CN116090808A - RPA breakpoint reconstruction method and device, electronic equipment and medium - Google Patents
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Abstract
The application relates to the technical field of automated processing, in particular to an RPA breakpoint reconstruction method, an apparatus, an electronic device and a medium, wherein the method comprises the following steps: the method comprises the steps of obtaining a historical execution log and current breakpoint information, determining an abnormal type of the current breakpoint information according to the historical execution log, determining reconstruction information of the current breakpoint information in a preset reconstruction standard based on the abnormal type, and generating a calling instruction according to the reconstruction information so as to call an execution component in an RPA execution flow to complete a reconstruction task of a breakpoint. By the method, the process can be automatically rebuilt when the RPA execution process is abnormal, and the fault tolerance of the RPA processing service process is improved.
Description
Technical Field
The application relates to the technical field of automated processing, in particular to an RPA breakpoint reconstruction method, an apparatus, an electronic device and a medium.
Background
The RPA is robot flow automation, can replace manpower to perform a large number of repeated works, such as business clearing, regular inspection, resource management system operation and other business scenes with fixed rules, can finish the work with higher efficiency, and simultaneously reduce the error rate caused by manual operation, and is currently applied to industries such as logistics, finance, electronic commerce, insurance and the like. For example, the logistics industry needs to collect a large amount of customer data in real time, and when the task of collecting customer data in real time is finished by manpower, the time is long, and the accuracy of final data is difficult to ensure.
However, since the RPA needs to define the processing flow in advance for the service scenario mainly aimed at, when the processing flow has a problem, the RPA cannot analyze the problem autonomously, so that the service flow is easy to be interrupted or abnormal, that is, the fault tolerance rate is low when the current RAP processes the service.
Disclosure of Invention
The purpose of the application is to provide an RPA breakpoint reconstruction method, an RPA breakpoint reconstruction device, electronic equipment and a medium, which are used for solving at least one technical problem.
The above object of the present application is achieved by the following technical solutions:
in a first aspect, the present application provides a method for reconstructing RPA breakpoint, which adopts the following technical scheme:
an RPA breakpoint reconstruction method, comprising:
acquiring a history execution log and current breakpoint information, wherein the current breakpoint information is execution flow information of a current RPA processing flow interrupt;
determining the abnormal type of the current breakpoint information according to the historical execution log;
and determining reconstruction information of the current breakpoint information in a preset reconstruction standard based on the abnormal type, and generating a calling instruction according to the reconstruction information so as to call an execution component in an RPA execution flow to complete a reconstruction task at the breakpoint.
In another possible implementation manner, the determining the exception type of the current breakpoint information according to the historical execution log includes:
determining a historical breakpoint flow in the historical execution log, wherein the historical breakpoint flow is an execution flow which is interrupted in the historical execution log due to flow abnormality;
determining the node position of the breakpoint position in the current breakpoint information, wherein the node position appears in the historical breakpoint flow;
judging whether the information quantity at the node position meets a preset standard or not;
if yes, determining the abnormal type of the current breakpoint information as an internal abnormal, and if not, determining the abnormal type of the current breakpoint information as an external abnormal.
In another possible implementation manner, the determining, based on the anomaly type, reconstruction information of the current breakpoint information in a preset reconstruction standard includes:
if the abnormality type is an external abnormality, determining the reconstruction information according to a target position in the current breakpoint information and the preset reconstruction standard, wherein the target position is an acquisition position when the execution flow acquires target information, and the target information is designated information acquired by the execution flow.
In another possible implementation manner, the determining the reconstruction information according to the target position in the current breakpoint information and the preset reconstruction standard includes:
determining the transmission type of the target information in the current breakpoint information;
updating the target position according to the transmission type and the target information;
and determining the reconstruction information based on the updated target position.
In another possible implementation, the method further includes:
if the abnormal type is internal abnormality, checking a data source in the current breakpoint information according to the historical execution log, and marking the data source according to a checking result;
determining an input position corresponding to the data source;
and generating user prompt information according to the input position so as to remind a user to verify the input information corresponding to the input position.
