Abstract: An example operation may include one or more of receiving a blockchain request comprising a timestamp added by one or more endorsing nodes included within a blockchain network, identifying that the timestamp added by an endorsing node from among the one or more endorsing nodes is a modification to a previously added timestamp provided by the computing node, determining a reputation value for the endorsing node based on a difference between the timestamp added by the endorsing node and the previously added timestamp provided by the computing node, and transmitting the determined reputation value of the endorsing node to an ordering node within the blockchain network.

Abstract: A computer-implemented method for detecting bottlenecks in microservice cloud systems is provided including identifying a plurality of nodes within one or more clusters associated with a plurality of containers, collecting thread profiles and network connectivity data by periodically dumping stacks of threads and identifying network connectivity status of one or more containers of the plurality of containers, classifying the stacks of threads based on a plurality of thread states, constructing a microservice dependency graph from the network connectivity data, aligning the plurality of nodes to bar graphs to depict an average number of working threads in a corresponding microservice, and generating, on a display, an illustration outlining the plurality of thread states, each of the plurality of thread states having a different representation.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: A computer-implemented method for detecting bottlenecks in microservice cloud systems is provided including identifying a plurality of nodes within one or more clusters associated with a plurality of containers, collecting thread profiles and network connectivity data by periodically dumping stacks of threads and identifying network connectivity status of one or more containers of the plurality of containers, classifying the stacks of threads based on a plurality of thread states, constructing a microservice dependency graph from the network connectivity data, aligning the plurality of nodes to bar graphs to depict an average number of working threads in a corresponding microservice, and generating, on a display, an illustration outlining the plurality of thread states, each of the plurality of thread states having a different representation.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: A method is provided for building calling context trees of an application to identify a thread or a device affecting a throughput of a transaction relating to the application. The method obtains profiles of call stacks of multiple threads. The method obtains wake-up profiles which are the call stacks of a notifier thread and a waiter thread, from among the multiple threads, in a case that the waiter thread leaves from a sleep state. The method builds the calling context trees to indicate transitions of methods tracing callee relations and wake-up relations based on the profiles of the call stacks and the wake-up profiles, wherein each method is represented by a node having an average thread number. The method extracts and displays tree portions which are transitively reachable from a calling context tree for the transaction and which include the thread or device affecting throughput.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application in a blockchain network, receiving validity information of a timestamp included in the blockchain request from one or more endorsing nodes in the blockchain network, modifying the timestamp included in the blockchain request based on the validity information received from the one or more endorsing nodes, ordering the blockchain request among a group of blockchain requests based on the modified timestamp with respect to timestamps of other blockchain requests in the group, and storing the ordered group of blockchain requests within a data block among a hash-linked chain of data blocks.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: An example operation may include one or more of receiving a blockchain request comprising a timestamp added by one or more endorsing nodes included within a blockchain network, identifying that the timestamp added by an endorsing node from among the one or more endorsing nodes is a modification to a previously added timestamp provided by the computing node, determining a reputation value for the endorsing node based on a difference between the timestamp added by the endorsing node and the previously added timestamp provided by the computing node, and transmitting the determined reputation value of the endorsing node to an ordering node within the blockchain network.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application in a blockchain network, receiving validity information of a timestamp included in the blockchain request from one or more endorsing nodes in the blockchain network, modifying the timestamp included in the blockchain request based on the validity information received from the one or more endorsing nodes, ordering the blockchain request among a group of blockchain requests based on the modified timestamp with respect to timestamps of other blockchain requests in the group, and storing the ordered group of blockchain requests within a data block among a hash-linked chain of data blocks.

Abstract: An example operation may include one or more of receiving a blockchain request from a client application, determining a network latency between the client application and the endorsing node based on a network path between the client application and the endorsing node, extracting a timestamp from the blockchain request, determining whether the extracted timestamp is invalid based on the network latency between the client application and the endorsing node, and in response to determining that the timestamp is valid, generating an endorsement for the blockchain request and transmitting the endorsement to the client application.

Abstract: A method is provided for building calling context trees of an application to identify a thread or a device affecting a throughput of a transaction relating to the application. The method obtains profiles of call stacks of multiple threads. The method obtains wake-up profiles which are the call stacks of a notifier thread and a waiter thread, from among the multiple threads, in a case that the waiter thread leaves from a sleep state. The method builds the calling context trees to indicate transitions of methods tracing callee relations and wake-up relations based on the profiles of the call stacks and the wake-up profiles, wherein each method is represented by a node having an average thread number. The method extracts and displays tree portions which are transitively reachable from a calling context tree for the transaction and which include the thread or device affecting throughput.

Abstract: A computer program product is provided for splitting a live-range of a variable in frequently executed regions of program instructions. The live-range of a variable is split into multiple sub-ranges, each of which can be assigned to a different register or spilled into memory. The amount of spill code is reduced in frequently used regions of code by coalescing the live ranges based on profile information obtained after splitting the live ranges at every join and fork point in a control flow graph.

Abstract: A system is provided for splitting a live-range of a variable in frequently executed regions of program instructions. The live-range of a variable is split into multiple sub-ranges, each of which can be assigned to a different register or spilled into memory. The amount of spill code is reduced in frequently used regions of code by coalescing the live ranges based on profile information obtained after splitting the live ranges at every join and fork point in a control flow graph.

Abstract: A computer program product is provided for splitting a live-range of a variable in frequently executed regions of program instructions. The live-range of a variable is split into multiple sub-ranges, each of which can be assigned to a different register or spilled into memory. The amount of spill code is reduced in frequently used regions of code by coalescing the live ranges based on profile information obtained after splitting the live ranges at every join and fork point in a control flow graph.

Abstract: A system is provided for splitting a live-range of a variable in frequently executed regions of program instructions. The live-range of a variable is split into multiple sub-ranges, each of which can be assigned to a different register or spilled into memory. The amount of spill code is reduced in frequently used regions of code by coalescing the live ranges based on profile information obtained after splitting the live ranges at every join and fork point in a control flow graph.

Abstract: A method and system are provided for splitting a live-range of a variable in frequently executed regions of program instructions. The live-range of a variable is split into multiple sub-ranges, each of which can be assigned to a different register or spilled into memory. The amount of spill code is reduced in frequently used regions of code by coalescing the live ranges based on profile information obtained after splitting the live ranges at every join and fork point in a control flow graph.

Abstract: A method of allowing exclusive access to shared data by a computing device and a computer readable article embodying instructions for executing the method. The method includes: reading from a storage unit into a memory a program including a code for execution in a critical section and an instruction to write a value into or read a value from a shared data area in the memory; acquiring a lock on the critical section before start of a first instruction in the critical section; writing a value into a thread-local area in the memory in response to an instruction to write the value into the shared data area; writing into the shared data area the value written into the thread-local area upon completion of a final instruction in the critical section; and releasing the lock on the critical section, thereby allowing exclusive access to shared data.