Abstract: The present disclosure discloses the system and method for efficient file storage and management. The method includes collecting information on access of different files by different applications on a master storage. The collected information is then normalized within a predetermined range. Additionally, the method includes training a machine learning model with the normalized information to predict which of the files should be stored in a cache. The cache is ten implemented by storing predicted files in the cache. Consequently, the different applications then access one of the predicted files in the cache without making multiple copies of the predicted files.

Abstract: The present disclosure discloses the system and method for efficient file storage and management. The method includes collecting information on access of different files by different applications on a master storage. The collected information is then normalized within a predetermined range. Additionally, the method includes training a machine learning model with the normalized information to predict which of the files should be stored in a cache. The cache is ten implemented by storing predicted files in the cache. Consequently, the different applications then access one of the predicted files in the cache without making multiple copies of the predicted files.

Abstract: Techniques are described for providing a natural language network security policy assistant for allowing a network administrator to implement network security policies using natural language security policy requests. A natural language request can be received by a user and can be translated using Artificial Intelligence into one or more security policy clauses. If the natural language security policy request leads to ambiguities with regard to intended security policies, one or more clarifying questions can be generated as natural language questions and sent to the user for clarification. One or more security policies can be implemented based on the one or more security policy clauses generated in response to the natural language security policy request and/or the natural language response to the clarifying questions.

Abstract: As impact quotient for a test automate can be determined and assigned based on factors such as static rules, results of a software analysis of the test automate, results of an analysis of historical data regarding the test automate, and a functional expert opinion. The factors used in the impact quotient determination can be assigned different weights which are adjustable based on the functional expert opinion. A test automate whose assigned impact quotient is below a threshold can be disabled and thus excluded from continuous executions. A test automate whose assigned impact quotient is not below the threshold can maintain an enabled status; updated impact quotients can later be determined for the test automate in response to prompts, in response to which the test automate can either maintain its enabled status or be disabled. Accordingly, low impact test automates can be removed from the pool of continuously executed test automates.

Abstract: Techniques are described for providing a natural language network security policy assistant for allowing a network administrator to implement network security policies using natural language security policy requests. A natural language request can be received by a user and can be translated using Artificial Intelligence into one or more security policy clauses. If the natural language security policy request leads to ambiguities with regard to intended security policies, one or more clarifying questions can be generated as natural language questions and sent to the user for clarification. One or more security policies can be implemented based on the one or more security policy clauses generated in response to the natural language security policy request and/or the natural language response to the clarifying questions.

Abstract: Techniques and solutions are provided for increasing the energy efficiency of computing code. Many computing operations can be implemented in a number of different ways. While the end result of each implementation may be the same, the energy efficiency of the implementations can vary dramatically. Disclosed techniques provide rules that can be used to analyze code for a particular implementation of an operation. If a rule is triggered, a recommendation to replace the implementation with a more energy efficient implementation can be provided, or the code can automatically be changed to include the more energy efficient implementation. Techniques for defining rules are also provided, such as by measuring or estimating energy used by various ways of implementing an operation. Measurement or estimation of energy used during code execution can be performed in a containerized environment, such as to provide improved accuracy, and allow for parallelization.

Abstract: The present disclosure provides techniques and solutions for automating the scheduling or execution of software tests defined for an increment to one or more software artifacts as the increment undergoes status changes during a development or release process. For example, tests can be executed or scheduled when an increment changes from a development landscape to a qualification landscape. A timeline scenario is defined that includes one or more timelines. The timelines include information useable to identify an increment and its associated tests, as well as configuration information for an entity where the tests will be executed. The increment is monitored, and tests specified in an appropriate timeline are executed or scheduled for execution when the timeline's associated status change is detected.

Abstract: Techniques are described for providing a natural language network security policy assistant for allowing a network administrator to implement network security policies using natural language security policy requests. A natural language request can be received by a user and can be translated using Artificial Intelligence into one or more security policy clauses. If the natural language security policy request leads to ambiguities with regard to intended security policies, one or more clarifying questions can be generated as natural language questions and sent to the user for clarification. One or more security policies can be implemented based on the one or more security policy clauses generated in response to the natural language security policy request and/or the natural language response to the clarifying questions.

Abstract: According to some embodiments, systems and methods are provided, including a memory storing processor-executable code; and a processing unit to execute the executable program code to: execute an automation test for a user interface application, wherein execution of the automation test includes accessing a web-object; determine whether the web-object is included in an object repository; in a case it is determined the web-object is not included in the object repository, create the web-object in the object repository; and in a case it is determined the web-object is included in the object repository: determine whether the accessed web-object includes at least one different property from the web-object included in the object repository; and update the web-object included in the object repository with the at least one different property in the accessed web-object. Numerous other aspects are provided.

