Page data verification method, device and equipment, storage medium and program product

Abstract

The application discloses a page data verification method and device, equipment, a storage medium and a program product, and the method comprises the following steps: capturing user actions on an interactive page of a current cloud computing resource order; in the case that the user actions are captured, collecting data on the corresponding interactive page according to at least one data collection item required by the current cloud computing resource order, to obtain parameter values corresponding to each data collection item under the corresponding interactive page; wherein the data collection item is determined according to a resource consumption calculation model matched to the current cloud computing resource order; in the case that the current cloud computing resource order is switched to an ending page, verifying the parameter values of all collected interactive pages to obtain a page data verification result of the current cloud computing resource order; the embodiment of the application considers the influence of user actions on page data in the execution process of the cloud computing resource order, and can effectively improve the accuracy of cross-page data flow verification.

Description

Technical Field

[0001] This invention relates to the field of data processing technology in cloud computing, and in particular to a page data verification method, apparatus, device, storage medium, and program product. Background Technology

[0002] In business scenarios such as ordering, cancellation, expansion, renewal, and changes in order billing methods, cloud computing resources require user operations to select data across multiple pages to reach the target page. Each page needs to match the incoming data with corresponding business rules to generate the appropriate page data, which serves as the basis for subsequent user operations. Different scenarios have different business rules, and these scenarios involve multi-page, step-by-step operations and cross-page data transfer to the target page. Therefore, ensuring the accuracy of data transfer between pages in various order scenarios is crucial for supporting the normal execution of business processes.

[0003] Existing methods for verifying the accuracy of data between pages primarily rely on setting multiple thresholds or deviation ranges from historical data to determine whether the page data falls within the threshold range or whether the deviation from historical data is within a reasonable range, thus verifying whether the page data is transmitted correctly. However, existing verification methods do not consider user actions during the page data verification process, making it impossible to determine whether the current page data matches the business scenario selected by the user, which affects the accuracy of page data verification. Summary of the Invention

[0004] To address the problems existing in the prior art, embodiments of the present invention provide a page data verification method, apparatus, device, storage medium, and program product. By capturing user actions during the execution of cloud computing resource orders and considering the impact of user actions on page data, the accuracy of page data verification can be effectively improved.

[0005] In a first aspect, embodiments of the present invention provide a page data verification method, including: Capture user actions on the interactive page of the current cloud computing resource order; Upon capturing user actions, data is collected from the corresponding interactive page based on at least one data collection item required for the current cloud computing resource order, to obtain parameter values ​​corresponding to each of the data collection items on the corresponding interactive page; wherein, the data collection item is determined based on the resource cost calculation model matched to the current cloud computing resource order; Upon redirection to the end page of the current cloud computing resource order, all collected parameter values ​​from the interactive pages are verified to obtain the page data verification results for the current cloud computing resource order.

[0006] As an improvement to the above solution, the method further includes: Feature analysis is performed on various types of cloud computing resource orders to determine the characteristic data of each type of cloud computing resource order; wherein, the characteristic data includes the product name of the cloud computing resource, the order scenario, the billing type, and the resource cost calculation model; A multi-level indexed feature database is constructed based on the characteristic data of various types of cloud computing resource orders; wherein, the feature database is indexed by product name, order scenario, and billing type, and the resource cost calculation model is the index target.

[0007] As an improvement to the above scheme, the process of determining the data collection items includes: Based on the product name, order scenario, and billing type of the current cloud computing resource order, the feature database is searched to determine the feature data that matches the product name, order scenario, and billing type of the current cloud computing resource order. Based on the parameter items corresponding to the resource overhead calculation model in the matched feature data, determine the data collection items required for the current cloud computing resource order.

[0008] As an improvement to the above solution, the method further includes: Collect the page address of the currently interacting page and check if the page address exists in the address list; When the page address does not exist in the address list, the page address is added to the address list, and the page address and the parameter values ​​of the corresponding interactive page are saved to the address parameter association set according to a preset string format. When the address list contains the page address, the parameter value corresponding to the page address in the address parameter association set is updated according to the parameter value of the corresponding interactive page.

