Patent Grant
11829953
The present disclosure relates to systems and methods for collaborative work systems. More particularly, disclosed systems and methods provide improvements in collaborative software development systems, providing controls for organizing and visualizing data in one or more databases.
Operation of modern enterprises can be complicated and time consuming. In many cases, managing the operation of a single project requires integration of several employees, departments, and other resources of the entity. To manage the challenging operation, project management software applications may be used. Such software applications allow a user to organize, plan, and manage resources by providing project-related information in order to optimize the time and resources spent on each project. It would be useful to improve these software applications to increase operation management efficiency.
Software development often involves different methodologies or frameworks depending on the use case and needs of the software product. Scrums and other project management techniques may assist in managing software development and completion of features within a project. Agile methods of management may include scrums, or iterative, incremental frameworks for developing and sustaining products. Software development may include sprints to manage work for development teams. Sprints, which may be an iterative timeframe for development, may be used across a variety of tasks or goals for a project or multiple projects. As such, it may be beneficial to utilize tools to track and assist teams with tasks and sprints.
In some examples, data boards or tables may contain various information regarding software development, including data about tasks and sprints of a project. Sometimes, such boards and tables may be difficult to set up for use with sprints because, for example, data may be presented in a manner which may not capture all the details of the statuses of sprints. Software sprints may be difficult to scale and manage a complex variety of tasks and sprints across projects. For example, users of a software management tool may experience difficulty in building a sprint framework. The sprint framework may not display sprint data in an efficient or effective manner. Difficulty in associating tasks and project data with different sprints may lead to overcomplicated boards that may be difficult for a user to operate. Improvements in sprint management tools are desirable to address these technical drawbacks.
Consistent with disclosed embodiments, systems, methods, and computer readable media for performing operations for managing a plurality of sprints using a plurality of electronically linked boards. The at least one processor may perform operations comprising generating a low-level board with rows and columns, the rows and columns for containing sprint-related function data associated with the plurality of sprints. The at least one processor may perform operations comprising generating at least one internal column and at least one external column on the low-level board, the at least one external column for containing links to at least one associated high-level board. The at least one processor may perform operations comprising presenting an activatable internal group-by control, presenting an activatable external group-by control, receiving a first indication of activation of the internal group-by control, and in response to the first indication, organizing rows on the low-level board into first groups based on common internal column data. The at least one processor may perform operations comprising receiving a second indication of activation of the external group-by control, and in response to the second indication, reorganizing rows on the low-level board into second groups by common external column data, accessing on the low-level board, the links to the at least one associated high-level board, extracting data from the at least one associated high-level board, and importing the extracted data onto the low-level board.
Consistent with disclosed embodiments, systems, methods, and computer readable media for managing at least one task across a plurality of workflow management boards based on electronic data value changes across the plurality of workflow management boards are disclosed. The method may comprise generating a low-level board with rows and columns, the rows and columns for containing sprint-related function data associated with a plurality of sprints. The method may comprise generating at least one internal column and at least one external column on the low-level board, the at least one external column for containing links to at least one associated high-level board. The method may comprise presenting an activatable internal group-by control, presenting an activatable external group-by control, receiving a first indication of activation of the internal group-by control, and in response to the first indication, organizing rows on the low-level board into first groups based on common internal column data. The method may comprise receiving a second indication of activation of the external group-by control, and, in response to the second indication, reorganizing rows on the low-level board into second groups by, common external column data, accessing on the low-level board, the links to the at least one associated high-level board, extracting data from the at least one associated high-level board, and importing the extracted data onto the low-level board.
Consistent with disclosed embodiments, systems, methods, and computer readable media for managing at least one task across a plurality of workflow management boards based on electronic data value changes across the plurality of workflow management boards are disclosed. Systems, methods, devices, and non-transitory computer readable media may comprise at least one processor. The at least one processor may be configured to generate a low level board with rows and columns, the rows and columns for containing sprint-related function data associated with a plurality of sprints. The at least one processor may be configured to generate at least one internal column and at least one external column on the low-level board, the at least one external column for containing links to at least one associated high-level board. The at least one processor may be configured to present an activatable internal group-by control, present an activatable external group-by control, receive a first indication of activation of the internal group-by control, in response to the first indication, organize rows on the low-level board into first groups based on common internal column data. The at least one processor may be configured to receive a second indication of activation of the external group-by control, and in response to the second indication, reorganize rows on the low-level board into second groups by common external column data, access on the low-level board, the links to the at least one associated high-level board, extract data from the at least one associated high-level board, and, import the extracted data onto the low-level board.
Exemplary embodiments are described with reference to the accompanying drawings. The figures are not necessarily drawn to scale. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the spirit and scope of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It should also be noted that as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
In the following description, various working examples are provided for illustrative purposes. However, is to be understood the present disclosure may be practiced without one or more of these details.
Throughout, this disclosure mentions “disclosed embodiments,” which refer to examples of inventive ideas, concepts, and/or manifestations described herein. Many related and unrelated embodiments are described throughout this disclosure. The fact that some “disclosed embodiments” are described as exhibiting a feature or characteristic does not mean that other disclosed embodiments necessarily share that feature or characteristic.
This disclosure presents various mechanisms for collaborative work systems. Such systems may involve software that enables multiple users to work collaboratively. By way of one example, workflow management software may enable various members of a team to cooperate via a common online platform. It is intended that one or more aspects of any mechanism may be combined with one or more aspect of any other mechanisms, and such combinations are within the scope of this disclosure.
This disclosure is constructed to provide a basic understanding of a few exemplary embodiments with the understanding that features of the exemplary embodiments may be combined with other disclosed features or may be incorporated into platforms or embodiments not described herein while still remaining within the scope of this disclosure. For convenience, and form of the word “embodiment” as used herein is intended to refer to a single embodiment or multiple embodiments of the disclosure.
