CN114157701B - Task testing method, device, equipment and storage medium - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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Abstract
The disclosure provides a task testing method, a task testing device, electronic equipment and a storage medium, relates to the technical field of cloud computing, and particularly relates to the technical field of cloud mobile phones. The specific implementation scheme is as follows: responding to a test request sent by a test demand end, and determining a target cloud mobile phone from locally deployed candidate cloud mobile phones; controlling the target cloud mobile phone to execute a test task in the test request; and generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end. The scheme of performing task test by matching the test demand end with the cloud server and the cloud mobile phone deployed by the cloud server is provided, and a new solution is provided for performing task test with low cost and high efficiency.
Description
Technical Field
The disclosure relates to the technical field of cloud computing, in particular to the technical field of cloud mobile phones, and specifically relates to a task testing method, device and equipment and a storage medium.
Background
With the development of computer technology, various artificial intelligence tasks, such as a voice interaction task, a model prediction task, an image recognition task and the like, have been applied to aspects of our lives. The quality of the artificial intelligence task effect directly affects the user experience. Therefore, testing of artificial intelligence tasks is critical.
Disclosure of Invention
The disclosure provides a task testing method, a task testing device, electronic equipment and a storage medium.
According to an aspect of the present disclosure, there is provided a task testing method, including:
responding to a test request sent by a test demand end, and determining a target cloud mobile phone from locally deployed candidate cloud mobile phones;
controlling the target cloud mobile phone to execute a test task in the test request;
and generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the task testing method of any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the task testing method of any of the embodiments of the present disclosure.
According to the technology disclosed by the invention, a scheme for performing task test by matching the test demand end with the cloud server and the cloud mobile phone deployed by the cloud server is provided, and a new solution is provided for performing task test with low cost and high efficiency.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1A is a flow chart of a task testing method provided in accordance with an embodiment of the present disclosure;
FIG. 1B is a system architecture diagram of a task test provided in accordance with an embodiment of the present disclosure;
FIG. 2 is a flow chart of a task testing method provided in accordance with an embodiment of the present disclosure;
FIG. 3 is a flow chart of a task testing method provided in accordance with an embodiment of the present disclosure;
FIG. 4 is a flow chart of a task testing method provided in accordance with an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a task testing device provided according to an embodiment of the present disclosure;
fig. 6 is a block diagram of an electronic device for implementing a task testing method of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
With the development of computer technology, various artificial intelligence tasks, such as a voice interaction task, a model prediction task, an image recognition task and the like, have been applied to aspects of our lives. The quality of the artificial intelligence task effect directly affects the user experience. At present, when an artificial intelligence task is tested, a test requirement end sends a test request to an intelligent terminal (such as an intelligent sound box, an intelligent television or an intelligent watch) deployed by the artificial intelligence task to be tested, and the intelligent terminal tests the test task deployed therein. Under the condition that the tasks to be tested are more, the number of intelligent terminals for deploying the tasks to be tested is correspondingly increased, so that the testing cost is higher. In addition, the requirement of concurrent testing of a large number of tasks cannot be met due to the influence of the actual number of intelligent terminals. Based on the above, the embodiment provides a scheme for performing task test by matching the test demand end with the cloud server and the cloud mobile phone deployed by the cloud server.
Fig. 1A is a flowchart of a task testing method provided according to an embodiment of the present disclosure. Fig. 1B is a schematic diagram of a system architecture for task testing provided according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for testing artificial intelligence tasks. The whole set of method can be cooperatively executed by a cloud mobile phone end, a cloud server end for deploying the cloud mobile phone and a test demand end. The solution of the embodiment is applied to the cloud server, and the method can be executed by a task testing device configured at the cloud server, and the device can be implemented in a software and/or hardware mode. As shown in fig. 1B, the cloud server 11 in the task testing system 1 of the present embodiment may be a server device that provides a cloud mobile phone service, for example, may be an ARM (Advanced RISC Machine, advanced reduced instruction set processor) server or an X86 server. The cloud server 11 may have at least one cloud handset 12 deployed therein by way of a virtual machine or an available container. The cloud server 11 can control a cloud handset 12 deployed therein.
