Patent Application
20210334676
The present disclosure generally relates to computer systems, and more particularly, to computer systems that are configured to test rules based on the types of changes to the rules.
The delivery of technology support systems is governed by complex rules that specify the types and scope of services to be delivered and rules for calculating a scope of the services delivered. The rules may be automated via implementations in a rule language, for efficiency.
Testing the large number of rules that may be associated with a large contract in an efficient manner can be a challenging and time-consuming task because of complex conditions and inter-rule dependencies. In additional, rules are often changed as they are developed. To address this problem, this disclosure describes a system that facilitates efficient rule testing for frequently evolving rules in a sandboxed environment.
A computer implemented method for testing rules by a computing device including selecting a current version of a rule and prior version of the rule, comparing the prior version of the rule and the current version of the rule to each other to identify a type of change made in the current version of the rule with respect to the prior version of the rule, and testing the prior version of a rule and the current version of the rule using a common data set, the testing being based on the identified type of change. The test result is provided to a user. The rule may include a guard part and a command part. The changes to the rules may include additions, deletions, and modifications of the guard part of the rule or a change to the action part of the rule, for example. When the change is an addition or deletion to the guard part of the rule, and the test results do not meet expected test results, that result is flagged for the user. A computing device and a non-transitory computer readable storage medium are also disclosed.
The techniques described herein may be implemented in a number of ways. Example implementations are provided below with reference to the following figures.
The drawings are of illustrative embodiments. They do not illustrate all embodiments. Other embodiments may be used in addition or instead. Details that may be apparent or unnecessary may be omitted to save space or for more effective illustration. Some embodiments may be practiced with additional components or steps and/or without all of the components or steps that are illustrated. When the same numeral appears in different drawings, it refers to the same or like components or steps.
In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant teachings. However, it should be apparent that the present teachings may be practiced without such details. In other instances, well-known methods, procedures, components, and/or circuitry have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present teachings.
Embodiments of the present disclosure generally relate to methods and systems for automatically testing evolving rules. The system automatically identifies which rules have been modified since their last execution and which dependent rules are potentially impacted by the modified rules. The system runs a set of tests on the modified rules and dependent rules that are potentially impacted by the modified rules to determine the impact of the changes to the rules. A rule may be guarded command, which is a programming statement that is guarded by a proposition. The statement can be executed only if the proposition is true. The guarded command has a guard clause, such as a WHEN clause/part, an IF clause/part, a conditions clause/part, or a propositions clause/part, for example, that lists one or more conditions, such as Boolean expressions and/or other suitable expressions that are to be satisfied in order to trigger the rule. The guarded command may also have a command clause/part, such as a THEN clause/part, an actions clause/part, a statements clause/part, for example, that lists one or more actions that are effectuated if the rule is triggered. Actions may include calculations, selections, assignments, insertions, deletions, data manipulations, and/or any other suitable action.
The system identifies changes made to guard part or command part of a modified rule, runs the old and new rule versions on the data used for testing the old rule version, and computes differences between the two outputs. The differences are presented to the user. Unexpected outputs may be flagged for the user. The architecture of and the processes performed by embodiments of the disclosure provide for faster and more reliable evaluation of large numbers of rules that an entity may be subject to. By virtue of the concepts discussed herein a technological improvement in the efficiency and computational accuracy of the computing device is provided in that fewer computing resources and a faster computation of an appropriately configured computing device, for example.
The THEN part (Lines 8-10) specifies the actions to be taken if the WHEN conditions are satisfied. For example, it may consist of an INSERT or UPDATE action on a datamodel table. The THEN part may include a set of assignments to fields of the table, for example. Line 5 in this example is an assignment to a temporary variable, which can be used in subsequent conditions. The THEN statement in Line 8, in this example, is to update a table or insert new records into a table, if the conditions are met. Lines 9-11 define the updates to the table fields. Other rules may have different number of lines defining different THEN functions, for example. Datasource Table: WH. SCHEMA.DISPATCH (holds service dispatch data). Datamodel Table: service_billing (holds generated billing items)
A rule R2 is dependent on a rule R1 if R1 writes to a field F and R2 reads that field. For example, rule 204 of
In accordance with embodiments of the disclosure, a subset of all the current rules is identified for testing in a sandbox. A sandbox is an isolated testing environment that is completely separate from any deployed systems using the rules. Thus, testing can be performed in the sandbox, using different datasets, with no impact on deployed systems. The subset of rules, which is referred to as “Affected Rules,” may contain modified rules and dependent rules, which are dependent on the modified rules. Modified rules are rules that have changed since their last successful execution in the sandbox. Dependent rules are rules that have definition-use dependencies on the modified rules. Differential testing can be done on modified rules along with their dependent rules.