[0009] As an improvement to the above solution, based on at least one data collection item required by the current cloud computing resource order, data is collected from the corresponding interactive page to obtain the parameter values ​​corresponding to each data collection item on the corresponding interactive page, including: Extract resource data descriptions from the data collection items and determine the smallest container tag for the page containing the resource data descriptions; Obtain the data value of the form input control under the smallest container label of the interactive page, and use it as the parameter value corresponding to the data collection item.

[0010] As an improvement to the above solution, the method further includes: Based on the matched resource overhead calculation model and the parameter values ​​corresponding to each of the data collection items, calculate the resource overhead settlement result for the current cloud computing resource order; The resource cost settlement result is compared and verified with the payment result displayed on the end page to obtain the data consistency verification result.

[0011] Secondly, embodiments of the present invention provide a page data verification device, comprising: The motion capture module is used to capture user actions on the interactive page of the current cloud computing resource order. The parameter acquisition module is used to acquire data from the corresponding interactive page based on at least one data acquisition item required by the current cloud computing resource order when user actions are captured, and to obtain the parameter values ​​corresponding to each data acquisition item on the corresponding interactive page; wherein, the data acquisition item is determined based on the resource cost calculation model matched to the current cloud computing resource order; The data verification module is used to verify the parameter values ​​of all collected interactive pages when redirected to the end page of the current cloud computing resource order, and obtain the page data verification result of the current cloud computing resource order.

[0012] Thirdly, embodiments of the present invention provide a page data verification device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the page data verification method as described in any one of the first aspects.

[0013] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the page data verification method as described in any one of the first aspects.

[0014] Fifthly, embodiments of the present invention provide a computer program product, including a computer program or instructions, which, when executed by a processor, implement the page data verification method as described in any one of the first aspects.

[0015] Compared to existing technologies, the present invention provides a page data verification method, apparatus, device, storage medium, and program product. This method captures user actions on interactive pages during the execution of cloud computing resource orders, using these actions as triggers for page data collection. Upon capturing user actions, data is collected from the corresponding interactive page based on at least one data collection item required by the cloud computing resource order, yielding parameter values ​​for each data collection item on the corresponding interactive page. These data collection items are determined based on a resource cost calculation model matched to the cloud computing resource order. When the user navigates to the end page of the current cloud computing resource order, all collected parameter values ​​from the interactive pages are verified. This achieves verification of cross-page data flow during the execution of cloud computing resource orders. The present invention fully considers the impact of user actions on page data during the execution of cloud computing resource orders, effectively improving the accuracy of cross-page data flow verification. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a page data verification method provided in an embodiment of the present invention; Figure 2 This is a structural block diagram of a page data verification device provided in an embodiment of the present invention; Figure 3 This is a structural block diagram of a page data verification device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It is understood that the various numerical designations used in the embodiments of this invention are merely for descriptive convenience and are not intended to limit the scope of this application. The order of the process numbers does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

[0020] In embodiments of the invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element. The term "a plurality or several" refers to two or more.

[0021] See Figure 1 , Figure 1 This is a flowchart of a page data verification method provided in an embodiment of the present invention. The page data verification method specifically includes: S11: Capture user actions on the interactive page of the current cloud computing resource order; S12: Upon capturing user actions, data is collected from the corresponding interactive page based on at least one data collection item required by the current cloud computing resource order, and parameter values ​​corresponding to each data collection item on the corresponding interactive page are obtained; wherein, the data collection item is determined based on the resource cost calculation model matched to the current cloud computing resource order; S13: When redirected to the end page of the current cloud computing resource order, verify the parameter values ​​of all collected interactive pages to obtain the page data verification results of the current cloud computing resource order.

