Destruction or disablement of the device and/or its secure contents may be provided upon detection of tamper attempts or upon input of a self-destruct command. Proof of the destruction or disablement of the device or its contents may be provided.

Abstract: The present disclosure relates to managing services by a managed service provider (MSP) in a cloud based infrastructure. A control plane of the MSP is established in a first tenancy, and a first access plane of the MSP is established in a second tenancy of a cloud environment. The control plane is configured to manage a plurality of services offered by the MSP to a first host machine included in the second tenancy. A first request is transmitted from the control plane to the first access plane, where the first request is forwarded by the first access plane to the first host machine, and corresponds to a service utilized by the first host machine and managed by the control plane of the MSP. In response to the first request being validated, a first state of the first host machine is modified in the second tenancy based on the first request.

Abstract: The present embodiments relate to a keystore service for encryption for a computing device of a cloud computing system. The computing device of the cloud computing system can receive a key identification, an encrypted key encryption key, an identity of a client device, and a request from the client device to store the key identification and the encrypted key identification key. The computing device can verify, based at least in part on the identity, an authority of the client device to store the key identification and encrypted key encryption key. The computing device can transmit, based at least in part on the verification, the key identification, the encrypted key encryption key, and request to store the key identification and the encrypted key encryption key to a keystore.

Abstract: Embodiments include systems and methods for generating a data throughput estimation model. A system may be monitored to measure both (a) data throughput and (b) computing statistics of one or more computing resources to generate an initial data set. The relationship between the data throughput and the computing statistics, in the initial data set, is used to generate a data throughput estimation model. The data throughput estimation model may be generated using a machine learning model, a neural network algorithm, boosting decision tree algorithm, and/or a random forest decision tree algorithm. Additional measurements of the computing resource statistics may be applied to the data throughput estimation model to estimate data throughput.

Abstract: Various embodiments of the present technology generally relate to systems and methods for efficiently cleaning up resources within a network by bundling binding session audit requests. A binding support function (BSF) may determine support for bundled audit requests and unbundled audit requests at one or more policy control functions (PCFs) associated with potentially stale session binding records at the BSF. Based on audit support function at the PCF, the BSF may determine whether to bundle audit requests together, issue unbundled audit requests, or not issue any audit requests. PCF support for bundled or unbundled auditing may be provided via a network repository function (NRF), via headers in binding creation or update requests, or both.

Abstract: Techniques for performing distributed rate limiting in networks in a cloud environment are described for determining an amount of network bandwidth available to be processed by flow control nodes within a cloud network for a first time period, determining a bandwidth allocation for traffic classes for the first time period, determining, a portion of the bandwidth allocation for the flow control nodes, providing, data to the flow control nodes, where the data indicates the portion of the bandwidth allocation for the traffic classes, and receiving, second data that indicates an amount of network traffic routed during the first time period by individual ones of the flow control nodes.

Abstract: The present disclosure relates to a system and techniques for resolving dangling references resulting from a dependency relationship between computing resource objects uncovered during a harvesting process. In embodiments, a harvester application adds computing resource objects associated with a client to a resource collection as those computing resource objects are identified. Dependencies are identified as each computing resource object is added to the resource collection, which are resolved only if the computing resource objects associated with those dependencies have already been added to the resource collection. If the computing resource objects associated with the dependencies have not already been added to the resource collection, then the dependency is added to an observer pool. Observer modules are configured to check each computing resource object as it is processed during the harvest process in order to match those computing resource objects to unresolved dependencies.

Abstract: In accordance with an embodiment, described herein is a system and method for improving performance within a multidimensional database computing environment. A multidimensional database, utilizing a block storage option, performs numerous input/output (I/O) operations when executing calculations. To separate I/O operations from calculations, a background task queue is created to identify data blocks requiring I/O. The background task queue is utilized by background writer threads to execute the I/O operations in parallel with calculations.

Abstract: Techniques for leveraging frequent patterns identified in a captured workload are provided. In one approach, multiple frequent patterns detected in a captured workload may be ordered by frequency to determine, for example, which patterns should be targeted for optimization. In another approach, a model of a captured workload is created, where the model comprises nodes that represent templates (which in turn correspond to requests) and edges that represent transitions between templates. The model is used to create an artificial workload, such as a workload that is twice as large as the originally-captured workload. The model may also be edited before creating the artificial workload. In another approach, workload models are compared to identify errors, regressions, or security issues. In another approach, an artificial workload is created for an application that is not yet deployed and then executed to determine whether the artificial workload or the originally-captured workload executed faster.

Abstract: Techniques are provided for customizing authentication and for handling pre-authentication and post-authentication plug-ins in an access management system. Users may want to access a protected resource, such as an application, and apply customizations to the protected resource. The customizations can be applied through the use of plug-ins, such as pre-authentication and post-authentication plug-ins. After it is determined that the user has permissions to apply a specified plug-in, analysis is performed to ensure that the plug-in complies with system requirements and that the criteria for implementing the plug-in has been satisfied. A browser session and control of the application can then be forwarded to the user.

Abstract: Techniques for automatically generating unit tests based on execution traces are disclosed. Trace data is traversed to identify a previously executed and traced target method, e.g., an initial version of the target method, and corresponding first set of input values and first return value used to invoke the initial version of the target method. Using the trace data, generating a test code for testing an updated version of the target method. Executing the test code includes invoking the updated version of the target method using the first set of inputs as arguments. In response to invoking the updated version of the target method, receiving a second return value. The second return value is compared to the first return value to determine whether the second return value matches the first return value. The results are then presented or stored.

Abstract: A method of code vulnerability detection includes obtaining a set of patches from at least one code repository for a vulnerability record of a vulnerability of a software component, applying the set of patches to obtain a modified set of code files modified by the set of patches, and inferring a vulnerable code section set according to the modified set of code files. The vulnerable code section set is a subset of the modified set of code files. The method further includes obtaining a vulnerable version list of a plurality of versions of the software component comprising the vulnerability, validating a version in the vulnerable version list as having the vulnerable code section set, and processing a target software comprising the version using the vulnerable code section set.

Abstract: Techniques for escalating a service ticket between two service providers include receiving an initial service ticket at an initial service provider for resolution of an issue from an affected entity that is affected by the issue. The initial service ticket comprises an access-restricted set of attributes of the affected entity. Based on the initial service ticket, the system generates an escalated service ticket at the initial service provider. The escalated service ticket identifies the issue and omits the access-restricted attributes. The system transmits the escalated service ticket to a higher-tiered service provider, which is not authorized to access the access-restricted set of attributes comprised in the initial service ticket.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A current value for an aggregate power threshold of a plurality of hosts may be identified. During a first time period, an aggregate power consumption of the plurality of hosts may be managed using the current value for the aggregate power threshold. A triggering event indicating a modification to the aggregate power threshold is needed may be detected. A new value for the aggregate power threshold may be determined based on the triggering event. During a second time period, the aggregate power consumption of the plurality of hosts may be managed using the new value for the aggregate power threshold.

Abstract: Techniques for deriving an optimal traversal path on a racetrack are disclosed. The system partitions a track into straight and curved segments. The system identifies optimal traversals through each segment from historical traversal data. The system stitches the optimal traversals together and smooths the optimal traversals at the transition points between track segments. The system verifies that the smoothed traversals meet one or more kinematic criteria before outputting the optimal traversal path.