Certain embodiments disclosed herein include devices, systems, and methods for collaborative work systems that may allow a user to interact with information in real time. To avoid repetition, the, functionality of some embodiments is described herein solely in connection with a processor or at least one processor. It is to be understood that such exemplary descriptions of functionality apply equally to methods and computer readable media and constitutes a written description of systems, methods, and computer readable media. The underlying platform may allow a user to structure a systems, methods, or computer readable media in many ways using common building blocks, thereby permitting flexibility in constructing a product that suits desired needs. This may be accomplished through the use of boards. A board may be a table configured to contain items (e.g., individual items presented in horizontal rows) defining objects or entities that are managed in the platform (task, project, client, deal, etc.). Unless expressly noted otherwise, the terms “board” and “table” may be considered synonymous for purposes of this disclosure. In some embodiments, a board may contain information beyond which is displayed in a table. Boards may include sub-boards that may have a separate structure from a board, Sub-boards may be tables with sub-items that may be related to the items of a board, Columns intersecting with rows of items may together define cells in which data associated with each item may be maintained. Each column may have a heading or label defining an associated data type. When used herein in combination with a column, a row may be presented horizontally and a column vertically. However, in the broader generic sense as used herein, the term “row” may refer to one or more of a horizontal and/or a vertical presentation. A table or tablature as used herein, refers to data presented in horizontal and vertical rows, (e.g., horizontal rows and vertical columns) defining cells in which data is presented. Tablature may refer to any structure for presenting data in an organized manner, as previously discussed, such as cells presented in horizontal rows and vertical columns, vertical rows and horizontal columns, a tree data structure, a web chart, or any other structured representation, as explained throughout this disclosure. A cell may refer to a unit of information contained in the tablature defined by the structure of the tablature. For example, a cell may be defined as an intersection between a horizontal row with a vertical column in a tablature having rows and columns. A cell may also be defined as an intersection between a horizontal and a vertical row, or as an intersection between a horizontal and a vertical column. As a further example, a cell may be defined as a node on a web chart or a node on a tree data structure. As would be appreciated by a skilled artisan, however, the disclosed embodiments are not limited to any specific structure, but rather may be practiced in conjunction with any desired organizational arrangement. In addition, tablature may include any, type of information, depending on intended use. When used in conjunction with a workflow management application, the tablature may include any information associated with one or more tasks, such as one or more status values, projects, countries, persons, teams, progress statuses, a combination thereof, or any other information related to a task.
While a table view may be one way to present and manage the data contained on a board, a table's or board's data may be presented in different ways. For example, in some embodiments, dashboards may be utilized to present or summarize data derived from one or more boards. A dashboard may be a non-table form of presenting data, using, for example, static or dynamic graphical representations. A dashboard may also include multiple non-table forms of presenting data. As discussed later in greater detail, such representations may include various forms of graphs or graphics. In some instances, dashboards (which may also be referred to more generically as “widgets”) may include tablature. Software links may interconnect one or more boards with one or more dashboards thereby enabling the dashboards to reflect data presented on the boards. This may allow, for example, data from multiple boards to be displayed and/or managed from a common location. These widgets may provide visualizations that allow a user to update data derived from one or more boards.
Boards (or the data associated with boards) may be stored in a local memory on a user device or may be stored in a local network repository. Boards may also be stored in a remote repository and may be accessed through a network. In some instances, permissions may be set to limit board access to the board's “owner” while in other embodiments a user's board may be accessed by other users through any of the networks described in this disclosure. When one user makes a change in a hoard, that change may be updated to the board stored in a memory or repository and may be pushed to the other user devices that access that same board. These changes may be made to cells, items, columns, boards, dashboard views, logical rules, or any other data associated with the boards. Similarly, when cells are tied together or are mirrored across multiple hoards, a change in one board may cause a cascading change in the tied or mirrored boards or dashboards of the same or other owners.
Boards and widgets may be part of a platform that may enable users to interact with information in real time in collaborative work systems involving electronic collaborative word processing documents. Electronic collaborative word processing documents (and other variations of the term) as used herein are not limited to only digital files for word processing, but may include any other processing document such as presentation slides, tables, databases, graphics, sound files, video files or any other digital document or file. Electronic collaborative word processing documents may include any digital file that may provide for input, editing, formatting, display, and/or output of text, graphics, widgets, objects, tables, links, animations, dynamically updated elements, or any other data object that may be used in conjunction with the digital file. Any information stored on or displayed from an electronic collaborative word processing document may be organized into blocks. A block may include any organizational unit of information in a digital file, such as a single text character, word, sentence, paragraph, page, graphic, or any combination thereof. Blocks may include static or dynamic information, and may be linked to other sources of data for dynamic updates. Blocks may be automatically organized by the system, or may be manually selected by a user according to preference. In one embodiment, a user may select a segment of any information in an electronic word processing document and assign it as a particular block for input, editing, formatting, or any other further configuration.
An electronic collaborative word processing document may be stored in one or more repositories connected to a network accessible by one or more users through their computing devices. In one embodiment, one or more users may simultaneously edit an electronic collaborative word processing document. The one or more users may access the electronic collaborative word processing document through one or more user devices connected to a network. User access to an electronic collaborative word processing document may be managed through permission settings set by an author of the electronic collaborative word processing document. An electronic collaborative word processing document may include graphical user interface elements enabled to support the input, display, and management of multiple edits made by multiple users operating simultaneously within the same document.
Various embodiments are described herein with reference to a system, method, device, or computer readable medium. it is intended that the disclosure of one is a disclosure of all. For example, it is to be understood that disclosure of a computer readable medium described herein also constitutes a disclosure of methods implemented by the computer readable medium, and systems and devices for implementing those methods, via for example, at least one processor. It is to be understood that this form of disclosure is for ease of discussion only, and one or more aspects of one embodiment herein may be combined with one or more aspects of other embodiments herein, within the intended scope of this disclosure.
Embodiments described herein may refer to a non-transitory computer readable medium containing instructions that when executed by at least one processor, cause the at least one processor to perform a method. Non-transitory computer readable mediums may be any medium capable of storing data in any memory in a way that may be read by any computing device with a processor to carry out methods or any other instructions stored in the memory. The non-transitory computer readable medium may be implemented as hardware, firmware, software, or any combination thereof. Moreover, the software may preferably be implemented as an application program tangibly embodied on a program storage unit or computer readable medium consisting of parts, or of certain devices and/or a combination of devices. The application program may be uploaded to, and executed by, a machine comprising any suitable architecture. Preferably, the machine may be implemented on a computer platform having hardware such as one or more central processing units (“CPUs”), a memory, and input/output interfaces. The computer platform may also include an operating system and microinstruction code. The various processes and functions described in this disclosure may be either part of the microinstruction code or part of the application program, or any combination thereof, which may be executed by a CPU, whether or not such a computer or processor is explicitly shown. In addition, various other peripheral units may be connected to the computer platform such as an additional data storage unit and a printing unit. Furthermore, a non-transitory computer readable medium may be any computer readable medium except for a transitory propagating signal.