[0022] It should be noted that the page data verification method described in this embodiment of the invention can be executed by terminal devices such as servers, computers, and mobile phones. Since the operation of a cloud computing platform relies on the actual usage scenarios of cloud resources, including resource ordering, cancellation, resource expansion, resource renewal, and conversion of resource billing methods (i.e., order scenarios), the cloud computing platform manages the use of cloud resources, from order configuration, usage adjustment, period renewal, cancellation termination, and metering method changes, by generating cloud computing resource orders (i.e., the order process). The execution of cloud computing resource orders involves multi-page data flow. To ensure the accuracy of page data during cross-page data flow, page data verification is required during the execution of cloud computing resource orders. The specific process is as follows: Monitor user actions on interactive pages during the execution of cloud resource orders initiated by users, such as input actions, click actions, and selection actions on interactive pages; user actions indicate that users may modify order scenarios or data values ​​on interactive pages.

[0023] Using user actions as the trigger condition for page data collection, when user actions are captured, at least one data collection item matched by the resource overhead calculation model matched by the cloud computing resource order is used to collect data from the interactive page and obtain the parameter values ​​corresponding to each data collection item on the interactive page. Upon redirecting to the end page of the current cloud computing resource order, all collected parameter values ​​from interactive pages are verified. For example, it is determined whether the parameter values ​​corresponding to the same data collection item under different interactive pages are consistent or whether only one interactive page's parameter value is collected. If so, a page data verification result indicating no problem with page data transmission is obtained, and the subsequent settlement process for the cloud computing resource order can proceed. Otherwise, a page data verification result indicating a problem with page data transmission is obtained, a page data transmission anomaly alarm is issued, and the execution process of the cloud computing resource order is terminated.

[0024] This invention monitors user actions on interactive pages during the execution of cloud resource orders initiated by users, fully considering the impact of user actions on page data during the execution of cloud resource orders. This ensures that the current page data matches the business scenario selected by the user, realizes the verification of cross-page data flow during the execution of cloud resource orders, and improves the accuracy of cross-page data flow verification.

[0025] Furthermore, the method also includes: Feature analysis is performed on various types of cloud computing resource orders to determine the characteristic data of each type of cloud computing resource order; wherein, the characteristic data includes the product name of the cloud computing resource, the order scenario, the billing type, and the resource cost calculation model; A multi-level indexed feature database is constructed based on the characteristic data of various types of cloud computing resource orders; wherein, the feature database is indexed by product name, order scenario, and billing type, and the resource cost calculation model is the index target.

[0026] In this embodiment of the invention, considering that the resource cost calculation methods for different cloud computing resource products and different order types may vary, a feature database with multi-level indexes is established by analyzing the feature data that uniquely determines the resource cost calculation model. This database is used for subsequent confirmation of data collection items for cloud computing resource orders, ensuring the efficiency and accuracy of data collection. The specific process is as follows: By analyzing different types of cloud computing resource orders, it is possible to determine that each product within a cloud computing resource can be uniquely identified by its product name, order scenario (also known as order type), and billing type. The product name, order scenario, billing type, and resource cost calculation model for different types of cloud computing resource orders can be extracted as feature data for the corresponding cloud computing resource orders. This feature data is then stored in a feature database according to a preset data format. For example, the feature data stored in the feature database is represented as follows: ({Product Name 1, {Order Scenario 1, {<Billing Type 1, Resource Cost Calculation Model 1>, ..., <Billing Type n, Resource Cost Calculation Model n>}}, ..., {Order Scenario n, {<Billing Type 1, Resource Cost Calculation Model 1>, ..., <Billing Type n, Resource Cost Calculation Model n>}}}, ..., {Product Name n, {Order Scenario 1, {<Billing Type 1, Resource Cost Calculation Model 1>, ..., <Billing Type n, Resource Cost Calculation Model n>}}, ..., {Order Scenario n, {<Billing Type 1, Resource Cost Calculation Model 1>, ..., <Billing Type n, Resource Cost Calculation Model n>}}}).

[0027] By using multi-level indexes based on product name, order scenario, and billing type, a unique resource cost calculation model can be found in the feature database. This model can be used to calculate the total resource volume and / or the cost accounting value for the total resource volume associated with a user-initiated cloud computing resource order, including but not limited to subscriptions, cancellations, expansions, and renewals.