Rules in the Affected Rules subset are then differentially tested by the system based on the type of change to a respective rule. Differential testing is the process running two versions of a rule on the same input data set and comparing the generated outputs. A current version of a modified rule (Rnew) is compared to an old or prior version of the modified rule (Rold) to identify whether the guard part, such as a WHEN part, or a command part, such as a THEN part, of the rule has been changed. A guard part may be changed in three ways-one or more guard conditions can be added to Rnew with respect to Rold, one or more guard conditions can be deleted from Rnew with respect to Rold, or one or more guard conditions can be modified in Rnew with respect to Rold. If the command part of the rule is changed, then rules dependent on the rule are tested. Different tests are applied to the rules dependent on the change. Users of the rules are provided with the test results for their own analysis. In the test results provided to the user, the differences between the two output sets can be highlighted, using various user-interface designs, to assist the user in checking the differences for correctness.
Example Block Diagram of System
The system 300 includes a rules database 302, which includes rules applicable to the user 1 and user 2. A test data database 304 may store data to be used in testing of the rules, as discussed below.
A sandbox server 306 includes a sandbox engine 308 that may retrieve rules from the rules database 302, identify rules that have been changed and how, store the changed (Affected) rules, retrieve test data from the test data database 304, differentially test the changed rules with the test data based on how they were changed, and inform the respective users of the results. In another example, the Affected Rules may be stored in another database external to the sandbox server 306. The rules stored in the rules database 302 and/or the test data stored in the test data database 304 may be stored in another location. It is noted that rules more commonly tested and/or test data more commonly used may be stored in the sandbox engine 308 in addition to or instead of being stored in the rules database 302 and/or the test data database 304.
A network 310 allows the sandbox server 306 to communicate with various resources connected to the network 310, such as the rules database 302 and the test database 304, and to retrieve the needed data from each. The network 310 also allows the sandbox engine 308 to communicate with user 1 and user 2.
While the rules database 302 is shown separate from the test data database 304, the two databases could be combined. In addition, the rules database 302, the test data database 304, and the sandbox server 306 may be implemented by virtual computing devices in the form of virtual machines or software containers that are hosted in the cloud 312, thereby providing an elastic architecture for processing and storage. The cloud 312 is discussed in more detail below.
If it has been determined that the rule has not been previously executed (No in block 404), the rule R is added to a set of New Rules, in block 409, and the process returns to block 402 to continue to evaluate another rule R. Whether or not a previous execution of a respective rule was successful may be determined based on the records of execution stored by the sandbox engine 308, for example.
If the rule R has been executed (Yes in block 404), it is determined by the sandbox engine 308 whether the last execution the rule R (Rexe) was successful, in block 408. If the last execution of the rule R by the sandbox engine 308 was not successful (No at block 404), R is treated as a new rule and added to the New Rules set, in block 409. In this embodiment of the disclosure, New Rules are identified for the user but are not further evaluated.
If the sandbox engine 308 determines that the execution of the rule R (Rexe) was successful (Yes in block 408), the WHEN and THEN parts of the current version of the rule R and the previously executed version of the rule Rexe are compared, in block 410. Comparison may be performed by the sandbox engine 308 by a textual comparison of the WHEN and THEN parts, or by constructing expression (parse) trees of the WHEN and THEN parts and comparing the two trees, for example. However, if the sandbox engine 308 determines that the execution of the rule R was not successful (No at block 408), the process continues with block 409, as discussed above.
The sandbox engine 308 determines whether there are differences between the current version of the rule R and the executed version of the rule Rexe, in block 412, based on the comparison in block 410. If it is determined that there are differences (Yes in block 410), the current version of the rule R is added to the set of Affected Rules, in block 406. The process 400 then returns to block 402 to analyze the next rule R. If it is determined that there are no differences between the current version of the rule R and the previously executed version of the rule Rexe, then the current version of the rule R is added to a set of Unaffected Rules in block 414, and the flowchart 400 returns to block 402 to analyze the next rule R. The user may be informed of the rules in the set of Unaffected Rules.
