Abstract: A computer-implemented system, computer-implemented method, and computer-program product includes receiving, via a graphical user interface, a request to generate an initial design of experiment plan based on one or more experiment factors; generating a first plan settings container object that represents the initial design of experiment plan in computer memory; and instantiating, within the graphical user interface, a plan explorer section that includes a plan settings graphical entry that displays a graphical representation of a plan factors data object and a plan model data object associated with the first plan settings container object.

Abstract: A computer-implemented system, computer-implemented method, and computer-program product includes receiving, via a graphical user interface, a request to generate an initial design of experiment plan based on one or more experiment factors; generating a first plan settings container object that represents the initial design of experiment plan in computer memory; and instantiating, within the graphical user interface, a plan explorer section that includes a plan settings graphical entry that displays a graphical representation of a plan factors data object and a plan model data object associated with the first plan settings container object.

Abstract: A computer-implemented system, computer-implemented method, and computer-program product includes receiving, via a graphical user interface, a request to generate an initial design of experiment plan based on one or more experiment factors; generating a first plan settings container object that represents the initial design of experiment plan in computer memory; and instantiating, within the graphical user interface, a plan explorer section that includes a plan settings graphical entry that displays a graphical representation of a plan factors data object and a plan model data object associated with the first plan settings container object.

Abstract: A system, method, and computer-program product includes obtaining application configuration data; computing, via an execution of a designed experiment, a plurality of application usability tests based on the application configuration data; generating a computer-executable application based at least on the plurality of application usability tests; and deploying the computer-executable application to a target computing environment for execution by one or more users.

Abstract: A computing device receives a request requesting a screening design for an experiment. The device obtains factors for screening. A first factor has a first set of candidate inputs comprising at least two candidate inputs for allowable inputs in the experiment. A second factor has a second set of candidate inputs comprising at least three candidate inputs for allowable inputs in the experiment. The device receives an indication of a run size. The device generates the screening design by assigning, based on the run size, the first factor to a two-level group that only allows at most two allowable inputs for the first factor in the experiment. The device generates the screening design by assigning, based on the initial run size, the second factor to a three-level group that only allows at most three allowable inputs for the second factor in the experiment. The device outputs the screening design.

Abstract: A computing device obtains first and second factors for a nesting design and first and second sets of candidate options for the first and second factors, respectively. The computing device also receives a nesting indication that the second factor is nested within the first factor. The computing device generates the nesting design by portioning the first and second sets of candidate options into respective first and second different sets of groups. Based on the nesting indication, the computing device generates an assignment of groups for a design, and also selects options in the nesting design for the first and second factors based on the assignment of groups. The computing device also generates terms for a computer model for a computer simulation of the nesting design, as well as one or more computer-generated assessments of the nesting design based on the computer simulation.

Abstract: A computing device receives a request requesting a screening design for an experiment. The device obtains, for the screening design, factors for screening in the experiment. A first factor is a categorical factor with a first set of candidate inputs comprising at least three candidate inputs in the experiment. A second factor is a continuous factor with a second set of candidate inputs comprising candidate input options within range(s) for the second factor. The device receives an indication of a run size that is a user-requested quantity of runs for the screening design. The device generates the screening design based on the run size. The device outputs the screening design. The screening design comprises runs of a quantity based on the user-requested quantity of runs for the screening design. The runs comprise the first set of candidate inputs and at least three inputs of the second set of candidate inputs.

Abstract: Techniques are described for providing a built-in “app” editor for an information technology (IT) and security operations application that enables users to create, modify, and test operation of apps under development within the editor. Some IT and security operations applications enable users to extend the applications by adding connectivity to third party technologies to run custom actions. For example, a user might create a custom app to enable an IT and security operations application to connect to an external service providing information about malicious Internet Protocol (IP) addresses, to connect to a relevant cloud provider service, or to interact with a firewall or other type of computing device used in a user's computing environment. Given the broad set of technologies that can be orchestrated by an IT and security operations application, apps broadly enable users to add custom functionality to interface with virtually any technology of interest.

Abstract: A system, method, and computer-program product includes displaying a plurality of factor-setting user interface (UI) control elements configured to receive an input of characters for specifying a set of design of experiment factors for creating a design of experiment (DOE), displaying a plurality of factor type UI control elements configured to receive input for specifying a factor type of a plurality of factor types, displaying a plurality of dynamic rows of editable UI control elements configured to receive inputs of experimental values for the set of DOE factors, and displaying a composite factor UI control component configured to receive inputs for generating one or more control signals that add or remove one or more DOE factors of the set of DOE factors.

Abstract: A system, method, and computer-program product includes displaying a plurality of factor-setting user interface (UI) control elements configured to receive an input of characters for specifying a set of design of experiment factors for creating a design of experiment (DOE), displaying a plurality of factor type UI control elements configured to receive input for specifying a factor type of a plurality of factor types, displaying a plurality of dynamic rows of editable UI control elements configured to receive inputs of experimental values for the set of DOE factors, and displaying a composite factor UI control component configured to receive inputs for generating one or more control signals that add or remove one or more DOE factors of the set of DOE factors.

Abstract: Described herein are techniques are provided for enabling a security orchestration, automation, and response (SOAR) service to automatically manage apps used to interface with an integrated security operations service and other related devices and services. Further described herein is a SOAR app generator service or application used to automate the creation of apps for a SOAR service based on application programming interfaces (API) specifications for related devices or services, as well as visual playbook editor interfaces for a SOAR service that enable the configuration of complex action input parameters including arrays and objects.