Abstract: Techniques and solutions are provided for increasing the energy efficiency of computing code. Many computing operations can be implemented in a number of different ways. While the end result of each implementation may be the same, the energy efficiency of the implementations can vary dramatically. Disclosed techniques provide rules that can be used to analyze code for a particular implementation of an operation. If a rule is triggered, a recommendation to replace the implementation with a more energy efficiency implementation can be provided, or the code can automatically be changed to include the more energy efficient implementation. Techniques for defining rules are also provided, such as by measuring or estimating energy used by various ways of implementing an operation. Measurement or estimation of energy used during code execution can be performed in a containerized environment, such as to provide improved accuracy, and allow for parallelization.

Abstract: According to some embodiments, systems and methods are provided, including a memory storing processor-executable code; and a processing unit to execute the executable program code to: execute an automation test for a user interface application, wherein execution of the automation test includes accessing a web-object; determine whether the web-object is included in an object repository; in a case it is determined the web-object is not included in the object repository, create the web-object in the object repository; and in a case it is determined the web-object is included in the object repository: determine whether the accessed web-object includes at least one different property from the web-object included in the object repository; and update the web-object included in the object repository with the at least one different property in the accessed web-object. Numerous other aspects are provided.

Abstract: According to some embodiments, a system and method comprising a plurality of automation tools; and a shared automation module, coupled to the plurality of automation tools including: a computer processor; a computer memory, coupled to the computer processor, storing instructions that, when executed by the computer processor cause the shared automation module to: receive a selection of a first automation tool of the plurality of automation tools; receive a selection of a second automation tool of the plurality of automation tools; execute the first automation tool to generate a first automation tool output; and execute the second automation tool using the stored first automation tool output to generate a second automation tool output. Numerous other aspects are provided.

Abstract: A device extracts data files from different data sources, and processes the data files to generate data from the data files. The device trains a first artificial intelligence model and a second artificial intelligence model based on historical data parameters, wherein the historical data parameters are associated with historical data previously processed by the device. The device utilizes the trained first artificial intelligence model and the data to generate data parameters for the data, and utilizes the trained second artificial intelligence model, the data, and the data parameters to generate a data structure configuration. The device generates a data structure for the data based on the data parameters and the data structure configuration, stores the data in the data structure, and provides a user interface for accessing the data structure.

Abstract: Data is received that encapsulate a test case document including a series of test instructions written in natural language for testing a software application. The software application includes a plurality of graphical user interface views (e.g., views in a web browser, etc.). Thereafter, the test case document is parsed using at least one natural language processing algorithm. This parsing includes tagging instructions in the test case document with one of a plurality of pre-defined sequence labels. Subsequently, a test automate is generated using at least one machine learning model trained using historical test case documents, corresponding automates, and their successful executions and based on the tagged instructions in the test case document. The generated test automate includes one or more test scripts which, when executed, perform a testing sequence of the software application according to the series of test instructions. Related apparatus, systems, techniques and articles are also described.

Abstract: A device extracts data files from different data sources, and processes the data files to generate data from the data files. The device trains a first artificial intelligence model and a second artificial intelligence model based on historical data parameters, wherein the historical data parameters are associated with historical data previously processed by the device. The device utilizes the trained first artificial intelligence model and the data to generate data parameters for the data, and utilizes the trained second artificial intelligence model, the data, and the data parameters to generate a data structure configuration. The device generates a data structure for the data based on the data parameters and the data structure configuration, stores the data in the data structure, and provides a user interface for accessing the data structure.

Abstract: A file stored in a first portion of a computer memory of a computer is determined to be a malicious file. A duplicate of the file is stored in a quarantine area in the computer memory, the quarantine area being in a second portion of the computer memory that is different from the first portion of the computer memory. One or more protection processes are performed on the file. The determination that the file is a malicious file is determined to be a false positive and the file is restored, during a boot sequence, to a state prior to the one or more protection processes being performed on the file.

Abstract: A file stored in a first portion of a computer memory of a computer is determined to be a malicious file. A duplicate of the file is stored in a quarantine area in the computer memory, the quarantine area being in a second portion of the computer memory that is different from the first portion of the computer memory. One or more protection processes are performed on the file. The determination that the file is a malicious file is determined to be a false positive and the file is restored, during a boot sequence, to a state prior to the one or more protection processes being performed on the file.

Abstract: A method and apparatus for analyzing end user license agreements and taking action based on the analysis outcome. In one embodiment, the method includes sensing initialization of an installable software program installation, extracting a EULA from the installable during installation, pausing presentation of the EULA to a user, providing a database of suspect terms, analyzing whether a suspect term exists in the EULA, and presenting at least one of the EULA or a suspect term to the user.

Abstract: A file stored in a first portion of a computer memory of a computer is determined to be a malicious file. A duplicate of the file is stored in a quarantine area in the computer memory, the quarantine area being in a second portion of the computer memory that is different from the first portion of the computer memory. One or more protection processes are performed on the file. The determination that the file is a malicious file is determined to be a false positive and the file is restored, during a boot sequence, to a state prior to the one or more protection processes being performed on the file.

Abstract: Systems and methods for detecting malicious processes in a non-signature based manner are disclosed. The system and method may include gathering features of processes running on an electronic device, applying a set of rules to the features, and applying a statistical analysis to the results of the rules application to determine whether a process should be classified into one or more of a plurality of process categories.