[0028] The feature database constructed above can be placed in the browser's background program, and the resource cost calculation model can be confirmed in the cloud computing resource order completed in the background program.

[0029] This invention constructs a feature database with three-level indexes for product name, order scenario, and billing type, and integrates a corresponding resource cost calculation model. The multi-level index enables precise matching of unique calculation models. Furthermore, the feature database is deployed in the browser's background program, where model confirmation is completed in the background. This adapts to diverse calculation needs across multiple products, order scenarios, and billing types. The background processing improves the efficiency of resource cost calculation model matching and invocation, ensuring the accuracy and convenience of page data verification during cloud computing resource order execution.

[0030] In one optional embodiment, the process of determining the data collection items includes: Based on the product name, order scenario, and billing type of the current cloud computing resource order, the feature database is searched to determine the feature data that matches the product name, order scenario, and billing type of the current cloud computing resource order. Based on the parameter items corresponding to the resource overhead calculation model in the matched feature data, determine the data collection items required for the current cloud computing resource order.

[0031] Specifically, based on at least one data collection item required for the current cloud computing resource order, data is collected from the corresponding interactive page to obtain the parameter values ​​corresponding to each data collection item on the corresponding interactive page, including: Extract resource data descriptions from the data collection items and determine the smallest container tag for the page containing the resource data descriptions; Obtain the data value of the form input control under the smallest container label of the interactive page, and use it as the parameter value corresponding to the data collection item.

[0032] In a complete order process for cloud computing resources, since the product and order scenario do not change with the user's actions, the billing type is provided for the user to choose from, and the data changes with the user's choices. Therefore, for the feature data used to confirm the resource cost calculation model, the product and order scenario are manually entered before the browser extension is launched. That is, it is implemented by adding a drop-down list control (i.e., form input control) in the pop-up window, such as a product drop-down list and an order scenario drop-down list. The list items contain the cloud computing resources and order scenarios supported by the extension, and the billing type is obtained by the extension collecting page data.

[0033] Considering that the resource cost calculation models for different order scenarios of the same product are different, the parameters involved in the resource cost calculation models will also differ. To facilitate data collection, we take the union of all the parameters required by the resource cost calculation models for the same product, and use the page data corresponding to these parameters as the data collection items for the parameters.

[0034] For the above parameters, if they are obtained directly from the page data, the specific data value of the parameter is obtained directly by using an extension program to collect the page data. For example, in cloud computing, there is a type of formula parameter that is the expiration time of the resource. If the page contains a data item that includes the expiration time, the expiration time of the cloud computing resource order can be obtained directly from the page data.

[0035] For the above parameters, secondary calculations are required based on collected page data. First, confirm the required data value, then confirm the calculation method for obtaining the data value. After the background program of the extension obtains the collected page data, it completes the corresponding calculations to achieve the final data value of the parameter. For example, in cloud computing, there is a type of formula parameter that is the number of days the resource has been used or the number of days the resource remains to be used. However, the page only shows the order time and the expiration time. Secondary calculations of the number of days the resource has been used or the number of days the resource remains to be used are required based on this collected data (such as the order time and the expiration time).

[0036] Since the parameter items are derived from page-collected data, each data collection item corresponds to two modules on the page: <Data Description> and <Data Value Selection>. According to UI design specifications, the data description (i.e., the parameter collection description) for the same parameter under the same product should be consistent across different pages. For example, the data description for the ordered resource size should be expressed as "ordered capacity," and the data description for the ordered quantity should be expressed as "ordered quantity." Browser extensions can locate the smallest capacity tag (i.e., the smallest div tag) containing the data description content through the page's data description, and then collect the input values ​​of the text boxes and dropdown boxes under that tag, or the values ​​represented by the selected buttons, to achieve the purpose of collecting the data values ​​of the corresponding parameter items.

