System and method of compiling a program having a mixture of host code and device code to enable Profile Guided Optimization (PGO) for device code execution. An exemplary integrated compiler can compile source code programmed to be executed by a host processor (e.g., CPU) and a co-processor (e.g., a GPU) concurrently. The compilation can generate an instrumented executable code which includes: profile instrumentation counters for the device functions; and instructions for the host processor to allocate and initialize device memory for the counters and to retrieve collected profile information from the device memory to generate instrumentation output. The output is fed back to the compiler for compiling the source code a second time to generate optimized executable code for the device functions defined in the source code.

Aspects of the present disclosure involve systems, methods, devices, and the like for creating an application lifecycle management platform for big data applications. In one embodiment the lifecycle management platform can include a multiple-layer container file that integrates multiple big-data tools/platforms. The system may create a generic template application, create a build environment for the generic template application, create a test environment for the generic template application, and run the built generic template application in the test environment prior to the user writing any new code in the generic template application. In one embodiment, the test environment includes a container management system or virtual machine that launches the big data application (which may be the generic template application before a developer edits the file) on a separate big-data server cluster.

Systems and methods for managing Application Programming Interfaces (APIs) are disclosed. Systems may involve automatically generating a honeypot. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a client device, a call to an API node and classifying the call as unauthorized. The operation may include sending the call to a node-imitating model associated with the API node and receiving, from the node-imitating model, synthetic node output data. The operations may include sending a notification based on the synthetic node output data to the client device.

This application relates to a computing system and method for an automated program error repair. In one aspect, the computing system includes a storage, a preprocessing processor, and an automated error repair processor. The storage stores a program code. The preprocessing processor acquires the program code from the storage and preprocesses the program code. Preprocessing includes tokenizing the program code with tokens, converting the tokens into vectors, and adding location information for the tokens. The automated error repair processor receives the preprocessed program code as an input from the preprocessing processor, detects an error in the preprocessed program code, corrects the detected error, and outputs the error-corrected program code. Detecting and correcting the error are performed based on a deep learning result and the location information for the tokens.

The present disclosure describes systems and methods for controlling access to secure debugging and profiling features of a computer system. Some illustrative embodiments include a system that includes a processor, and a memory coupled to the processor (the memory used to store information and an attribute associated with the stored information). At least one bit of the attribute determines a security level, selected from a plurality of security levels, of the stored information associated with the attribute. Asserting at least one other bit of the attribute enables exportation of the stored information from the computer system if the security level of the stored information is higher than at least one other security level of the plurality of security levels.

A technique includes accessing, by at least one hardware processor, a recorded request and a recorded response associated with an integration test involving a first computer system and a second computer system. The recorded request was previously issued by the first computer system to the second computer system to cause the second computer system to provide the recorded response. The technique includes, in a virtualized integration test involving the second computer system and initiated using the recorded request, comparing, by the hardware processor(s), the recorded response to a request produced by the second computer system in the virtualized integration test. The technique includes identifying, by the hardware processor(s), an action taken by the second computer system as being likely to be associated with a regression based on the comparison.

A computer-implemented method, computer program product and computing system for receiving a complex task; processing the complex task to define a plurality of discrete tasks each having a discrete goal; executing the plurality of discrete tasks on a plurality of machine-accessible public computing platforms; determining if any of the plurality of discrete tasks failed to achieve its discrete goal; and if a specific discrete task failed to achieve its discrete goal, defining a substitute discrete task having a substitute discrete goal.

The present disclosure provides techniques for configuring and provisioning a tenant for testing microservices in a multi-tenant instance. Code is committed for a modified microservice, and a configuration is received for a production tenant of the multi-tenant instance. The configuration is updated to include a reference to the updated microservice, and then provided to a provisioner that provisions a test tenant based on the configuration. The microservices for the test tenant are compared with versions in a code version management system and updated, then a reference to the test tenant is provided to a developer to test the modified microservice. The test tenant may be deprovisioned after a predetermined amount of time, by a command of the developer, or other automated method.

A CI/CD assist device accepts configuration data and test data collectively from a terminal (a vendor terminal) of a provider that provides a network service to a customer. The configuration data specifies a functional unit required to provide the network service, and the test data specifies test content for the network service or the functional unit. Each of an NOS, an NOS, and an NOS automatically builds the functional unit specified by the configuration data that is accepted by the CI/CD assist device. Each of a test device, a test device, and a test device automatically conducts a test on the network service or the functional unit based on the test data. The network service and the functional unit are built in each environment.

A debugging management platform and an operating method for the same are provided. In the operating method, the debugging management platform operates a debugging agent service for establishing a debugging channel between a software development platform and a test platform. When receiving debugging packets are issued by the software development platform or the test platform, the debugging agent service analyzes the debugging packets and checks if the debugging packets meet an information security standard. The debugging packets are forwarded to the test platform or the software development platform if the debugging packets meet the information security standard. If the debugging packets do not meet the information security standard, the debugging packets are not forwarded, so as to ensure information security of the debugging packets that are forwarded between different environments.