In another possible implementation manner, the generating a call instruction according to the reconstruction information further includes:
checking the target information according to the type of the target information in the current breakpoint information;
if the verification result is that the information type corresponding to the target information does not belong to the target information type, updating the target position according to the position unit corresponding to the target position;
and updating the reconstruction information according to the updated target position.
In another possible implementation manner, the updating the reconstruction information according to the updated target position further includes:
and generating feedback information according to the updated target position.
In a second aspect, the present application provides an RPA breakpoint reconstruction device, which adopts the following technical scheme:
the information acquisition module is used for acquiring a history execution log and current breakpoint information, wherein the current breakpoint information is execution flow information at a breakpoint of a current RPA processing flow;
the type determining module is used for determining the abnormal type of the current breakpoint information according to the historical execution log;
and the information determining module is used for determining the reconstruction information of the current breakpoint information in a preset reconstruction standard based on the abnormal type, and generating a calling instruction according to the reconstruction information so as to call an execution component in an RPA execution flow to complete the reconstruction task at the breakpoint.
In another possible implementation manner, when the determining type module determines the exception type of the current breakpoint information based on the historical execution log, the determining type module is specifically configured to:
determining a historical breakpoint flow in the historical execution log, wherein the historical breakpoint flow is an execution flow which is interrupted in the historical execution log due to flow abnormality;
determining the node position of the breakpoint position in the current breakpoint information, wherein the node position appears in the historical breakpoint flow;
judging whether the information quantity at the node position meets a preset standard or not;
if yes, determining the abnormal type of the current breakpoint information as an internal abnormal, and if not, determining the abnormal type of the current breakpoint information as an external abnormal.
In another possible implementation manner, when the determining information module determines the reconstruction information of the current breakpoint information in a preset reconstruction standard based on the anomaly type, the determining information module is specifically configured to:
if the abnormality type is an external abnormality, determining the reconstruction information according to a target position in the current breakpoint information and the preset reconstruction standard, wherein the target position is an acquisition position when the execution flow acquires target information, and the target information is designated information acquired by the execution flow.
In another possible implementation manner, when the determining information module determines the reconstruction information according to the target position in the current breakpoint information and the preset reconstruction standard, the determining information module is specifically configured to:
determining the transmission type of the target information in the current breakpoint information;
updating the target position according to the transmission type and the target information;
and determining the reconstruction information based on the updated target position.
In another possible implementation, the apparatus further includes: a marking information module, a determining input module and a generating prompt module, wherein,
the marking information module is used for verifying the data source in the current breakpoint information according to the historical execution log and marking the data source according to a verification result;
the determining input module is used for determining the input position corresponding to the data source;
and the generation prompt module is used for generating user prompt information according to the input position so as to remind a user to check the input information corresponding to the input position.
In another possible implementation, the apparatus further includes: a verification target information module, an update target position module and an update reconstruction information module, wherein,
the verification target information module is used for verifying the target information according to the target information type in the current breakpoint information;
the updating target position module is used for updating the target position according to the position unit corresponding to the target position;
the reconstruction information updating module is used for updating the reconstruction information according to the updated target position.
In another possible implementation, the apparatus further includes: a feedback module is generated, wherein,
and the generation feedback module is used for generating feedback information according to the updated target position.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
at least one processor;
a memory;
at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: and executing the RPA breakpoint reconstruction method.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the RPA breakpoint reconstruction method as described above.
In summary, the present application includes at least one of the following beneficial technical effects:
compared with the related art, in the method, the history execution log and the current breakpoint information of the RPA execution flow are obtained, the abnormal type of the breakpoint of the execution flow corresponding to the current breakpoint information is determined according to the history execution log, the reconstruction information is obtained according to the preset reconstruction standard and the determined abnormal type, the corresponding reconstruction information of the RPA breakpoint is determined according to different abnormal types, finally, a call instruction is generated according to the reconstruction information, an execution assembly in the RPA execution flow is controlled to complete reconstruction of the breakpoint of the current execution flow, the independent breakpoint reconstruction of the RPA is realized, and the fault tolerance of the RPA during processing business process is improved.