Abstract: A computing device receives user input for a design of an experiment. The user input indicates respective factor identities for factors in the design of the experiment, respective response identities for responses to options for the factors in the design, and a user-defined objective for the one or more responses. Additionally, based on the user input, the computing device displays a subset of a set of multiple model types and a user-definable amount of design runs for the design. Each design run presents settings according to the design for each of the factors. The computing device also receives settings indicating a user-selected model type from the subset and a user-defined amount of design runs, and based on the settings, selects one or more design construction criteria for generating the design. The computing device then generates the design according to the design construction criteria.

Abstract: A computing device obtains first and second factors for a nesting design and first and second sets of candidate options for the first and second factors, respectively. The computing device also receives a nesting indication that the second factor is nested within the first factor. The computing device generates the nesting design by portioning the first and second sets of candidate options into respective first and second different sets of groups. Based on the nesting indication, the computing device generates an assignment of groups for a design, and also selects options in the nesting design for the first and second factors based on the assignment of groups. The computing device also generates terms for a computer model for a computer simulation of the nesting design, as well as one or more computer-generated assessments of the nesting design based on the computer simulation.

Abstract: An apparatus includes a processor to: generate variants of an experiment design based on varied parameters; for each variant, estimate terms based on the model, and derive an optimality value; present a table of the variants including a column for each varied parameter and a column for the optimality value, a row for each variant, and a bar graph for each column depicting a distribution of the values therein; present function controls operable to select a function to perform on row(s) of the table in response to selection of a bar of a bar graph of a column; in response to selection of a function, change the current function to the selected function; and in response to a selection of a bar of a bar graph of a column, perform the current function on row(s) based on instances of the value associated with selected bar.

Abstract: An apparatus includes a processor to: present prompts guiding selection of first subset terms for estimation of variants of an experiment design based on a model thereof, and second subset terms for estimation using Bayesian modification; monitor for selections of term; in response to each change in the first subset terms, determine whether all first subset terms can be estimated based on the model; in response to the first subset including too many terms, present an indication of too many terms being selected for estimation based on the model; in response to the first subset including fewer terms than can be estimated based on the model, present an indication that more terms could be selected for estimation based on the model; and for each variant of the experiment design, estimate each first subset term based on the model, and estimate each second subset term using Bayesian modification.

Abstract: An apparatus includes a processor to: present prompts guiding selection of first subset terms for estimation of variants of an experiment design based on a model thereof, and second subset terms for estimation using Bayesian modification; monitor for selections of term; in response to each change in the first subset terms, determine whether all first subset terms can be estimated based on the model; in response to the first subset including too many terms, present an indication of too many terms being selected for estimation based on the model; in response to the first subset including fewer terms than can be estimated based on the model, present an indication that more terms could be selected for estimation based on the model; and for each variant of the experiment design, estimate each first subset term based on the model, and estimate each second subset term using Bayesian modification.

Abstract: An apparatus includes a processor to: generate variants of an experiment design based on varied parameters; for each variant, estimate terms based on the model, and derive an optimality value; present a table of the variants including a column for each varied parameter and a column for the optimality value, a row for each variant, and a bar graph for each column depicting a distribution of the values therein; present function controls operable to select a function to perform on row(s) of the table in response to selection of a bar of a bar graph of a column; in response to selection of a function, change the current function to the selected function; and in response to a selection of a bar of a bar graph of a column, perform the current function on row(s) based on instances of the value associated with selected bar.

Abstract: Portable containers for people to provide cleanup activity while hiking, running, hunting, camping, enjoying snow sports, or otherwise enjoying the outdoors. The portable containers can stay substantially clean due to a water-resistant coating. The portable containers can include compact folding where the container can roll-up to carry the most trash with the least amount of space. The portable containers can be lightweight making it easy to carry for all outdoor adventures. The portable containers can enable cleanliness and convenience in a hands-free solution including a pull tab to open a top opening thereof. The portable container can include an elastic or inelastic cord tensioner and spring steel system used to keep the opening in an increased open area state for easy hands-free access to the interior. The portable container can include a bottom opening zipper for hands-free gravity enabled disposal of trash and waste held within the portable container.

Abstract: System and methods for aligning event data recorded by recording devices. Recording devices create, transmit, and store alignment data. Alignment data created by a recording device is stored in the memory of the recording device with a time that is maintained by the recording device and that is relative to the time of event data recorded by the recording device that creates the alignment data. Recording devices further receive and store transmitted alignment data. Alignment data received by a recording device is stored in the memory of the recording device with a time that is maintained by the receiving recording device and that is relative to the time of event data recorded by the recording device that creates alignment data. Stored alignment data may be used to align the playback of event data of devices that have the same alignment data.

Abstract: System and methods for aligning event data recorded by recording devices. Recording devices create, transmit, and store alignment data. Alignment data created by a recording device is stored in the memory of the recording device with a time that is maintained by the recording device and that is relative to the time of event data recorded by the recording device that creates the alignment data. Recording devices further receive and store transmitted alignment data. Alignment data received by a recording device is stored in the memory of the recording device with a time that is maintained by the receiving recording device and that is relative to the time of event data recorded by the recording device that creates alignment data. Stored alignment data may be used to align the playback of event data of devices that have the same alignment data.