Source code verification, including receiving a declaration of a variable as a secret type, determining if any source code is configured to use the variable as a type other than secret, and if it is determined that there is source code that will use the variable as a type other than secret, creating an exception in the source code verification process.

Systems, devices and methods are provided for testing a terminal application. For example, a test component is implanted into a source code program of a terminal application to be tested; one or more preset debugging codes are written into the source code program of the terminal application; one or more function addresses of the debugging codes in the source code program of the terminal application are acquired and registered; compiling and executing the source code program; an application test page is generated on a terminal user interface; and in response to a test execution instruction being triggered by a client on the application test page, the debugging codes is called via the function addresses in the test component to test the terminal application.

Provided are systems and methods for batching instructions of a bot during execution/runtime of the bot. The bot may be a software program that is designed to perform user interface interactions (e.g., button clicks, opening/closing pages, text entry, etc.) in place of a human. In one example, a method may include receiving a request to execute a bot program configured to perform a sequence of actions on a user interface of a software application, identifying a plurality of actions of the bot program that can be batched, assembling a plurality of instructions for performing the plurality of actions of the bot program into a batched payload, and transmitting an automation request with the batched payload to a back-end of the application on a server.

Systems and methods for checking program code are disclosed. The method includes executing a first check of the program code, and making a first determination about the first check. Metadata is stored based on making the first determination. A second check of the program code is run based on the metadata, and a result of the second check is stored in memory. The program code is executed based on the second check. In some embodiments, the method for checking program code includes running a simulation of a check of the program code by a processing device; storing a result of the simulation in memory; executing the check of the program code outside of the simulation; making a determination about the check outside of the simulation; retrieving a result stored in the memory based on the determination; and executing the program code based on the check.

Example robotic process automation systems and methods are described. In one implementation, a processing system receives one or more configuration options for a Bot, where the configuration options are associated with a design specification for the Bot. The processing system generates the Bot using the configuration options and instantiates the Bot on the processing system. A workflow associated with the design specification is executed by the Bot.

Disclosed herein are embodiments of systems, methods, and products comprise a processor, which provides runtime enforcement of data flow integrity. The processor accesses the application binary file from the disk to execute an application and translates the application binary into intermediate representation. The processor applies the logic of data flow integrity controls to the intermediate representation. Specifically, the processor identifies the vulnerable code in the intermediate representation. The processor applies data flow integrity controls to the vulnerable code. The processor adds simple instrumentation that only changes the application's behavior when unauthorized data tampering occurs while preserving the application's normal behavior. When certain operations may cause unauthorized data tampering, the processor takes proper measures to stop the operations. The processor translates the intermediate representation back to a machine code and replaces the original binary with the machine code.

A computerized method of content verification comprising using a server for receiving a first data from a host monitoring code embedded in a webpage or an application loaded from a content server and executed by a client device, the host monitoring code is executed by the client device during an execution of the webpage or the application which further embeds nesting element(s) for loading nested content from nested content server(s), the first data is indicative of the execution, receiving a second data indicative of the execution from a guest monitoring code embedded in the nested content, combining the first data and second data for compliance verification of the execution with one or more rules associated with the nested content and initiating action(s) according to the verification. Wherein the first data is not available to the guest monitoring code and the second data is not available to the host monitoring code.

A method for operating an electronic device is provided. The method includes checking context information for controlling a display divided into a first display and a second display, and controlling at least one of the first display and the second display based on the context information.

Embodiments presented herein provide techniques for evaluating for dynamically testing an application or “app” on multiple computing devices at the same time. Each device participating in a testing session runs a device agent which monitors and records user input directed to the app on that device. When a user input event occurs is directed to the app on one of the devices, the corresponding device agent translates the user input into replication events that can be broadcast to, and then replayed by, the app on the other computing devices participating in the testing session.

According to an aspect of an embodiment, a method may include identifying a fault at a fault location in a software program using a test suite. The method may also include determining multiple textual similarity scores by determining a textual similarity score with respect to each of multiple repair candidates for the fault. In addition, the method may include sorting the repair candidates based on the textual similarity scores. The method may also include selecting a particular repair candidate from the repair candidates based on the sorting. Moreover, the method may include implementing the particular repair candidate at the fault location based on the selection of the particular repair candidate.