Drawings
FIG. 1 is a flow chart of an RPA breakpoint reconstruction method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an RPA breakpoint reconstruction device according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an RPA breakpoint reconstruction electronic device according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below in conjunction with fig. 1-3.
The present embodiment is merely illustrative of the present application and is not intended to be limiting, and those skilled in the art, after having read the present specification, may make modifications to the present embodiment without creative contribution as required, but is protected by patent laws within the scope of the present application.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Embodiments of the present application are described in further detail below with reference to the drawings attached hereto.
The embodiment of the application provides an RPA breakpoint reconstruction method, which is executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, or the like, but is not limited thereto, and the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, which is not limited herein, and as shown in fig. 1, the method may include step S11, step S12, and step S13, where:
step S11, acquiring a history execution log and current breakpoint information.
The execution log in the embodiment of the application includes current breakpoint information and historical execution log, the current breakpoint information is flow information of a current interrupt flow, the current breakpoint information includes a start time, a breakpoint position, target information and a target position of the current interrupt flow, the historical execution log is an execution log existing in a memory 30 days before the start time of the current interrupt flow, and includes a flow type and an execution state of the historical execution flow.
For the embodiment of the application, the execution log in the local memory is obtained, the execution log existing 30 days before the starting time of the current interrupt flow is used as the historical execution log, and the flow information corresponding to the current interrupt flow is used as the current breakpoint information.
Step S12, determining the abnormal type of the current breakpoint information according to the historical execution log.
Wherein the exception types include external exceptions and internal exceptions, and generally, the external exceptions include operation object exceptions and resource exceptions, for example, execution flow interruption belongs to resource exceptions due to the failure of WPS on which RPA robots run to normally open; internal anomalies include business logic anomalies and robot anomalies, for example, business logic anomalies are the case when a business process exceeds a given business rule, and robot anomalies are the case when an execution flow is interrupted due to an operation error of an RPA robot.
For the embodiment of the application, the breakpoint position in the current breakpoint information is determined, a historical execution flow with the execution state of execution interruption is screened out from the historical execution log, and the display position of the breakpoint position is determined in the obtained historical execution flow. And determining the historical execution flow which is the same as the current breakpoint information flow type in the screened historical execution flow, and determining the abnormal type of the current breakpoint information according to the display position of the breakpoint position in the determined historical execution flow and the historical execution log corresponding to the determined historical execution flow.
And step S13, determining reconstruction information of the current breakpoint information in a preset reconstruction standard based on the exception type, and generating a call instruction according to the reconstruction information so as to call an execution component in the RPA execution flow to complete a reconstruction task at the current breakpoint.
The preset reconstruction standard is the corresponding relation between the target position in the current breakpoint information and the reconstruction information, and the target position is the acquisition position when the execution flow corresponding to the current breakpoint information acquires the information.
For the embodiment of the application, when the abnormal type of the current breakpoint information is external abnormality, matching the target position in the current breakpoint information with a preset reconstruction standard, and generating a call instruction according to reconstruction information obtained by matching so as to reconstruct an execution flow corresponding to the current breakpoint information.
In another possible implementation manner of the embodiment of the present application, step S12 may specifically include step S121 (not shown in the figure), step S122 (not shown in the figure), step S123 (not shown in the figure), and step S124 (not shown in the figure), where,
step S121, determining a history breakpoint flow in the history execution log.
The historical breakpoint flow is an execution flow with an execution state of execution interruption in the historical execution log.
For the embodiment of the application, the historical breakpoint flow is obtained by screening according to the execution state of the historical execution flow in the historical execution log. And screening and reserving the historical breakpoint flow with the same flow type as that in the current breakpoint information in the reserved historical breakpoint flow according to the flow type of the historical execution flow.
Step S122, determining the node position of the breakpoint position in the current breakpoint information, which occurs in the historical breakpoint flow.
For the embodiment of the application, comparing the node position in the history breakpoint flow with the breakpoint position in the current breakpoint information, and when the node position is the same as the executing node corresponding to the breakpoint position and the executing node corresponding to the node position is the interrupt node in the corresponding history breakpoint flow, reserving the corresponding history breakpoint flow and the node position corresponding to the breakpoint position.