As shown in fig. 1A-1B, the task testing method provided in this embodiment may include:
s101, responding to a test request sent by a test demand end, and determining a target cloud mobile phone from locally deployed candidate cloud mobile phones.
The test requirement end can be a user end with test task requirement or a service end for providing test service. As shown in fig. 1B, the test requirement end 10 generally includes a front end 110 and a back end 120, where the front end 110 may be a global wide area network (web) front end or an application client for a user to input a test task; the backend 120 may be a central control server, such as a ice cream central control system, for interacting with the cloud server 11, so that the cloud mobile phone 12 deployed in the cloud server 11 performs a test task.
The test request can be a test request which is initiated from the front end to the rear end of the test request end and contains a test task when a user has a test requirement, and the test task can be any task for testing the artificial intelligence algorithm. For example, the method can be a task for testing a voice algorithm in a human-computer interaction scene. The test task at least comprises a test algorithm, if the test task is a voice test task, the test algorithm is a voice algorithm to be tested. Optionally, the test request may further include: test environments for test tasks, test samples or specified test cloud handsets, and the like. The test sample is sample data required for testing the test task, for example, if the test task is a voice test task, the test sample may be voice data of a user. Alternatively, the number of test tasks included in one test request may be one or more.
In this embodiment, the cloud server and all cloud handsets deployed by the cloud server may be used as candidate cloud handsets, and the target cloud handset may be the cloud handset that executes the test request this time. The number of the target cloud mobile phones can be one or more.
Optionally, in this embodiment, after receiving a test request initiated by a user, the test request is forwarded to a cloud server deployed with a cloud mobile phone capable of executing a test task. Optionally, if there are multiple optional cloud servers, the test requirement end may select one or more sending test requests from the multiple optional cloud servers based on the working states of the cloud handsets deployed by the respective cloud servers, the performance of the cloud servers, and the like. And the cloud server receiving the test task can respond to the test request and search a target cloud mobile phone capable of executing the test task in the test request from the locally deployed candidate cloud mobile phones.
Specifically, there are many ways of determining the target cloud mobile phone from the locally deployed candidate cloud mobile phones in this embodiment. For example, if only one candidate cloud mobile phone is deployed locally, the candidate cloud mobile phone can be directly used as the target cloud mobile phone. If the information of the cloud mobile phone (i.e. the test cloud mobile phone) for executing the test task is specified in the test request, if the identifier of the test cloud mobile phone is the identifier of the test cloud mobile phone, the test cloud mobile phone can be searched in the candidate cloud mobile phones deployed locally based on the information of the test cloud mobile phone and used as the target cloud mobile phone. If a plurality of candidate cloud mobile phones are deployed locally and the test cloud mobile phone is not specified in the test request, one or a plurality of candidate cloud mobile phones can be selected randomly to serve as target cloud mobile phones; and checking the idle condition of each candidate cloud mobile phone, and randomly selecting one or more idle candidate cloud mobile phones as target cloud mobile phones. Other manners of determination may also be employed, and this embodiment is not limited thereto.
Optionally, in this embodiment, for each test task in the test request, a corresponding one or more target cloud handsets may be determined for the test task. For example, a target cloud handset may be determined for a test task when the test task is small; when the test task is larger, a plurality of target cloud mobile phones are determined for the test task, and the test task is executed by the cooperation of the plurality of target cloud mobile phones, so that the test efficiency is improved. And determining a plurality of target cloud mobile phones for each test task, and then determining a final test result of the test task based on test data of the plurality of target cloud mobile phones for the same test task so as to maintain the accuracy of the test result.
S102, controlling the target cloud mobile phone to execute the test task in the test request.
Optionally, the specific manner in which the cloud server controls the target cloud mobile phone to execute the test task in the test request may be: firstly, acquiring an identifier of a target cloud mobile phone, such as an internet protocol (Internet Protocol, IP) address, starting the target cloud mobile phone according to the IP address, and then sending a test task in a test request, a test sample associated with the test task and a test program to the target cloud mobile phone so as to control the target cloud mobile phone to call the test program to test the test task based on the test sample, and feeding back obtained test data to a cloud server.