As used herein, a non-transitory computer-readable storage medium refers to any type of physical memory on which information or data readable by at least one processor can be stored. Examples of memory include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, any other optical data storage medium, any physical medium with patterns of holes, markers, or other readable elements, a PROM, an EPROM, a FLASH-EPROM or any other flash memory, NVRAM, a cache, a register, any other memory chip or cartridge, and networked versions of the same. The terms “memory” and “computer-readable storage medium” may refer to multiple structures, such as a plurality of memories or computer-readable storage mediums located within an input unit or at a remote location. Additionally, one or more computer-readable storage mediums can be utilized in implementing a computer-implemented method. The memory may include one or more separate storage devices collocated or disbursed, capable of storing data structures, instructions, or any other data. The memory may further include a memory portion containing instructions for the processor to execute. The memory may also be used as a working scratch pad for the processors or as a temporary storageAccordingly, the term computer-readable storage medium should be understood to include tangible items and exclude carrier waves and transient signals.
Some embodiments may involve at least one processor. Consistent with disclosed embodiments, “at least one processor” may constitute any physical device or group of devices having electric circuitry that performs a logic operation on an input or inputs. For example, the at least one processor may include one or more integrated circuits (IC), including application-specific integrated circuit (ASIC), microchips, microcontrollers, microprocessors, all or part of a central processing unit (CPU), graphics processing unit (GPU), digital signal processor (DSP), field-programmable gate array (FPGA), server, virtual server, or other circuits suitable for executing instructions or performing logic operations. The instructions executed by at least one processor rimy, for example, be pre-loaded into a memory integrated with or embedded into the controller or may be stored in a separate memory. The memory may include a Random Access Memory (RAM), a Read-Only Memory (ROM), a hard disk, an optical disk, a magnetic medium, a flash memory, other permanent, fixed, or volatile memory, or any other mechanism capable of storing instructions. In some embodiments, the at least one processor may include more than one processor. Each processor may have a similar construction or the processors may be of differing constructions that are electrically connected or disconnected from each other. For example, the processors may be separate circuits or integrated in a single circuit. When more than one processor is used, the processors may be configured to operate independently or collaboratively, and may be co-located or located remotely from each other. The processors may be coupled electrically, magnetically, optically, acoustically, mechanically or by other means that permit them to interact.
Consistent with the present disclosure, disclosed embodiments may involve a network. A network may constitute any type of physical or wireless computer networking arrangement used to exchange data. For example, a network may be the Internet, a private data network, a virtual private network using a public network, a Wi-Fi network, a LAN or WAN network, a combination of one or more of the forgoing, and/or other suitable connections that may enable information exchange among various components of the system. In sonic embodiments, a network may include one or more physical links used to exchange data, such as Ethernet, coaxial cables, twisted pair cables, fiber optics, or any other suitable physical medium for exchanging data. A network may also include a public switched telephone network (“PSTN”) and/or a wireless cellular network. A network may be a secured network or unsecured network. In other embodiments, one or more components of the system may communicate directly through a dedicated communication network. Direct communications may use any suitable technologies, including, for example, BLUETOOTH™, BLUETOOTH LE™ (BLE), Wi-Fi, near field communications (NFC), or other suitable communication methods that provide a medium for exchanging data and/or information between separate entities.
Certain embodiments disclosed herein may also include a computing device for generating features for work collaborative systems, the computing device may include processing circuitry communicatively connected to a network interface and to a memory, therein the memory contains instructions that, when executed by the processing circuitry, configure the computing device to receive from a user device associated with a user account instruction to generate a new column of a single data type for a first data structure, wherein the first data structure may be a column oriented data structure, and store, based on the instructions, the new column within the column-oriented data structure repository, wherein the column-oriented data structure repository may be accessible and may be displayed as a display feature to the user and at least a second user account. The computing devices may be devices such as mobile devices, desktops, laptops, tablets, or any other devices capable of processing data. Such computing devices may include a display such as an LED display, augmented reality (AR), virtual reality (VR) display.
Disclosed embodiments may include and/or access a data structure. A data structure consistent with the present disclosure may include any collection of data values and relationships among them. The data may be stored linearly, horizontally, hierarchically, relationally, non-relationally, uni-dimensionally, multidimensionally, operationally, in an ordered manner, in an unordered manner, in an object-oriented manner, in a centralized manner, in a decentralized manner, in a distributed manner, in a custom manner, or in any manner enabling data access. By way of non-limiting examples, data structures may include an array, an associative array, a linked list, a binary tree, a balanced tree, a heap, a stack, a queue, a set, a hash table, a record, a tagged union, ER model, and a graph. For example, a data structure may include an XML database, an RDBMS database, an SQL database or NoSQL alternatives for data storage/search such as, for example, MongoDB, Redis, Couchbase, Datastax Enterprise Graph, Elastic Search, Splunk, Solr, Cassandra, Amazon DynamoDB, Scylla, HBase, and Neo4J. A data structure may be a component of the disclosed system or a remote computing component (e.g., a cloud-based data structure). Data in the data structure may be stored in contiguous or non-contiguous memory. Moreover, a data structure, as used herein, does not require information to be co-located. It may be distributed across multiple servers, for example, that may be owned or operated by the same or different entities. Thus, the term “data structure” as used herein in the singular is inclusive of plural data structures.
Certain embodiments disclosed herein may include a processor configured to perform methods that may include triggering an action in response to an input. The input may be from a user action or from a change of information contained in a user's table or board, in another table, across multiple tables, across multiple user devices, or from third-party applications. Triggering may be caused manually, such as through a user action, or may be caused automatically, such as through a logical rule, logical combination rule, or logical templates associated with a board. For example, a trigger may include an input of a data item that is recognized by at least one processor that brings about another action.
In some embodiments, the methods including triggering may cause an alteration of data and may also cause an alteration of display of data contained in a board or in memory. An alteration of data may include a recalculation of data, the addition of data, the subtraction of data, or a rearrangement of information. Further, triggering may also cause a communication to be sent to a user, other individuals, or groups of individuals. The communication may be a notification within the system or may be a notification outside of the system through a contact address such as by email, phone call, text message, video conferencing, or any other third-party communication application.