Step S123, determining whether the information amount at the node position meets the preset standard.
The preset standard is to be adjusted according to the usage scenario of the RPA, and in the embodiment of the present application, the preset standard is that the information amounts at the display positions are the same in the adjacent historical breakpoint flows.
Step S124, if yes, determining the abnormality type of the current breakpoint information as an internal abnormality, and if not, determining the abnormality type of the current breakpoint information as an external abnormality.
For the embodiment of the application, determining adjacent breakpoint flows in the historical breakpoint flows, judging whether the information quantity at the display position in the adjacent breakpoint flows is the same, if the information quantity is the same, determining that the abnormality type is internal abnormality, otherwise, if the information quantity is different, determining that the abnormality type is external abnormality. The adjacent breakpoint flow means a historical execution flow when the execution flow fails to be executed twice or more continuously, for example, the adjacent breakpoint flow is a historical breakpoint flow with a time difference of less than 5 minutes at a start time, and when the technical scheme in the application is actually applied, the definition should be adjusted according to the type, the effect and other actual conditions of the historical breakpoint flow, and the method is not limited to the definition in the examples in the embodiments of the application.
For example, if the first execution flow is interrupted due to network delay during the execution of the adjacent breakpoint flows, the amount of information acquired by the interruption node is 0 when the flow is executed, that is, the amount of information of the interruption node is 0. And then the network speed is partially recovered in the second execution flow, but the network speed is still unstable, so that the information amount acquired by the interrupt node is 2KB when the flow is executed, namely the information amount of the interrupt node is 2KB. At this time, the information amount obtained by the interrupt node of the adjacent breakpoint flow is different, that is, the information amount corresponding to the display position of the adjacent breakpoint flow is different, and the current breakpoint information exception type corresponding to the adjacent breakpoint flow is determined to be external exception.
The information quantity at the interrupt node is determined to judge the abnormal type corresponding to the current breakpoint information, so that the interrupt flow which can be autonomously reconstructed by the RPA is determined, and the efficiency of the follow-up reconstruction execution flow is improved.
In another possible implementation manner of the embodiment of the present application, step S13 may specifically include step S131 (not shown in the figure), where,
step S131, if the abnormality type is an external abnormality, the reconstruction information is determined according to the target position in the current breakpoint information and the preset reconstruction standard.
The target position is an acquisition position when the execution flow acquires target information, which means an expected acquisition position of an RPA user when the RPA acquires the target information, namely, an acquisition position corresponding to the target information in the current breakpoint information, the target information is designated information acquired by the execution flow, which means the designated acquisition information of the RPA user when the RPA is used, namely, the acquisition information of the RPA flow, and a preset reconstruction standard is a corresponding relation between a transmission type of the target information and a reconstruction mode.
For the embodiment of the application, if the abnormal type of the current breakpoint information is an external abnormality, judging whether the transmission type of the target information in transmission is sub-packet transmission, if so, searching a reconstruction mode corresponding to sub-packet transmission in a preset reconstruction standard, updating a target position in the current breakpoint information, namely, the position of the RPA when the target information is acquired next time, according to the reconstruction mode and the target information, and finally determining reconstruction information of an execution flow of the reconstruction RPA according to the updated target position.
In another possible implementation manner of the embodiment of the present application, step S131 may specifically include step S1311 (not shown in the figure), step S1312 (not shown in the figure), and step S1313 (not shown in the figure), where,
in step S1311, the transmission type of the target information in the current breakpoint information is determined.
Step S1312, updating the target location according to the transmission type and the target information.
For the embodiment of the application, the transmission type of the target information is determined according to the information type of the target information in the current breakpoint information, for example, if the information type of the target information is a png type image, the transmission type is determined to be packet transmission; and if the target information is text of txt type, the transmission type is determined to be whole packet transmission.
If the determined transmission type is the sub-packet transmission, judging whether the information quantity of the target information is larger than 0, if so, packaging the acquired information, and searching a reconstruction mode corresponding to the sub-packet transmission in a preset reconstruction standard.
And determining the acquisition position when the target information is acquired next time according to the corresponding reconstruction mode and the target information, and replacing the acquisition position with the target position.