[0037] Considering that the calculation formulas for different order scenarios for the same product vary, and the required sets of parameters also differ, to facilitate data collection, the union of all parameter items involved in the resource cost calculation model for the same product is taken. All page data collection items related to these parameter items are then used as the data collection items for that product, such as dataSet={collection parameter description 1, collection parameter description 2, ..., collection parameter description n}. Since the confirmation of the resource cost calculation model requires a billing type, the dataSet must also contain data of that type. The descriptions of the same parameter on different products may differ on the page; therefore, a data collection dataset model is established and stored by product category, i.e., {<product name_1, dataSet_1>, <product name_2, dataSet_2>, ..., <product name_n, dataSet_n>}. The data collection item for a product is found through its product name.

[0038] This invention achieves accurate and targeted collection of cloud computing resource order data by matching the product name, order scenario, and billing type of cloud computing resource orders with a feature database, thereby accurately determining the data collection items suitable for the resource cost calculation model. Based on the resource data description, it locates the smallest container label on the page and collects the parameter values ​​of the form input controls therein. This ensures that the collected data matches the actual needs of resource cost calculation.

[0039] Furthermore, the method also includes: Collect the page address of the currently interacting page and check if the page address exists in the address list; When the page address does not exist in the address list, the page address is added to the address list, and the page address and the parameter values ​​of the corresponding interactive page are saved to the address parameter association set according to a preset string format. When the address list contains the page address, the parameter value corresponding to the page address in the address parameter association set is updated according to the parameter value of the corresponding interactive page.

[0040] In this embodiment of the invention, in addition to the aforementioned product dropdown list and order scenario dropdown list, to improve the user-friendliness and manageability of the process, start and end points for data collection, as well as an entry point for displaying verification results, can be added to the Popup pop-up window. After entering the first page of the cloud computing resource order operation, the Popup pop-up window opens. After selecting the product being verified from the product dropdown list and the correct order scenario from the order scenario dropdown list, clicking the "Start Data Collection" button will begin collecting page data. Simultaneously, the product and order scenario data will be transmitted to the backend via a single message passing method within the plugin for subsequent confirmation of the resource cost calculation model.

[0041] To ensure that the data selected by the user is correctly transmitted, thereby improving the accuracy of the parameter values ​​used in the resource overhead calculation model and thus guaranteeing the accuracy of the verification results, it is necessary to determine which data needs to be collected by identifying the factors that affect the resource overhead calculation model. These factors are more specifically the parameter items of the resource overhead calculation model, as described above.

[0042] Understandably, both enabling an extension and detecting a click event on a page are defined as user actions and will trigger data collection. First, the page address of the current page (i.e., the interactive page) is collected, such as the URL (Uniform Resource Identifier), and then the page address is checked in the address list urlList to see if that page address exists.

[0043] If it doesn't exist, save the address in the address list urlList in the list order. urlList = [url_1, url_2,..., url_n]. Then, based on the product name indicated by the current cloud computing resource order and the established data collection set model, find the corresponding data collection item dataSet. The extended program content script uses the DOM API of JavaScript to obtain the "collection parameter description" of each data item from the data collection item and then sends it to the built-in API of the browser to find the position of this parameter on the current page. Then, find the smallest div tag containing this parameter description, and use JavaScript and the built-in API of the browser to obtain the input values of the text box and dropdown box under this tag, or the value of the selected button. Finally, save the collected values in the string format of ({collection parameter description 1, <urlList[1], collection parameter value_1>,..., <urlList[n], collection parameter value_n>}, {collection parameter description 2, <urlList[1], collection parameter value_1>,..., <urlList[n], collection parameter value_n>},..., {collection parameter description n, <urlList[1], collection parameter value_1>,..., <urlList[n], collection parameter value_n>}) to obtain the address parameter association set. {collection parameter description 1, <urlList[n], collection parameter value 1>} means that the first collected parameter value (i.e., the data value) of the collection parameter description 1 is collected in the page address corresponding to urlList[n] (the nth page address in the address list) and is saved in string type; If the address exists in the address list, it means that the user has performed the operation of going back to the previous page or refreshed the page. At this time, after collecting the page data, update the parameter values on this page according to urlList[n].