As discussed above, rules dependent on Affected Rules may also be analyzed for changes. The flowchart 400 can include the optional block to iteratively determine, for each Affected Rule, whether there is an affected dependent rule, in block 416, as indicated by the broken arrow. As discussed above, a rule R2 is dependent on a rule R1 if R1 writes to a field F and R2 reads that field. Rules meeting that condition may be identified by the sandbox engine 308. The sandbox engine 308 may associate rules with dependent rules for later use. If it is determined that a respective Affected Rule has one or more dependent rules (Yes in block 416), the dependent rule Rdep is added to the Affected Rules, in block 406. If it is determined that a respective Affected Rule does not have a dependent rule Rdep (No in block 416), the process 400 returns to block 402 to analyze the next rule R.
As discussed above, in this example, the rules in the Affected Rules subset are differentially tested by the system based on the type of change to a respective rule.
A prior version of the rule Rold corresponding to Rnew is retrieved, in block 504. The prior version of the rule Rold may be retrieved from the rules database 302, a database in the sandbox server 306, or a database in the sandbox engine 308, for example, by the sandbox engine 308. The WHEN and THEN parts of Rnew and the corresponding Rold are compared, in block 506. The comparison may be performed by the sandbox engine 308 by textual comparison or by constructing expression (parse) trees of the WHEN part and the THEN part and comparing the two trees as above, for example.
The sandbox engine 308 determines whether the WHEN part of Rnew is changed with respect to WHEN part of Rold, in block 508. If the sandbox engine 308 determines that the WREN part is changed (Yes in block 508), the sandbox engine determines whether a condition is added to the WHEN part, in block 510.
If the sandbox engine 308 determines that a condition is added, in block 510, then the rule Rnew is tested in accordance with the test of
If it is determined by the sandbox engine 308 that a condition is not deleted (No in block 512), the process 500 continues to determine whether a condition is modified, in block 514. If the sandbox engine 308 determines that a condition is modified, in block 514, then the rule Rnew is tested in accordance with the test of
Returning to block 508, if the sandbox engine 308 determines that the WHEN part is not changed (No in block 508), the sandbox engine determines whether the THEN part is changed, in block 516. If the sandbox engine 308 determines that the THEN part is changed, the new rule Rnew is tested in accordance with
Since a new condition was added to the prior rule Rold to obtain the new rule Rnew, it is expected that there will be fewer successful instances or records of Rnew(D) than Rold(D) (Rnew(D)≤Rold(D)). This is because, for each input record on which the WHEN conditions are met, one or more output records are produced (as new records or updated records). For an input record on which some WHEN condition is not met, no output record is created. The data set includes data that will meet both scenarios, so that the conditions are met on some records and not on others. A “successful instance” is a test of the rule where the conditions are met. Because Rnew has new conditions added, there will typically be fewer successful instances in Rnew than in Rold.
The result of the comparison is sent to the user by the sandbox engine 308. If the result of the comparison for a respective new rule Rnew is not the expected result, the sandbox engine 308 can flag the result for the user.
Since a condition was deleted from the prior rule Rold to obtain the new rule Rnew, it is expected that there will be more successful instances of Rnew(D) than Rold(D) (Rnew(D)≥Rold(D)). The result of the comparison is sent to the user. If the result of the comparison for a respective new rule Rnew is not the expected result, this can be flagged for the user by the sandbox engine 308.
Since a condition was modified from the prior rule Rold to obtain the new rule Rnew, it is not known how whether there will be more, less, or an equal number of instances of Rnew(D) than Rold(D) ((Rnew(D) ?=Rold(D)). The result of the comparison is sent to the user to inform the user whether a respective new version of a rule Rnew results in greater, fewer, or the same number of successful instances than the prior version of the rule, by the sandbox engine 308.
In each of the examples of
If it is determined that the THEN part of the rule is changed in block 516 of
Test data is retrieved, in block 702. The test data may be retrieved by the sandbox engine 308 from the test data database 304, for example. The prior rule Rold is run with the test data, in block 704 and the result is run with the dependent rule Rdep, in block 706. The output of Output Rdep(Rold(D)) is provided in block 708. The sandbox engine 308 can run the test to generate the output in block 708.