Some embodiments include one or more of automations, logical rules, logical sentence structures and logical (sentence structure) templates. While these terms are described herein in differing contexts, in a broadest sense, in each instance an automation may include a process that responds to a trigger or condition to produce an outcome; a logical rule may underly the automation in order to implement the automation via a set of instructions; a logical sentence structure is one way for a user to define an automation; and a logical template/logical sentence structure template may be a fill-in-the-blank tool used to construct a logical sentence structure. While all automations may have an underlying logical rule, all automations need not implement that rule through a logical sentence structure. Any other manner of defining a process that respond to a trigger or condition to produce an outcome may be used to construct an automation.
Other terms used throughout this disclosure in differing exemplary conte is may generally share the following common definitions.
In some embodiments, machine learning algorithms (also referred to as machine learning models or artificial intelligence in the present disclosure) may be trained using training examples, for example in the cases described below. Some non-limiting examples of such machine learning algorithms may include classification algorithms, data regressions algorithms, image segmentation algorithms, visual detection algorithms (such as object detectors, face detectors, person detectors, motion detectors, edge detectors, etc.), visual recognition algorithms (such as face recognition, person recognition, object recognition, etc.), speech recognition algorithms, mathematical embedding algorithms, natural language processing algorithms, support vector machines, random forests, nearest neighbors algorithms, deep learning algorithms, artificial neural network algorithms, convolutional neural network algorithms, recursive neural network algorithms, linear machine learning models, non-linear machine learning models, ensemble algorithms, and so forth. For example, a trained machine learning algorithm may, comprise an inference model, such as a predictive model, a classification model, a regression model, a clustering model, a segmentation model, an artificial neural network (such as a deep neural network, a convolutional neural network, a recursive neural network, etc,), a random forest, a support vector machine, and so forth. In some examples, the training examples may include example inputs together with the desired outputs corresponding to the example inputs. Further, in some examples, training machine learning algorithms using the training examples may generate a trained machine learning algorithm, and the trained machine learning algorithm may be used to estimate outputs for inputs not included in the training examples. In some examples, engineers, scientists, processes and machines that train machine learning algorithms may further use validation examples and/or test examples. For example, validation examples and/or test examples may include example inputs together with the desired outputs corresponding to the example inputs, a trained machine learning algorithm and/or an intermediately trained machine learning algorithm may be used to estimate outputs for the example inputs of the validation examples and/or test examples, the estimated outputs may be compared to the corresponding desired outputs, and the trained machine learning algorithm and/or the intermediately trained machine learning algorithm may be evaluated based on a result of the comparison. In some examples, a machine learning algorithm may have parameters and hyper parameters, where the hyper parameters are set manually by a person or automatically by a process external to the machine learning algorithm (such as a hyper parameter search algorithm), and the parameters of the machine learning algorithm are set by the machine learning algorithm according to the training examples. In some implementations, the hyper-parameters are set according to the training examples and the validation examples, and the parameters are set according to the training examples and the selected hyper-parameters.
Disclosed embodiments may involve managing a plurality of sprints using a plurality of electronically linked boards. A sprints may relate to a portion of development of a computer software, or a time period during which one or more individuals may work to develop or complete an improvement or addition to a system, computer program, software application, or other item. In some embodiments, a sprint may include strategies, plans, methods, or procedures for designating time frames, periods, or intervals for developing a product, solution, or service. For example, sprints may include strategies for issue management, team management, task management, scrums, frameworks, workflows, agile development, scrums, product development, software development, project management, product management, or any other planning method for software development, programming, application development, engineering. For example, sprints may include management strategies for achieving goals in designated time periods to develop a software product. In some embodiments, sprints may involve a series of iterations to separate a project or product into subcomponents of the project or product. For example, a sprint may include a management strategy to complete a product in a specific amount of time. In some embodiments, a sprint may include strategies for developing software within a specific, short, fixed-length time period. A skilled artisan may recognize that a sprint may involve iterations of planning, backlogs, scrum, review, user stories, or burn down charts. In some embodiments, a plurality of sprints may include at least one sprint occurring in series or parallel. Electronically linked boards may include boards, as described herein, which may connect, mirror, transmit, copy, relay, refer, share, or communicate data, inputs, outputs, features, details, or any other form of information. In some embodiments, electronically linked boards may share information between one or more boards. For example, data in rows and columns of a board may be shared with at least one other board. In some embodiments, stored data or metadata may identify one or more links between rows, columns, and/or cells of a high level board and a low level board. Disclosed embodiments may involve electronic data value changes across a plurality of workflow management boards. Workflow management may include infrastructure for set-up, performance and monitoring for a sequence of tasks, a series of steps to complete a specific task, organizing tasks, streamlining processes, routing, distribution, coordination, agile systems, lean systems, scrum systems, waterfall systems, Kanban systems, or adaptive systems. Electronic data value changes may include changes, alterations, transitions, or transformations in values of data or information.
Disclosed embodiments may involve managing time-sensitive tasks using electronically linked boards. Time-sensitive tasks may not be limited to sprints, as discussed herein. Time-sensitive tasks may include assignments with a dependency on time, such as timed projects, timed assignments, tasks classified by priority, iterative tasks, or periodical tasks. Disclosed embodiments may involve linking or connecting data and information regarding time-sensitive tasks between one or more boards. In some embodiments, time-sensitive data may be contained in columns external to a board. In some embodiments, time-sensitive task data may be contained in a high-level board. In some embodiments, a low-level board may be linked to at least one high-level board, and data associated with one or more time-sensitive tasks may be imported from one board to another. In some embodiments, linking boards and importing data may be performed in response to an indication of activation of one or more group-by controls.
Disclosed embodiments may involve generating a low-level board with rows and columns, the rows and columns for containing sprint-related function data associated with the plurality of sprints. In some embodiments, generating a board may include presenting or displaying at least one board including a low-level board. A low-level board may include at least one board containing, displaying, sharing, or presenting, information regarding project, product, or software development. A low-level board may include groupings of information presented in rows and columns of tables, as described herein. In some embodiments, a low-level board may contain rows and columns containing sprint-related function data. Sprint-related function data may include information or data such as to sprints, scrums, team members, tasks, persons, dates, issues, timelines, deadlines, goals, sprint summaries, statuses, progress, activity, or any other details regarding management of software development. For example, sprint-related function data may include features, tasks, owners, statuses, priorities, descriptions, due dates, timelines, bugs, roles, and other datum points.