The test tasks are obtained from the test requests, the test samples and the test programs can be obtained from the test requests, and the test samples and the test programs can be obtained from a local or external test sample library and a test program library without limitation. Preferably, in order to improve the test efficiency, the test requirement end can collect different test samples in advance for different types of test tasks and send the test samples to the cloud server in advance, and accordingly, before receiving the test tasks, the cloud service stores the test samples corresponding to the different test tasks locally, and when the test samples need to be obtained, the test samples need to be obtained locally, so that the test sample obtaining efficiency is improved, and further the task test efficiency is improved. Optionally, the test program may be stored in the cloud server in advance in a similar manner, which will not be described in detail.
Optionally, in this embodiment, if the number of the target cloud handsets determined in S101 is multiple, the multiple target cloud handsets may be controlled to execute the related test tasks of the test request simultaneously, so as to improve the test efficiency of the test tasks.
S103, generating a test result according to test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end.
Optionally, in this embodiment, after the target cloud mobile phone finishes executing the test task to obtain the test data, the test task is fed back to the cloud server, and when the cloud server generates the test result based on the test data of the target cloud mobile phone, the test data can be directly used as the test result; the test result can also be coded based on a preset template, and a standard test report is generated as the test result.
When the received test data are multiple groups of test data fed back by multiple target cloud mobile phones, the multiple groups of test data can be fused to obtain a test result. For example, if multiple sets of test data belong to different test tasks or different test stages of the same test task, multiple sets of test data may be integrated to obtain all test tasks or a test result for completing the test tasks; if multiple groups of test data are obtained after each target cloud mobile phone tests all links of the same test task, the differences among the groups of test data can be analyzed at the moment, and a final test result is generated.
Optionally, after the cloud server generates the test result, the test result needs to be fed back to the test demand end, specifically, the test result may be fed back to the back end of the test demand end, and then transmitted to the front end from the back end for display.
According to the technical scheme, after the cloud server responds to the test request sent by the test demand end, the target cloud mobile phone is determined from the locally deployed candidate cloud mobile phones, the target cloud mobile phone is controlled to execute the test task in the test request, and then a test result is generated according to the test data obtained by the target cloud mobile phone executing the test task and is fed back to the test demand end. According to the scheme, the test requirement end and the cloud server and the cloud mobile phone deployed by the cloud server are matched to perform task test, and because a plurality of cloud mobile phones can be deployed in one cloud server, the plurality of cloud mobile phones can concurrently execute test tasks based on one cloud server, the execution cost of the test tasks is reduced, and the task execution efficiency is improved.
Preferably, in this embodiment, if there are a plurality of cloud handsets deployed locally by the cloud server and the test request does not specify a test cloud handset, the method for determining the target cloud handset from the locally deployed candidate cloud handsets may further include: and determining the target cloud mobile phone from the candidate cloud mobile phones according to the historical test success rate of the locally deployed candidate cloud mobile phones. The historical test success rate may refer to the probability of successfully completing a test task when the candidate cloud mobile phone historically executes the test task. Specifically, the cloud server can analyze the historical test success rate of each candidate cloud mobile phone deployed locally, and select one or more candidate cloud mobile phones with high success rate as target cloud mobile phones. According to the embodiment, the cloud mobile phone with high test success rate is selected to execute the test task of the test request, so that the success rate of the test task is further improved.
Preferably, in this embodiment, the communication connection between the cloud server side and the test demand side is preferably established by a remote login manner based on a Secure Shell (SSH) protocol. Correspondingly, feeding back the test result to the test demand end, including: encrypting the test result and feeding the encrypted test result back to the test demand end. Specifically, the test result can be encrypted based on an encryption rule corresponding to the SSH protocol, and the encrypted test result is fed back to the test requirement end; other encryption algorithms may be used to encrypt the test results, as is not limited. The embodiment encrypts the test result and transmits the test result, thereby improving the security and privacy of the test result in the transmission process.