[0044] After entering the end page, such as the page showing the payment price, click the stop collection button in the Popup window. The data collection set sends a message internally through the extension program to the event handler for verifying the correct transfer of data between pages. The specific verification process is as follows: For each collection parameter in the data collection set, it is saved in the format of {collection parameter description 1, <urlList[1], collection parameter value_1>,..., <urlList[n], collection parameter value_n>}, that is, the parameter values of the collection parameter description 1 collected on multiple pages. To verify the correct transfer of parameter values between pages, compare the collection parameter values_1 to parameter values_n collected on each page. If one parameter value is inconsistent, it means that there is a problem with data transfer, an exception is thrown, and the program ends; if all parameter values are equal or the parameter value is only collected on one page, it is judged that there is no problem with data transfer.

[0045] In the embodiment of the present invention, consistency verification is carried out on the parameter values corresponding to the same parameter description collected from multiple pages. Only when the parameter values corresponding to the corresponding parameters of multiple pages are exactly the same, or the parameter value is collected only on a single page, it is determined that there is no problem with page data transfer. If any parameter value is inconsistent, an exception is immediately thrown and the program is terminated, so that data transfer anomalies can be accurately identified, the accuracy of the collected data can be guaranteed from the source, and at the same time, the abnormal process can be blocked in time to reduce the ineffective processing cost.

[0046] Further, the method further includes: Calculating a resource cost settlement result of the current cloud computing resource order according to the matched resource cost calculation model and the parameter values corresponding to each of the data collection items; Comparing and verifying the resource cost settlement result with the payment result displayed on the end page to obtain a data consistency verification result.

[0047] In the embodiment of the present invention, after the page data verification passes, that is, when there is no problem with page data transfer, the corresponding resource cost calculation model can be further matched according to the characteristic data of the cloud computing resources, and the parameter values of the parameter items of the resource cost calculation model collected above are input into the resource cost calculation model to perform the resource cost settlement of the cloud computing resource order, and the corresponding resource cost settlement result is obtained, such as the required payment price.

[0048] It can be understood that each parameter value in the resource cost calculation model needs to be obtained through a function. There are 2 types of functions. One type is "formula parameter value 1 = fix_stringToInt(collection parameter description 1)", that is, by taking the first collection parameter value_1 in the collected data {collection parameter description 1, <urlList[1], collection parameter value_1>,..., <urlList[n], collection parameter value_n>} of the input parameter collection parameter description 1, extracting the numbers in the character data by regular matching to generate a new string, and then converting it into a numeric type; the other type is "formula parameter value 1 = fix_calculate(collection parameter description 1)", which means that data calculation needs to be performed to obtain the formula parameter value. If the parameter values involved in the resource cost calculation model are {formula parameter 1, formula parameter 2, formula parameter 3}, each parameter selects a different function according to its own value-taking method to obtain the parameter value, and then brings it into the corresponding formula to complete the calculation, and the parameter values required by the resource cost calculation model are obtained.

[0049] Clicking the "Show Test Results" button in the Popup pop-up window displays the resource cost settlement result of the cloud computing resource order on the current end page. The result is compared and verified with the payment result on the end page to determine whether the required payment price indicated by the resource cost settlement result is consistent with the payment result displayed on the end page. If they are consistent, it means that the data on the end page is correct, and the user is allowed to proceed to the next step. Otherwise, it means that the data on the end page is incorrect, the process ends, and the user is prohibited from proceeding to the next step. This ensures the reliability of the settlement data and promptly blocks erroneous processes.

[0050] Compared with the prior art, the technical advantages of the embodiments of the present invention are as follows: By automatically verifying the correctness of data transmission between pages through browser extensions, automatically matching the resource cost calculation model of cloud computing resource orders, and automatically collecting the parameter items required by the resource cost calculation model for calculation, the accuracy of page data verification can be improved. It can be applied to different product types and has universality.