In some embodiments, a low-level board may contain data corresponding to one or more tasks of a project, such as a software development project. A low-level board may be organized by project or specific tasks. Different tasks may be aggregated together and displayed on a table or board, such as a low-level board. In some embodiments, different low-level boards may contain information corresponding to different projects. For example, smaller projects within a larger a software development may each have a corresponding low-level board.
In some embodiments, at least one processor may generate at least one internal column and at least one external column on the low-level board. An internal column may include sets, categories, classifications, or other arrangements of storing information as described herein. In some embodiments, an internal column may include information or data collected, originating, or obtained from the same board or table the column exists in. In some embodiments, an internal column may contain data related to specific tasks of a project. For example, an internal column may contain information inputted directly into the cells of the column on the low-level board. In some embodiments, an internal column may not access data contained within boards different than the board the internal column exists in. An internal column may contain sprint-related function data. In some embodiments, an external column may include information or data collected, originating, or obtained from a board or table different from the board the column exists in. In some embodiments, an external column may access data contained within other boards or tables. For example, an external column may present data or information that is extracted from another board. In some embodiments, internal columns and external columns may, include blank values or cells with no value.
In some embodiments, at least one external column may link to at least one associated high-level board. In some embodiments, links may include connections between electronically linked boards, as described herein. Links may include forms of data sharing including communication and mirroring. For example, links may include connecting or communication between boards to mirror information such that data contained on one board is displayed on another board. A high-level board may include at least one board containing, displaying, sharing, or presenting information regarding project, product, or software development, or sprints. The high-level board may be organized differently than the low-level board. In some embodiments, the high-level board may organize or display information or data based on categories. In some embodiments, a high-level board may track, audit, monitor, or observe a project. For example, a high-level board may track a project across one or more sprints. The high-level board may contain high-level data or information regarding the project it tracks, including metadata. In some embodiments, an associated high-level board may correspond to data or information contained in a low-level board. In some embodiments, a low-level board may correspond to one or more high-level boards. For example, different groups of data contained in a low-level board may associate with different high-level boards.
Disclosed embodiments may involve each row of a plurality of rows on the at least one associated high-level board being configured to hold data associated with a specific sprint. A specific sprint may include sprints with different names, different goals, or different sprint data. As discussed herein, the high-level board may include a plurality of rows and columns. In some embodiments, each row in the high-level board may hold or contain data associated with different sprints. As an example, in high-level hoard 87-3-00, rows 87-3-40 include a plurality of rows each holding data associated with a different sprint. In some embodiments, the at least one associated high-level board may be configured to hold sprint backlog data or metadata. The high-level board may include sprint metadata, sprint name, sprint duration, sprint goals, risk, effort, uncertainty, task progress, backlog, bugs, activity status, and other indications or metadata. Sprint backlog data may include tasks, items, issues, bugs, or other work intended to be completed during a specific sprint. Metadata may include descriptions of other data including structure, identity, attributes, context, features, administration, or reference information. Metadata may include sets of data describing or giving information about other data or information. For example, metadata may describe information about a sprint, such as sprint name, duration, goals, risk, effort required, work complexity, uncertainty, dates, progress, tasks, backlogs, bugs, or status. In some embodiments, metadata may comprise sprint metadata including data associated with one or more attributes about a sprint.
In some embodiments, at least one processor may cause one or more displays to present an activatable internal group-by control. Activatable controls may include controls, triggers, switches, mechanisms, buttons, drop-downs, or other actuators for interacting with a board, dashboard, or other software configuration. Group-by controls may include a function or capability for sorting, arranging, categorizing, classifying, reorganizing, ordering, combining, or other organizing of information or data into sets, groups, or other divisions. Internal group-by controls may include organizing information based on information that is internal to the board. As discussed herein, internal may include information local to, directly inputted into, or accessible to a board. Disclosed embodiments may involve presenting an activatable external group-by control. External group-by controls may include organizing information based on information that is external to the board. As discussed herein, external may include information or data collected, originating, or obtained from a board or table different from the board the control is presented on.
In some embodiments, at least one processor may receive a first indication of activation of the internal group-by control. In some embodiments, an indication of activation may include a mouse click, press, gesture, or other feedback cue confirming a selection of an option. In some embodiments, an indication of activation may include a response of a change in configuration of a board. For example, a first indication of activation of an internal group-by column may involve selecting a criteria, rule, basis, standard, or grouping, such as internal data. In some embodiments, group-by control 87-4-00 may present options including selecting internal group-by controls 87-4-10. For example, receiving a first indication of activation may include selecting internal group-by controls 87-4-10 as a grouping basis. In some embodiments, the basis for grouping may depend on the internal column chosen.
In some embodiments in response to the first indication, at least one processor may organize rows on the low-level board into first groups based on common internal column data. Common internal column data may include data, values, entries, inputs or information contained in cells of internal columns. In some embodiments, common internal column data may comprise data values in a cell of internal columns with a value equivalent to one or more other data values in the same internal column. For example, an internal column may contain a set of data, and within the set, there may be at least one group of equivalent data such that one or more values are equivalent to each other, and each such group may be regarded as common internal data. The common internal data may serve as a basis to organize rows on the low-level board. In some embodiments, each set of equivalent data may represent a category, classification, or group to organize rows. Organizing rows may include arranging, grouping, ordering, assembling, structuring, or otherwise sorting rows of a board or table. For example, after receiving an indication of activation, rows may be organized on a low-level board according to first groups determined b common internal column data from a certain internal column groups may include a first classification of rows on the board.
Disclosed embodiments may involve receiving a second indication of activation of the external group-by control. In some embodiments, a second indication of activation of an external group-by column may involve selecting a criteria, rule, basis, standard, or grouping, such as external data. In some embodiments, group—by control 87-4-00 may present options including selecting external group-by controls 87-4-20. For example, receiving a second indication of activation may include selecting external group-by controls 87-4-10 as a grouping basis. In some embodiments, the basis for grouping may depend on the external column chosen.