Similarly, the new rule Rnew is run with the test data, in block 710 and the result is run with the dependent rule Rdep, in block 712. The output Rdep(Rnew(D)) is provided in block 714. The sandbox engine 308 can run the test to generate the output in block 714. It is noted that the same dependent rule Rdep may be used with both Rold and Rnew, or, due to the change in the THEN part of Rnew, a different dependent rule may be used when conducting this test on Rnew.
The output Rdep(Rnew(D)) and the output Rdep(Rold(D)) are compared, in block 716, by the sandbox engine 308. It is not known how whether there will be more, less, or an equal number of instances of Rdep(Rnew(D)) or Rdep(Rold(D)) ((Rdep(Rnew(D))?=Rdep(Rold(D)). The result of the comparison is sent to the user to inform the user whether a respective new version of the rule results in greater, fewer, or the same number of successful instances than the prior version of the rule, by the sandbox engine 308. As above, if Rdep(Rnew(D)) is empty, or provides no results, Rnew and Rold may be run with new data provided by the user or generated by the sandbox engine 308, as discussed below, for example.
The test results may be in the form of a set of records stored in a database that the user has access to, for example. The database may be in the sandbox server 306 or it may be a separate database in the system 300 of
Example Computer Platform
Functions relating to the testing of evolving rules in accordance with embodiments of the disclosure can be performed with the use of one or more computing devices connected for data communication via wireless or wired communication, for example.
The computer platform 800 may include a processing device, such as a central processing unit (CPU) 802, a hard disk drive (“HDD”) 804, random access memory (“RAM”) and read only memory (“ROM”) 806, a keyboard 808, a mouse 810, a display 812, and a communication interface 814, which are connected to a system bus 816, for example.
A sandbox engine program 818 that corresponds to the sandbox engine 308 of
The sandbox engine program 818 may have various modules configured to perform different functions, as shown in
A rules database 910, such as the rules database 302 of
A rule execution history database 918 in this example stores records of previously executed rules, which are used in the process 400 of
A sandbox user interface 920 receives instructions from a user and presents the test results to the user in the form of a web browser, for example. A data exporter 922 may also provide the test results to a user in the form of a file, such as a CSV 924, for example.
The data generator 926 automatically generates synthetic test data relevant for testing a given rule or rules, if needed. In one example, the data generator 926 is configured to generate one or more datasets for testing particular rules by generating a query language query based on a first rule. The query language query is executed on a data table to return one or more datasets for testing the first rule. The query language query can be generated by initializing conditions of a WHERE part of the query language query based on the first rule and transforming the conditions of the WHERE part of the query language query based on a sequence of rules on which the first rule depends, for example. The transformed conditions of the WHERE part of the query language query are converted into query language syntax. Conditions from a guard part of the first rule are inserted into the WHERE part of the query language query. If any variable of any condition in the WHERE part of the query language query is assigned in a guard part of a second rule in the sequence of guarded commands, the variable in the WHERE part of the query language query is replaced with a corresponding assignment specified in the guard part of the second rule. Conditions from a guard part of the second rule are inserted into the WHERE part of the query language query conditions. Duplicate or tautological conditions are removed from the WHERE part of the query language query. Backward traversals on a rule dependence graph are performed to identify a subgraph of rules on which the first rule depends. A topological sort is performed on the subgraph to generate the sequence of rules. One or more datasets are generated that cause all conditions of the WHERE part of the query language query to evaluate true, and one or more datasets are generated that cause the given condition to evaluate false and causes conditions preceding the given condition to evaluate true.
The data selector 928 selects the test data to be used as input for executing a rule. The sandbox database 930 stores test data used as input for rule execution and output created from rule executions and selectively provides the test data to the rule executor 912 for use in testing respective rules, as discussed above. The test data may be provided by the user and/or generated by the data generator 926. The sandbox database 930 also provides test data to the differential tester 914. As discussed above, rules more commonly tested and/or test data more commonly used may be stored in the sandbox engine 308, such as in the sandbox database 930, in addition to or instead of being stored in the rules database 302 and/or the test data database 306.