For example, the target information gives a png image of width 646 pixels, height 909 pixels, and size 24kb, reconstructed by: dividing the acquired information and the target information appointed in the RPA user into a plurality of areas by taking 1 pixel as a unit, determining information parameters of the target information according to the current breakpoint information, determining information parameters of the acquired information according to a data source, matching the information parameters of all areas in the target information with the information parameters of all areas in the acquired information, determining the position of a matching failure area, taking the determined position as an acquired position when reconstructing the RPA execution flow, and finally replacing the acquired position with the target position. By matching the information parameters, the area with failed matching is locked, the repeated acquisition of the partial correct target information which is already acquired by the reconstructed execution flow is avoided, and the speed of acquiring the complete target information is improved.
In step S1313, the reconstruction information is determined based on the updated target position.
For the embodiment of the application, when the target position is taken as the position of the target information during the reconstruction execution flow, namely, the information corresponding to the target position is taken as the grabbing object of the execution flow after reconstruction, and the reconstruction information is generated according to the target position and the grabbing object so as to facilitate reconstruction of the RPA execution flow. For example, when the updated target position is a certain interface coordinate on the web page, taking the data at the corresponding interface coordinate as a grabbing object, and then generating reconstruction information to grab the information at the corresponding interface coordinate on the web page, so as to reconstruct the RPA execution flow.
Another possible implementation manner of the embodiment of the present application further includes step S101 (not shown in the figure), step S102 (not shown in the figure), and step S103, where,
step S101, if the abnormality type is internal abnormality, checking the data source in the current breakpoint information according to the historical execution log, and marking the data source according to the checking result.
The data source is various input parameters manually input when the RPA user performs component arrangement in the RPA editor.
For the embodiment of the application, if the abnormality type of the current breakpoint information is internal abnormality, a history execution log corresponding to a history breakpoint flow is searched, history data with the same data type as that of a data source in the history execution log is determined, and a history input section is formed according to the maximum value and the minimum value in the determined history data. Judging whether the data corresponding to the data type in the data source is in a history input interval or not, if not, determining that the verification result is verification failure, and marking the corresponding data source.
Step S102, determining the input position corresponding to the data source.
Step S103, generating user prompt information according to the input positions so as to remind the user to check the input information corresponding to the input positions.
For the embodiment of the application, the input position corresponding to the data source in the current breakpoint information is determined, and user prompt information is generated according to the input position, for example, the user prompt information is: you need to check the input information at the "timeout time" in the RPA flow library.
Another possible implementation manner of the embodiment of the present application, step S13 may further include step S1301 (not labeled in the figure), step S1302 (not labeled in the figure), and step S1303 (not labeled in the figure), where,
step S1301, the target information is checked according to the target information type in the current breakpoint information.
The verification mode adopted by the embodiment of the application is matching, and the verification mode can be adjusted according to actual conditions when the technical scheme in the application is actually applied.
In step S1302, if the verification result is that the information type corresponding to the target information does not belong to the target information type, the target position is updated according to the position unit corresponding to the target position.
For the embodiment of the application, the information type of the target information is determined, the determined information type is matched with the target information type in the current breakpoint information, if the matching fails, verification is determined to fail, and a last-stage position unit corresponding to the lowest-stage position unit of the target position is reserved as the lowest-stage position unit so as to update the target position.
Step S1303, updating the reconstruction information according to the updated target position.
For the embodiment of the present application, the grabbing object is updated according to the information corresponding to the updated target position, and the reconstruction information is determined by the same method as in step S403, which is not described herein again. In the embodiment of the application, by expanding the target position, the interruption of the execution flow caused by the change of the target information position is avoided to a certain extent, and the fault tolerance of the RPA is improved.
Another possible implementation manner of the embodiment of the present application, step S1303 further includes step S13031 (not labeled in the drawing), where,
step S13031, generating feedback information according to the updated target position.