[0051] The entire page data verification method can be encapsulated in a browser extension. The program is launched on the start page, and automatically collects, processes, and saves data from each page as the user interacts with it. On the end page, data collection stops and data transfer between pages begins, followed by data verification and display of verification results. Compared to traditional manual testing methods, this method effectively solves the problems of high manpower costs and low efficiency in manual testing. It is not only simple to use and saves manpower costs, but also effectively improves testing efficiency and quality.

[0052] See Figure 2 , Figure 2 This is a structural block diagram of a page data verification device provided in an embodiment of the present invention. The page data verification device includes: The motion capture module 11 is used to capture user actions on the interactive page of the current cloud computing resource order. The parameter acquisition module 12 is used to acquire data from the corresponding interactive page based on at least one data acquisition item required by the current cloud computing resource order when a user action is captured, and to obtain the parameter values ​​corresponding to each data acquisition item on the corresponding interactive page; wherein, the data acquisition item is determined based on the resource cost calculation model matched to the current cloud computing resource order; The data verification module 13 is used to verify the parameter values ​​of all collected interactive pages when redirected to the end page of the current cloud computing resource order, so as to obtain the page data verification result of the current cloud computing resource order.

[0053] In an optional embodiment, the device further includes: The first feature data determination module is used to perform feature analysis on various types of cloud computing resource orders and determine the feature data of various types of cloud computing resource orders; wherein, the feature data includes the product name of the cloud computing resource, the order scenario, the billing type, and the resource cost calculation model; The feature database construction module is used to build a multi-level indexed feature database based on the feature data of various types of cloud computing resource orders; wherein, the feature database uses product name, order scenario, and billing type as indexes, and resource cost calculation model as index target.

[0054] In an optional embodiment, the device further includes: The second feature data determination module is used to search the feature database based on the product name, order scenario, and billing type of the current cloud computing resource order to determine the feature data that matches the product name, order scenario, and billing type of the current cloud computing resource order. The data collection item determination module is used to determine the data collection items required for the current cloud computing resource order based on the corresponding parameter items of the resource overhead calculation model in the matched feature data.

[0055] In an optional embodiment, the device further includes: The page address acquisition module is used to acquire the page address of the currently interactive page and check whether the page address exists in the address list; The address saving module is used to add the page address to the address list when the page address does not exist in the address list, and to save the page address and the parameter values ​​of the corresponding interactive page to the address parameter association set according to a preset string format. The parameter value update module is used to update the parameter value corresponding to the corresponding page address in the address parameter association set according to the parameter value of the corresponding interactive page when the page address exists in the address list.

[0056] In one optional embodiment, the parameter acquisition module 12 includes: A tag determination unit is used to extract resource data descriptions from the data collection items and determine the smallest container tag of the page containing the resource data descriptions; The data acquisition unit is used to acquire the data values ​​of the form input controls under the smallest container label of the interactive page, and use them as the parameter values ​​corresponding to the data acquisition items.

[0057] In an optional embodiment, the device further includes: The calculation module is used to calculate the resource cost settlement result of the current cloud computing resource order based on the matched resource cost calculation model and the parameter values ​​corresponding to each of the data collection items. The comparison module is used to compare and verify the resource cost settlement result with the payment result displayed on the end page to obtain a data consistency verification result.

[0058] It should be noted that the working process of each module in the page data verification device described in the embodiments of the present invention can refer to the working process of the page data verification method described in the above embodiments, and the technical effect achieved is the same as that of the page data verification method described in the above embodiments, so it will not be repeated here.

[0059] See Figure 3 , Figure 3 This is a structural block diagram of a page data verification device provided in an embodiment of the present invention. The page data verification device includes a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, it implements the steps in the various page data verification method embodiments described above, such as steps S11 to S13.

[0060] For example, the computer program may be divided into one or more modules or units, which are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules or units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the page data verification device.