In some embodiments in response to the second indication, at least one processor may reorganize rows on the low-level board into second groups based on common external column data. Common external column data may include data, values, entries, or information contained in cells of external columns. Common external common data may include data mirrored or linked from columns from other boards. In some embodiments, common external column data may comprise data values in a cell of external columns with a value equivalent to one or more other data values in the same external column. For example, an external column may contain a set of data, and within the set, there may be at least one group of equivalent data such that one or more values are equivalent to each other, and each such group may be regarded as common external data. The common external data may serve as a basis to reorganize rows on the low-level board. In some embodiments, each set of equivalent data may represent a category, classification, or group to organize rows. Reorganizing rows may include a new arrangement, grouping, ordering, assembling, structuring, or otherwise sorting of rows of a board or table. In some embodiments, reorganizing rows may include maintaining the same arrangement of one or more rows in the board. For example, after receiving an indication of activation, rows may be reorganized on a low-level board according to second groups determined by common external column data from a specific external column. Second groups may include a second classification of rows on the board. In some embodiments, the second classification may be the same as the first classification.
In some embodiments, in response to selection of an external group-by, a board may be reorganized by common external column data into second groups such that each second group may be a new heading determined by the common external column data. External data may be extracted from associated boards via the external columns, and the external data may be presented in the associated second group. In some embodiments, boards may be grouped by a relationship with another board.
In some embodiments, the external group-by control and internal group-by control may be configured for simultaneous reorganization of one or more rows on the low-level board, based on common internal column data and common external column data. Simultaneous performance may involve one or more processes or actions occurring in a similar time frame, caused by a common trigger, or executed on the same board. For example, the external group-by control and internal group-by control may be configured to simultaneously group a board based on one or more rule sets or predetermined settings.
In some embodiments, data associated with a specific sprint may be linked to the specific sprint via at least one external column. For example, sprint data may be contained in high-level board 87-3-00. In some embodiments, external column 87-3-30 may link data from another board to high-level board 87-3-30. Such data may include sprint data such as a sprint timeline or timeframe. The sprint data linked by external column 87-3-30 may then appear in the high-level board 87-3-00. In some embodiments, the external group-by may be configured to reorganize rows on the low-level board into a plurality of groups by common external column data, access on the low-level board, the additional links to the plurality of high-level boards, extract additional data from the plurality of associated high-level boards, and import the extracted data onto the low-level board. For example, a low-level board may be associated with a plurality of high-level boards, such as at least one high-level board containing sprint data for a specific project and one or more boards containing other data regarding software development. The external group-by may provide the option to link external columns containing data from these associated high-level boards to the low-level board. Common external column data may be used to reorganize the rows on the low-level board. The additional links may be accessed, and additional data from the associated high-level boards may be extracted, and imported onto the low-level board, as discussed herein.
As discussed herein, internal columns and external columns may also be comprised of linkage columns. Linkage columns may include columns within a board that may link the board with at least one other board. Linkage columns may connect, mirror, transmit, copy, relay, refer, share, or communicate data, inputs, outputs, features, details, or any other form of information between the one or more columns of the board. Disclosed embodiments may involve at least one external column being a linkage column. In some embodiments, the low-level board may include a plurality of linkage columns. A plurality of linkage columns may involve one or more linkage columns in the same board, which may link to one or more linkage columns in one or more separate boards. In some embodiments, each of the plurality of linkage columns may contain additional links to each of a plurality of associated high-level boards. As discussed herein, a board such as a low-level board may be connected to a plurality of associated high-level boards, which may comprise at least one high-level board. In some embodiments, additional links may comprise one or more links to a column of another board. For example, additional links on a low-level board may link to one or more linkage columns on at least one high-level board.
In some embodiments, at least one processor may access, on the low-level board, the links to the at least one associated high-level board. Accessing may include acquiring, reading, obtaining, connecting, locating, gathering, or transferring links, data, information, or values. In some embodiments, accessing links may include obtaining the rows or columns of a board or table. For example, accessing links may include obtaining the rows or columns of one or more high-level boards associated with a low-level board. In some embodiments, the at least one processor may extract data from the at least one associated high-level board. Extracting data may include retrieving, pulling out, capturing, restoring, or mirroring data, information, values, or metadata from a different board. In some embodiments, data may be extracted from multiple boards, such as multiple high-level boards. Disclosed embodiments may involve importing the extracted data onto the low-level board. Importing may involve bringing in, pulling in, conveying, transporting, moving, transferring, relaying, inserting, presenting, mirroring, copying displaying, or otherwise transmitting data or information. In some embodiments, importing extracted data may include transmitting information contained in one board to another. For example, importing extracted data may include pulling in data contained in a high-level board to a low-level board. In some embodiments, importing may include displaying the transmitted information or data. For example, importing extracted data may include copying data from one or more rows of columns of a table or board and presenting the copied data in another board.
As an example, low-level board 87-6-00 is an exemplary configuration of a low-level board containing imported extracted data. Low-level board may be associated with high-level board 87-3-00 (
In some embodiments, at least one processor may aggregate data from the items of the low-level board that are linked to. Low-level boards that are linked to may include boards that are linked to a column, row, cell, or other data value in a high-level board. Aggregation of data may include combining, collecting, mixing, summing, or processing data. Aggregation of data may include combining different sets, pieces, or values of data into one or more different sets of data. In some embodiments, aggregation of data may include processing different values of data and presenting them on a board as a different set of data or a summary of the data. For example, a low-level board linked to a high-level board corresponding to sprint data may have data aggregated. The data may be processed and presented on the low-level board. As an example, low-level board 87-6-00 may be grouped by sprints, and include priority data 87-6—45 regarding different tasks within the grouping of sprint two 87-6-10. Data aggregation may combine the different priority data from tasks within sprint two grouping 87-6-10, and combine the priority data and present it as aggregated data 87-6-50. In some embodiments, aggregated data 87-6-50 may be presented as a battery widget or pie chart, providing a summary or overview of the different values of priority data within the grouping.
In some embodiments, linkage between different boards, such as a low-level board and a high—level board, may be utilized for timed assignments, iterative projects, or projects with deadlines or specified timeframes. Timeframe data may be contained in a high-level board, and may be imported and presented on a low-level board.
In some embodiments, the imported data may influence one or more of a sorting or an arrangement of items in at least one group of the low-level board. Influencing may involve causing, determining, affecting, effecting, modifying, impacting, or inducing. In some embodiments, the imported data may influence a sorting or arrangement of items by determining the classification or categorization of data within the low-level board. For example, imported data such as sprint name may cause the low-level board to by categorized by names of the sprints.
The processing circuitry such as processing circuitry 87-7-110 may be coupled via a bus 87-7-105 to a memory 120.