For the embodiment of the application, the feedback information is generated by the lowest position unit corresponding to the target position before updating and the lowest position unit after updating. For example, the unit of the lowest level position corresponding to the target position before updating is j rows and i columns of sheet1 in the excel data table, and the unit of the position after updating is sheet1 in the excel data table, the feedback information is generated as follows: corresponding information does not exist in j rows and i columns in the sheet1, and the corresponding information acquisition position is automatically adjusted to the sheet 1.
The above embodiment describes an RPA breakpoint reconstruction method from the viewpoint of a method flow, and the following embodiment describes an RPA breakpoint reconstruction device from the viewpoint of a virtual module or a virtual unit, which is described in detail in the following embodiment.
An embodiment of the present application provides an RPA breakpoint reconstruction device 20, as shown in fig. 2, the RPA breakpoint reconstruction device 20 may specifically include: an acquisition information module 21, a determination type module 22, and a determination information module 23, wherein,
the acquiring information module 21 is configured to acquire a history execution log and current breakpoint information, where the current breakpoint information is execution flow information at a breakpoint of a current RPA processing flow;
a determining type module 22, configured to determine an exception type of the current breakpoint information according to the historical execution log;
the determining information module 23 is configured to determine rebuilding information of the current breakpoint information in a preset rebuilding standard based on the exception type, and generate a call instruction according to the rebuilding information, so as to call an execution component in the RPA execution flow to complete a rebuilding task at the breakpoint.
One possible implementation manner of the embodiment of the present application is specifically configured to, when determining the type of exception of the current breakpoint information according to the historical execution log, the type determining module 22:
determining a historical breakpoint flow in a historical execution log, wherein the historical breakpoint flow is an execution flow which is interrupted in the historical execution log due to flow abnormality;
determining the node position of the breakpoint position in the current breakpoint information in the historical breakpoint flow;
judging whether the information quantity at the node position meets a preset standard or not;
if yes, determining the abnormal type of the current breakpoint information as internal abnormality, and if not, determining the abnormal type of the current breakpoint information as external abnormality.
In one possible implementation manner of this embodiment of the present application, when the determining information module 23 determines the reconstruction information of the current breakpoint information in the preset reconstruction standard based on the anomaly type, the determining information module is specifically configured to:
if the abnormality type is external abnormality, determining reconstruction information according to a target position in the current breakpoint information and a preset reconstruction standard, wherein the target position is an acquisition position when the execution flow acquires target information, and the target information is designated information acquired by the execution flow.
In one possible implementation manner of the embodiment of the present application, when determining that the information module 23 determines the reconstruction information according to the target position in the current breakpoint information and the preset reconstruction standard, the method is specifically used for:
determining the transmission type of target information in the current breakpoint information;
updating the target position according to the transmission type and the target information;
and determining reconstruction information based on the updated target position.
In one possible implementation manner of the embodiment of the present application, the apparatus 20 further includes: a marking information module, a determining input module and a generating prompt module, wherein,
the marking information module is used for verifying the data source in the current breakpoint information according to the historical execution log and marking the data source according to the verification result;
the input determining module is used for determining the input position corresponding to the data source;
and the generating prompt module is used for generating user prompt information according to the input position so as to remind the user to check the input information corresponding to the input position.
In one possible implementation manner of the embodiment of the present application, the apparatus 20 further includes: a verification target information module, an update target position module and an update reconstruction information module, wherein,
the verification target information module is used for verifying target information according to the type of the target information in the current breakpoint information;
the updating target position module is used for updating the target position according to the position unit corresponding to the target position;
and the updating reconstruction information module is used for updating the reconstruction information according to the updated target position.
In one possible implementation manner of the embodiment of the present application, the apparatus 20 further includes: a feedback module is generated, wherein,
and the generation feedback module is used for generating feedback information according to the updated target position.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the RPA breakpoint reconstruction device 20 described above may refer to the corresponding process in the foregoing method embodiment, and will not be described herein again.
In an embodiment of the present application, as shown in fig. 3, an electronic device 300 shown in fig. 3 includes: a processor 301 and a memory 303. Wherein the processor 301 is coupled to the memory 303, such as via a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that, in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 is not limited to the embodiment of the present application.
The processor 301 may be a CPU (Central Processing Unit ), general purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit ), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. Processor 301 may also be a combination that implements computing functionality, e.g., comprising one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.
