Distributed ledger-based networks (DLNs) employ self-executing codes, also known as smart contracts, to manage interactions occurring on the networks, which may result in the generation of a massive amount of DLN state data representing the interactions and participants thereof. The instant disclosure discloses systems, apparatus and methods that allow interactions to occur on the DLNs without modification to stored data, thereby improving the storage capabilities of the networks.

Described are a method, system, and computer program product for operating dynamic shadow testing environments for machine-learning models. The method includes generating a shadow testing environment operating at least two transaction services. The method also includes receiving a plurality of transaction authorization requests. The method further includes determining a first percentage associated with a first testing policy of the first transaction service and a second percentage associated with a second testing policy of the second transaction service. The method further includes replicating in the shadow testing environment, in real-time with processing the payment transactions, a first portion of the plurality of transaction authorization requests and a second portion of the plurality of transaction authorization requests. The method further includes testing the first transaction service using the first set of replicated transaction data and the second transaction service using the second set of replicated transaction data.

A method and system for finding vulnerabilities in a program using fuzzing have been provided. The disclosure provides a vulnerability detection framework using a language agnostic single fuzzer that can fuzz smart contracts written in different programming languages. The idea here is that a smart contract written in a high-level language is converted/compiled into an LLVM intermediate representation (LLVM IR) code and then perform the fuzzing on this LLVM IR code instead of fuzzing smart contract source code directly. The process of generating fuzz driver, report driver is automated by handling the standardization issue by carefully dividing the smart contracts into categories. The present disclosure is proposing processes of automation of fuzz or report driver generation. Further the language agnostic feature (done with intermediate representation) is also achieved. Further profiling is achieved which processes fuzzer output and generates meaningful data points.

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support creation and execution of automated sequences of user interface (UI) interactions. To facilitate creation and execution of automated sequences of UI interactions, an automation engine is provided and includes a model configured to capture image data when creating the sequence of UI interactions. The model may also be used during replay of the sequence of UI interactions. For example, the model may be used during replay of the sequence of UI interactions to locate UI elements corresponding to the UI interactions, or to perform pre-and/or post-validation of action execution. The automation engine may also provide processes to enable location of dynamic content, such as UI elements that may be presented in different or unexpected locations, and processes to address complex UI elements, such as data grids, tree views, and drawings (e.g., CAD drawings).

A method and system for remote testing of a plurality of devices is disclosed. The method may include receiving a request from a client system to perform testing on a set of remote devices. The local system and the client system are connected via a first network connection and the plurality of remote devices are connected to the local system via a second network connection. The method may further include receiving an input from the client system with reference to a test-suite to perform a testing action on the set of remote devices, generating a test command corresponding to the input, and transmitting the test command to each of the set of remote devices. The method may further include receiving feedback from each of the set of remote devices and transmitting the feedback to the client system.

A method includes receiving an identification of a feature associated with digital content of a third-party content provider, wherein the identification comprises a feature variable placeholder associated with the feature. The method further includes receiving a configuration of a feature flag associated with the feature. The method further includes determining, by a processing device of an experimentation system, a plurality of feature variable values corresponding to the feature variable placeholder. The method further includes configuring, by the processing device, one or more rules on the experimentation system to determine: when and to whom the feature is to be deployed, based on the feature flag; and which of the plurality of feature variable values is to be deployed when and to whom.

Embodiments disclosed herein provide for methods and systems for providing an enterprise synthetic monitoring framework, wherein the enterprise synthetic monitoring framework is configured to provide exhaustive end-to-end monitoring for a variety of applications and workflows including those that are browser and non-browser based, those that are implemented on mobile devices, and those that are implemented utilizing native protocols.

In the conventional semiconductor device, it is impossible for two CPUs to operate memories to be debugged at synchronous timings. According to one embodiment, the operation verifying program analyzes the operation verifying command received by the first semiconductor device 10 from the external device 31 by its own device (S32), transfers the operation verifying command to the second semiconductor device 20 (S31, S41), also analyzes the operation verifying command in the second semiconductor device 20 (S42), outputs the trigger signal (S34, S44) to the first semiconductor device 10 from the second semiconductor device 20 based on the result of the analysis, writes the memory setting values included in the operation verifying command to the memories in the respective semiconductor device (S35, S45) based on the trigger signal, and restarts the device operation based on the written memory setting values.

Web-based robotic process automation (RPA) designer systems that allow RPA developers to design and implement web serverless automations, user interface (UI) automations, and other automations are disclosed. Such web-based RPA designer systems may allow a developer to sign in through the cloud and obtain a list of template projects, developer-designed projects, services, activities, etc. Thus, RPA development may be centralized and cloud-based, reducing the local processing and memory requirements on a user's computing system and centralizing RPA designer functionality, enabling better compliance. Automations generated by the web-based RPA designer systems may be deployed and executed in virtual machines (VMs), containers, or operating system sessions.

Systems and methods are provided for automatically generating a fault-enabled software development kit (SDK) to test an application. The generating includes determining one or more faults based on codes associated with the SDK and a frequency of occurrences of faults while executing the SDK. A fault injector automatically injects the determined faults in select layers of code in the SDK and generates fault configuration data associated with the automatically injected faults in the SDK. The fault configuration data describes faults that have been injected in the fault-enabled SDK to test an application. The fault-enabled SDK tests the application without needs for modifying the application code for testing purposes. The fault-enabled SDK further provides types of faults that may be common in using the SDK without requiring application developers to have detailed understanding of internals of the SDK to test the application with simulated faults.