The memory 87-7-120 may further include a memory portion 87-7-122 that may contain instructions that when executed by the processing circuitry 87-7-110, may perform the method described in more detail herein. The memory 87-7-120 may be further used as a working scratch pad for the processing circuitry 87-7-110, a temporary storage, and others, as the case may be. The memory 87-7-120 may be a volatile memory such as, but not limited to, random access memory (RAM), or non-volatile memory (NVM), such as, but not limited to, flash memory. The processing circuitry 87-7-110 may be further connected to a network device 87-7-140, such as a network interface card, for providing connectivity between the computing device 87-7-100 and a network, such as a network 87-8-210, discussed in more detail with respect to
The processing circuitry 87-7-110 and/or the memory 120 may also include machine-readable media for storing software. “Software” as used herein refers broadly to any type of instructions, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. Instructions may include code (e.g., in source code format, binary code format, executable code format, or any other suitable format of code), The instructions, when executed by the one or more processors, may cause the processing system to perform the various functions described in further detail herein,
One or more user devices 87-8-220-1 through user device 87-8-220-rn, where ‘m’ in an integer equal to or greater than 1, referred to individually as user device 87-8-220 and collectively as user devices 87-8-220, may be communicatively coupled with the computing device 87-7-100 via the network 87-8-210. A user device 87-8-220 may be for example, a smart phone, a mobile phone, a laptop, a tablet computer, a wearable computing device, a personal computer (PC), a smart television and the like. A user device 87-8-220 may be configured to send to and receive from the computing device 87-7-100 data and/or metadata associated with a variety of elements associated with single data type column-oriented data structures, such as columns, rows, cells, schemas, and the like.
One or more data repositories 87-8-230-1 through data repository 87-8-230-n, where ‘n’ in an integer equal to or greater than 1, referred to individually as data repository 87-8—87-8-230 and collectively as data repository 87-8-230, may be communicatively coupled with the computing device 87-7-100 via the network 87-8-210, or embedded within the computing device 87-7-100. Each data repository 87-8-230 may be communicatively connected to the network 87-8-210 through one or more database management services (DBMS) 87-8-235-1 through DBMS 87-8-235-n. The data repository 87-8-230 may be for example, a storage device containing a database, a data warehouse, and the like, that may be used for storing data structures, data items, metadata, or any information, as further described below. In some embodiments, one or more of the repositories may be distributed over several physical storage devices, e.g., in a cloud-based computing environment. Any storage device may be a network accessible storage device, or a component of the computing device 87-7-100.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. The materials, methods, and examples provided herein are illustrative only and not intended to be limiting.
Implementation of the method and system of the disclosed embodiments may involve performing or completing certain selected tasks or steps manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of preferred embodiments of the method and system of the disclosed embodiments, several selected steps may be implemented by hardware (HW) or by software (SW) on any operating system of any firmware, or by a combination thereof. For example, as hardware, selected steps of the disclosure could be implemented as a chip or a circuit. As software or algorithm, selected steps of the disclosure could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In any case, selected steps of the method and system of the disclosure could be described as being performed by a data processor, such as a computing device for executing a plurality of instructions.
As used herein, the terms “machine-readable medium” “computer-readable medium” refers to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal used to provide machine instructions and/or data to a programmable processor.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Although the present disclosure is described with regard to a “computing device”, a “computer”, or “mobile device”, it should be noted that optionally any device featuring a data processor and the ability to execute one or more instructions may be described as a computing device, including but not limited to any type of personal computer (PC), a server, a distributed server, a virtual server, a cloud computing platform, a cellular telephone, an IP telephone, a smartphone, a smart watch or a PDA (personal digital assistant). Any two or more of such devices in communication with each other may optionally comprise a “network” or a “computer network”.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (a LED (light-emitting diode), (I)LED (organic LED), or LCD (liquid crystal display) monitor/screen) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user can be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), and the Internet.
The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be appreciated that the above-described methods and apparatus may be varied in many ways, including omitting or adding steps, changing the order of steps and the type of devices used. It should be appreciated that different features may be combined in different ways. In particular, not all the features shown above in a particular embodiment or implementation are necessary in every embodiment or implementation of the present disclosure. Further combinations of the above features and implementations are also considered to be within the scope of some embodiments or implementations of the present disclosure.
While certain features of the described implementations have been illustrated as described herein, many modifications, substitutions, changes and equivalents will now occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fail within the scope of the implementations. It should be understood that they have been presented by way of example only, not limitation, and various changes in form and details may be made. Any portion of the apparatus and/or methods described herein may be combined in any combination, except mutually exclusive combinations. The implementations described herein can include various combinations and/or sub-combinations of the functions, components and/or features of the different implementations described.
Disclosed embodiments may include any one of the following features alone or in combination with one or more other features, whether implemented as a method, by at least one processor, and/or stored as executable instructions on non-transitory computer-readable media: A system for managing at least one task across a plurality of workflow management boards based on electronic data value changes across the plurality of workflow management boards, the system comprising at least one processor configured to: generate a low-level board with rows and columns, the rows and columns for containing sprint-related function data associated with a plurality of sprints; generate at least one internal column and at least one external column on the low-level board, the at least one external column for containing links to at least one associated high-level board; present an activatable internal group-by control; present an activatable external group-by control; receive a first indication of activation of the internal group—by control; in response to the first indication, organize rows on the low-level board into first groups based on common internal column data; receive a second indication of activation of the external group-by control; and in response to the second indication, reorganize rows on the low-level board into second groups by common external column data. The at least one processor may access, on the low-level board, the links to the at least one associated high-level board; extract data from the at least one associated high-level board; and import the extracted data onto the low-level board.
Disclosed embodiments may include any one of the following features alone or in combination with one or more other features, whether implemented as a method, by at least one processor, and/or stored as executable instructions on non-transitory computer readable media: generating a low-level board with rows and columns, the rows and columns for containing sprint—related function data associated with the plurality of sprints; generating at least one internal column and at least one external column on the low-level board, the at least external column for containing links to at least one associated high-level board; presenting an activatable internal group-by control; presenting an activatable external group-by control; receiving a first indication of activation of the internal group-by control; in response to the first indication, organizing rows on the low-level board into first groups based on common internal column data; receiving a second indication of activation of the external group-by control; and in response to the second indication: reorganizing rows on the low-level board into second groups by common external column data; accessing on the low-level board, the links to the at least one associated high-level board; extracting data from the at least one associated high-level board; and importing the extracted data onto the low-level board.