The Memory 303 may be, but is not limited to, a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory ), a CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 303 is used for storing application program codes for executing the present application and is controlled to be executed by the processor 301. The processor 301 is configured to execute the application code stored in the memory 303 to implement what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. But may also be a server or the like. The electronic device shown in fig. 3 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments herein.
The present application provides a computer readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application and it should be noted that, for a person skilled in the art, several improvements and modifications can be made without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. An RPA breakpoint reconstruction method, comprising:
acquiring a history execution log and current breakpoint information, wherein the current breakpoint information is execution flow information at a breakpoint of a current RPA processing flow;
determining the abnormal type of the current breakpoint information according to the historical execution log;
and determining reconstruction information of the current breakpoint information in a preset reconstruction standard based on the abnormal type, and generating a calling instruction according to the reconstruction information so as to call an execution component in an RPA execution flow to complete a reconstruction task at the breakpoint.
2. The method of claim 1, wherein determining the exception type of the current breakpoint information according to the historical execution log comprises:
determining a historical breakpoint flow in the historical execution log, wherein the historical breakpoint flow is an execution flow which is interrupted in the historical execution log due to flow abnormality;
determining the node position of the breakpoint position in the current breakpoint information, wherein the node position appears in the historical breakpoint flow;
judging whether the information quantity at the node position meets a preset standard or not;
if yes, determining the abnormal type of the current breakpoint information as an internal abnormal, and if not, determining the abnormal type of the current breakpoint information as an external abnormal.
3. The method for RPA breakpoint reconstruction according to claim 1, wherein the determining reconstruction information of the current breakpoint information in a preset reconstruction standard based on the anomaly type includes:
if the abnormality type is an external abnormality, determining the reconstruction information according to a target position in the current breakpoint information and the preset reconstruction standard, wherein the target position is an acquisition position when the execution flow acquires target information, and the target information is designated information acquired by the execution flow.
4. A method of RPA breakpoint reconstruction according to claim 3, wherein the determining the reconstruction information according to the target location in the current breakpoint information and the preset reconstruction criteria includes:
determining the transmission type of the target information in the current breakpoint information;
updating the target position according to the transmission type and the target information;
and determining the reconstruction information based on the updated target position.
5. A method of RPA breakpoint reconstruction according to claim 3, further comprising:
if the abnormal type is internal abnormality, checking a data source in the current breakpoint information according to the historical execution log, and marking the data source according to a checking result;
determining an input position corresponding to the data source;
and generating user prompt information according to the input position so as to remind a user to verify the input information corresponding to the input position.
6. A method of RPA breakpoint reconstruction according to claim 3, wherein the generating a call instruction according to the reconstruction information further comprises:
checking the target information according to the type of the target information in the current breakpoint information;
if the verification result is that the information type corresponding to the target information does not belong to the target information type, updating the target position according to the position unit corresponding to the target position;
and updating the reconstruction information according to the updated target position.
7. The method of claim 6, wherein the updating the reconstruction information according to the updated target position further comprises:
and generating feedback information according to the updated target position.
8. An RPA breakpoint reconstruction device, comprising:
the information acquisition module is used for acquiring a history execution log and current breakpoint information, wherein the current breakpoint information is execution flow information at a breakpoint of a current RPA processing flow;
the type determining module is used for determining the abnormal type of the current breakpoint information according to the historical execution log;
and the information determining module is used for determining the reconstruction information of the current breakpoint information in a preset reconstruction standard based on the abnormal type, and generating a calling instruction according to the reconstruction information so as to call an execution component in an RPA execution flow to complete the reconstruction task at the breakpoint.
9. An electronic device, comprising:
at least one processor;
a memory;
at least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: performing the RPA breakpoint reconstruction method according to any one of claims 1 to 7.