[0061] The page data verification device may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will understand that the schematic diagram is merely an example of a page data verification device and does not constitute a limitation on the device. It may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the page data verification device may also include input / output devices, network access devices, buses, etc.

[0062] The processor 21 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 21 is the control center of the page data verification device, connecting all parts of the entire page data verification device via various interfaces and lines.

[0063] The memory 22 can be used to store the computer programs and / or modules. The processor 21 implements various functions of the page data verification device by running or executing the computer programs and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0064] If the modules or units integrated into the page data verification device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 21, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0065] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0066] The above description represents the preferred embodiments of the present invention. It should be noted that, for those skilled in the art, various improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for verifying page data, characterized in that, include: Capture user actions on the interactive page of the current cloud computing resource order; Upon capturing user actions, data is collected from the corresponding interactive page based on at least one data collection item required for the current cloud computing resource order, to obtain parameter values ​​corresponding to each of the data collection items on the corresponding interactive page; wherein, the data collection item is determined based on the resource cost calculation model matched to the current cloud computing resource order; Upon redirection to the end page of the current cloud computing resource order, all collected parameter values ​​from the interactive pages are verified to obtain the page data verification results for the current cloud computing resource order.

2. The page data verification method as described in claim 1, characterized in that, The method further includes: Feature analysis is performed on various types of cloud computing resource orders to determine the characteristic data of each type of cloud computing resource order; wherein, the characteristic data includes the product name of the cloud computing resource, the order scenario, the billing type, and the resource cost calculation model; A multi-level indexed feature database is constructed based on the characteristic data of various types of cloud computing resource orders; wherein, the feature database is indexed by product name, order scenario, and billing type, and the resource cost calculation model is the index target.

3. The page data verification method as described in claim 2, characterized in that, The process of determining the data collection items includes: Based on the product name, order scenario, and billing type of the current cloud computing resource order, the feature database is searched to determine the feature data that matches the product name, order scenario, and billing type of the current cloud computing resource order. Based on the parameter items corresponding to the resource overhead calculation model in the matched feature data, determine the data collection items required for the current cloud computing resource order.

4. The page data verification method as described in claim 1, characterized in that, The method further includes: Collect the page address of the currently interacting page and check if the page address exists in the address list; When the page address does not exist in the address list, the page address is added to the address list, and the page address and the parameter values ​​of the corresponding interactive page are saved to the address parameter association set according to a preset string format. When the address list contains the page address, the parameter value corresponding to the page address in the address parameter association set is updated according to the parameter value of the corresponding interactive page.

5. The page data verification method as described in claim 1, characterized in that, Based on at least one data collection item required by the current cloud computing resource order, data is collected from the corresponding interactive page to obtain the parameter values ​​corresponding to each data collection item on the corresponding interactive page, including: Extract resource data descriptions from the data collection items and determine the smallest container tag for the page containing the resource data descriptions; Obtain the data value of the form input control under the smallest container label of the interactive page, and use it as the parameter value corresponding to the data collection item.

6. The page data verification method as described in claim 1, characterized in that, The method further includes: Based on the matched resource overhead calculation model and the parameter values ​​corresponding to each of the data collection items, calculate the resource overhead settlement result for the current cloud computing resource order; The resource cost settlement result is compared and verified with the payment result displayed on the end page to obtain the data consistency verification result.

7. A page data verification device, characterized in that, include: The motion capture module is used to capture user actions on the interactive page of the current cloud computing resource order. The parameter acquisition module is used to acquire data from the corresponding interactive page based on at least one data acquisition item required by the current cloud computing resource order when user actions are captured, and to obtain the parameter values ​​corresponding to each data acquisition item on the corresponding interactive page; wherein, the data acquisition item is determined based on the resource cost calculation model matched to the current cloud computing resource order; The data verification module is used to verify the parameter values ​​of all collected interactive pages when redirected to the end page of the current cloud computing resource order, and obtain the page data verification result of the current cloud computing resource order.

8. A page data verification device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the page data verification method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the page data verification method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the page data verification method according to any one of claims 1 to 6.

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