A program, such as Apache™, can be stored for operating the system as a Web server. In one embodiment, the HDD 804 can store an executing application that includes one or more library software modules, such as those for the Java™ Runtime Environment program for realizing a JVM (Java™ virtual machine).
Example Cloud Platform
As discussed above, functions relating to evaluating evolving rules may include a cloud 312, as shown in
Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
Characteristics are as follows:
On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service's provider.
Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).
Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.
Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.
Service Models are as follows:
Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.
Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations.
Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).
Deployment Models are as follows:
Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.
Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.
Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.
Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).
A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure that includes a network of interconnected nodes.
Referring now to
Referring now to
Hardware and software layer 1160 include hardware and software components. Examples of hardware components include: mainframes 1161; RISC (Reduced Instruction Set Computer) architecture based servers 1162; servers 1163; blade servers 1164; storage devices 1165; and networks and networking components 1166. In some embodiments, software components include network application server software 1167 and database software 1168.
Virtualization layer 1170 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers 1171; virtual storage 1172; virtual networks 1173, including virtual private networks; virtual applications and operating systems 1174; and virtual clients 1175.
In one example, management layer 1180 may provide the functions described below. Resource provisioning 1181 provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing 1182 provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal 1183 provides access to the cloud computing environment for consumers and system administrators. Service level management 1184 provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment 1185 provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.
Workloads layer 1190 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation 1191; software development and lifecycle management 1192; virtual classroom education delivery 1193; data analytics processing 1194; transaction processing 1195; and interaction engine 1196, such as the sandbox engine 308 of
The descriptions of the various embodiments of the present teachings have been presented for purposes of illustration but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
While the foregoing has described what are considered to be the best state and/or other examples, it is understood that various modifications may be made therein and that the subject matter disclosed herein may be implemented in various forms and examples, and that the teachings may be applied in numerous applications, only some of which have been described herein. It is intended by the following claims to claim any and all applications, modifications and variations that fall within the true scope of the present teachings.
The components, blocks, features, objects, benefits, and advantages that have been discussed herein are merely illustrative. None of them, nor the discussions relating to them, are intended to limit the scope of protection. While various advantages have been discussed herein, it will be understood that not all embodiments necessarily include all advantages. Unless otherwise stated, all measurements, values, ratings, positions, magnitudes, sizes, and other specifications that are set forth in this specification, including in the claims that follow, are approximate, not exact. They are intended to have a reasonable range that is consistent with the functions to which they relate and with what is customary in the art to which they pertain.
Numerous other embodiments are also contemplated. These include embodiments that have fewer, additional, and/or different components, blocks, features, objects, benefits, and advantages. These also include embodiments in which the components and/or blocks are arranged and/or ordered differently.
Aspects of the present disclosure are described herein with reference to call flow illustrations and/or block diagrams of a method, apparatus (systems), and computer program products according to embodiments of the present disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the call flow illustrations and/or block diagrams, can be implemented in hardware, software, or a combination thereof. In the context of software, the blocks represent computer readable and executable program instructions that, when executed by one or more processors, perform the recited operations. Generally, computer executable instructions may include routines, programs, objects, components, data structures, and the like that perform functions or implement abstract data types.
These computer readable and executable program instructions may be provided to a processor of a computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the call flow process and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the call flow and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational blocks to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the call flow process and/or block diagram block or blocks.
The computer readable program instructions may be stored in a non-transitory computer readable storage medium, which may be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, a magnetic storage device an optical storage device, an electromagnetic storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of a computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc rad-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structure in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein is not to be construed as being transitory signals per se. such as radio waves or freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the call flow process or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Blocks of the flowcharts can be implemented by hardware, software, or a combination thereof. It will also be noted that each block of the block diagrams and/or call flow illustration, and combinations of blocks in the block diagrams and/or call flow illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
While the foregoing has been described in conjunction with exemplary embodiments, it is understood that the term “exemplary” is merely meant as an example, rather than the best or optimal. Except as stated immediately above, nothing that has been stated or illustrated is intended or should be interpreted to cause a dedication of any component, block, feature, object, benefit, advantage, or equivalent to the public, regardless of whether it is or is not recited in the claims.
It will be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein. Relational terms such as first and second and the like may be used solely to distinguish one entity or action from another without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by “a” or “an” does not, without further constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.
The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments have more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.