Disclosed embodiments may include any one of the following features alone or in combination with one or more other features, whether implemented as a method, by at least one processor, and/or stored as executable instructions on non—transitory computer readable media: generating a low-level board with rows and columns, the rows and columns for containing sprint-related function data associated with the plurality of sprints; generating at least one internal linkage column on the low-level board, the at least one linkage column for containing links to at least one associated high-level board; presenting an activatable group-by control; receiving an indication of activation of the group-by control on the linkage column, and in response to the indication, reorganizing rows on the low-level board into groups by common column data; accessing on the low-level board, the links to the at least one associated high-level board; extracting data from the at least one associated high-level board; and importing the extracted data onto the low-level board.
Disclosed embodiments may include each row of a plurality of rows on the at least one associated high-level board is configured to hold data associated with a specific sprint. Disclosed embodiments may include aggregation of data from the items of the low-level board that are linked to. Disclosed embodiments may include at least some of the imported extracted data is presented in each of the groups in the low-level board. Disclosed embodiments may include at least one associated high-level board is configured to hold sprint backlog data or metadata. Disclosed embodiments may include the at least one external column is a linkage column, the low-level board includes a plurality of linkage columns, and each of the plurality of linkage columns contains additional links to each of a plurality of associated high-level boards. Disclosed embodiments may include the low-level board includes a plurality of linkage external columns, and wherein each of the plurality of external columns contains additional links to each of a plurality of associated high-level boards. Disclosed embodiments include the external group-by is configured to: reorganize rows on the low-level board into a plurality of groups by common external column data; access on the low-level board, the additional links to the plurality of associated high-level boards; extract additional data from the plurality of associated high-level boards; and import the extracted additional data onto the low-level board. Disclosed embodiments may include the imported data influences one or more of a sorting or an arrangement of items in at least one group of the low-level board. Disclosed embodiments may, include the external group-by control and internal group-by control are configured for simultaneous performance to reorganize rows on the low-level board based on common internal column data and common external column data. Disclosed embodiments may include each row of a plurality of rows on the at least one associated high—level board is configured to hold data associated with a specific sprint. Disclosed embodiments may include data associated with the specific sprint is linked to the specific sprint via the at least one external column. Disclosed embodiments may include at least one associated high-level board is configured to hold sprint backlog data. Disclosed embodiments may include the imported data from the high-level is utilized in the low-level board.
Systems and methods disclosed herein involve unconventional improvements over conventional approaches. Descriptions of the disclosed embodiments are not exhaustive and are not limited to the precise forms or embodiments disclosed. Modifications and adaptations of the embodiments will be apparent from consideration of the specification and practice of the disclosed embodiments. Additionally, the disclosed embodiments are not limited to the examples discussed herein.
The foregoing description has been presented for purposes of illustration. It is not exhaustive and is not limited to the precise forms or embodiments disclosed. Modifications and adaptations of the embodiments will be apparent from consideration of the specification and practice of the disclosed embodiments. For example, the described implementations include hardware and software, but systems and methods consistent with the present disclosure may be implemented as hardware alone.
It is appreciated that the above described embodiments can be implemented by hardware, or software (program codes), or a combination of hardware and software. If implemented by software, it can be stored in the above-described computer-readable media. The software, when executed by the processor can perform the disclosed methods. The computing units and other functional units described in the present disclosure can be implemented by hardware, or software, or a combination of hardware and software. One of ordinary skill in the art will also understand that multiple ones of the above described modules/units can be combined as one module or unit, and each of the above described modules/units can be further divided into a plurality of sub-modules or sub-units.
The block diagrams in the figures illustrate the architecture, functionality-, and operation of possible implementations of systems, methods, and computer hardware or software products according to various exemplary disclosed embodiments. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing the specified logical functions. It should be understood that in some alternative implementations, functions indicated in a block may occur out of order noted in the figures. For example, two blocks shown in succession may be executed or implemented substantially concurrently, or two blocks may sometimes be executed in reverse order, depending upon the functionality involved. Some blocks may also be omitted. It should also be understood that each block of the block diagrams, and combination of the blocks, may be implemented by special purpose hardware-based systems that perform the specified functions or acts, or by combinations of special purpose hardware and computer instructions.
In the foregoing specification, embodiments have been described with reference to numerous specific details that can vary from implementation to implementation. Certain adaptations and modifications of the described embodiments can be made. Other embodiments can be apparent to those skilled in the art from consideration of the specification and practice of the disclosed embodiments. It is intended that the specification and examples be considered as example only, with a true scope and spirit of protection being indicated by the following claims. It is also intended that the sequence of steps shown in figures are only for illustrative purposes and are not intended to be limited to any particular sequence of steps. As such, those skilled in the art can appreciate that these steps can be performed in a different order while implementing the same method.
It will be appreciated that the embodiments of the present disclosure are not limited to the exact construction that has been described above and illustrated in the accompanying drawings, and that various modifications and changes may be made without departing from the scope thereof.
Other embodiments will be apparent to those skilled in the art from consideration of the specification and practice of the disclosed embodiments disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosed embodiments being indicated by the following claims.
Computer programs based on the written description and methods of this specification are within the skill of a software developer. The various programs or program modules can be created using a variety of programming techniques. One or more of such software sections or modules can be integrated into a computer system, non—transitory computer readable media, or existing software.
Moreover, while illustrative embodiments have been described herein, the scope includes any and all embodiments having equivalent elements, modifications, omissions, combinations (e.g., of aspects across various embodiments), adaptations or alterations based on the present disclosure. The elements in the claims are to be interpreted broadly based on the language employed in the claims and not limited to examples described in the present specification or during the prosecution of the application. These examples are to be construed as non-exclusive. Further, the steps of the disclosed methods can be modified in any manner, including by reordering steps or inserting or deleting steps. It is intended, therefore, that the specification and examples be considered as exemplary only, with a true scope and spirit being indicated by the following claims and their full scope of equivalents.
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| WO 2021144656 | Jul 2021 | WO |
| WO 2021161104 | Aug 2021 | WO |
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| Number | Date | Country | |
|---|---|---|---|
| 63148092 | Feb 2021 | US | |
| 63122439 | Dec 2020 | US | |
| 63121803 | Dec 2020 | US | |
| 63078301 | Sep 2020 | US | |
| 63019396 | May 2020 | US | |
| 63018593 | May 2020 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 17242452 | Apr 2021 | US |
| Child | 18048131 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 18048131 | Oct 2022 | US |
| Child | 18148881 | US |