10. A computer readable storage medium, having stored thereon a computer program which, when executed in a computer, causes the computer to perform the RPA breakpoint reconstruction method according to any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116596292A (en) * | 2023-07-17 | 2023-08-15 | 知微行易(上海)智能科技有限公司 | Method for generating dynamic OCAP abnormal action plan |
| CN116634209A (en) * | 2023-07-24 | 2023-08-22 | 武汉能钠智能装备技术股份有限公司 | Breakpoint video recovery system and method based on hot plug |
| CN117193232A (en) * | 2023-07-26 | 2023-12-08 | 珠海金智维信息科技有限公司 | RPA-based flow node fault processing method, system, device and medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160124835A1 (en) * | 2014-10-29 | 2016-05-05 | Microsoft Corporation | Diagnostic workflow for production debugging |
| CN109325865A (en) * | 2018-08-13 | 2019-02-12 | 中国平安人寿保险股份有限公司 | Abnormality eliminating method, device, computer equipment and storage medium |
| CN111949551A (en) * | 2020-09-01 | 2020-11-17 | 网易（杭州）网络有限公司 | Application program testing method, device, equipment and storage medium |
| CN112241330A (en) * | 2020-03-31 | 2021-01-19 | 北京来也网络科技有限公司 | Flow processing method, device, equipment and storage medium combining RPA and AI |
| CN113626227A (en) * | 2020-05-06 | 2021-11-09 | 深圳Tcl新技术有限公司 | Abnormal log information reporting method, intelligent terminal and storage medium |
| CN113626241A (en) * | 2021-08-10 | 2021-11-09 | 中国平安财产保险股份有限公司 | Application program exception handling method, device, equipment and storage medium |
| CN113672427A (en) * | 2021-08-26 | 2021-11-19 | 北京来也网络科技有限公司 | Exception handling method, device, equipment and medium based on RPA and AI |
| CN114398239A (en) * | 2022-01-18 | 2022-04-26 | 平安国际智慧城市科技股份有限公司 | Log monitoring method and device, computer equipment and storage medium |
-
2023
- 2023-03-06 CN CN202310205389.2A patent/CN116090808A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160124835A1 (en) * | 2014-10-29 | 2016-05-05 | Microsoft Corporation | Diagnostic workflow for production debugging |
| CN109325865A (en) * | 2018-08-13 | 2019-02-12 | 中国平安人寿保险股份有限公司 | Abnormality eliminating method, device, computer equipment and storage medium |
| CN112241330A (en) * | 2020-03-31 | 2021-01-19 | 北京来也网络科技有限公司 | Flow processing method, device, equipment and storage medium combining RPA and AI |
| CN113626227A (en) * | 2020-05-06 | 2021-11-09 | 深圳Tcl新技术有限公司 | Abnormal log information reporting method, intelligent terminal and storage medium |
| CN111949551A (en) * | 2020-09-01 | 2020-11-17 | 网易（杭州）网络有限公司 | Application program testing method, device, equipment and storage medium |
| CN113626241A (en) * | 2021-08-10 | 2021-11-09 | 中国平安财产保险股份有限公司 | Application program exception handling method, device, equipment and storage medium |
| CN113672427A (en) * | 2021-08-26 | 2021-11-19 | 北京来也网络科技有限公司 | Exception handling method, device, equipment and medium based on RPA and AI |
| CN114398239A (en) * | 2022-01-18 | 2022-04-26 | 平安国际智慧城市科技股份有限公司 | Log monitoring method and device, computer equipment and storage medium |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116596292A (en) * | 2023-07-17 | 2023-08-15 | 知微行易(上海)智能科技有限公司 | Method for generating dynamic OCAP abnormal action plan |
| CN116596292B (en) * | 2023-07-17 | 2023-09-12 | 知微行易(上海)智能科技有限公司 | Method for generating dynamic OCAP abnormal action plan |
| CN116634209A (en) * | 2023-07-24 | 2023-08-22 | 武汉能钠智能装备技术股份有限公司 | Breakpoint video recovery system and method based on hot plug |
| CN116634209B (en) * | 2023-07-24 | 2023-11-17 | 武汉能钠智能装备技术股份有限公司 | Breakpoint video recovery system and method based on hot plug |
| CN117193232A (en) * | 2023-07-26 | 2023-12-08 | 珠海金智维信息科技有限公司 | RPA-based flow node fault processing method, system, device and medium |
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