Fig. 2 is a flowchart of a task testing method provided according to an embodiment of the present disclosure. Based on the foregoing embodiments, the embodiments of the present disclosure further explain in detail how to "determine a target cloud mobile phone from locally deployed candidate cloud mobile phones", as shown in fig. 2, a task testing method provided in this embodiment may include:
s201, responding to a test request sent by a test demand end, and determining a test hardware environment and/or a test software environment according to a test task in the test request.
The test hardware environment may refer to a computer physical system, i.e. a hardware facility, formed by a computer and peripheral devices thereof required for completing a test task. Specifically, the environment may be an environment constructed by the sum of physical conditions and physical conditions required for the transmission activity, and may be, for example, a requirement for a processor, a memory, and an external device of the electronic device. The test software environment may refer to a software running environment required to complete a test task, peripheral software required for software running, and the like. For example, it may be the software that runs the corresponding operating system environment.
Optionally, in this embodiment, the cloud server may determine whether the test request includes a test hardware environment and/or a test software environment corresponding to the test task in response to the test request, and if so, directly obtain the test hardware environment and/or the test software environment from the test request; if the test task does not include the test task, the target intelligent terminal actually applied to the test task of the test request can be determined, and then the hardware environment of the target intelligent terminal is used as the test hardware environment, and the software environment of the target intelligent terminal is used as the test software environment. The cloud server can interact with the test requirement end to determine the target intelligent terminal and the software environment and/or the hardware environment thereof.
S202, determining a target cloud mobile phone from locally deployed candidate cloud mobile phones according to the test hardware environment and/or the test software environment.
Optionally, in this embodiment, the cloud server may search at least one candidate cloud mobile phone whose hardware environment satisfies the test hardware environment and/or whose software environment satisfies the test software environment from locally deployed candidate cloud mobile phones, as the target cloud mobile phone.
S203, controlling the target cloud mobile phone to execute the test task in the test request.
S204, generating a test result according to test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end.
According to the technical scheme, after the cloud server responds to the test request sent by the test demand end, the test hardware environment and/or the test software environment are determined, further, candidate cloud mobile phones meeting the test hardware environment and/or the test software environment are selected from the locally deployed candidate cloud mobile phones to serve as target cloud mobile phones, the target cloud mobile phones are controlled to execute the test task in the test request, and further, test results are generated according to the test data fed back by the target cloud mobile phones and fed back to the test demand end. According to the scheme, the target cloud mobile phone for executing the test task is determined by combining the hardware environment and/or the software environment matched with the test task, so that the matching between the target cloud mobile phone and the intelligent terminal for the actual application of the test task is ensured, and the accuracy of the task test result is improved.
Fig. 3 is a flowchart of a task testing method provided according to an embodiment of the present disclosure. Based on the foregoing embodiments, the embodiments of the present disclosure further explain in detail how to "determine a target cloud mobile phone from locally deployed candidate cloud mobile phones in response to a test request sent by a test demand end", as shown in fig. 3, a task test method provided in this embodiment may include:
s301, responding to a test request sent by a test demand end, and determining the demand quantity of the cloud mobile phone.
The required number of cloud mobile phones may refer to the number of cloud mobile phones required for testing a test task in a test request.
Optionally, in this embodiment, the required number of cloud mobile phones may be determined according to the number of test tasks in the test request, for example, if one cloud mobile phone executes one test task, the number of test tasks included in the test request at this time is the required number of cloud mobile phones. The required number of cloud mobile phones can be determined according to the number of test tasks in the test request and the number of test links of each test task, for example, if the test request contains 2 test tasks, the test task 1 comprises 2 test links, the test task 2 comprises 3 test links, then 2 cloud mobile phones are required for completing the test task 1, and 3 cloud mobile phones are required for completing the test task 2, namely, the required number of cloud mobile phones is 5. And may also be determined based on the test requirements in the test request. For example, if at least 3 tests are required to be performed on the test task in the test request to give a final test result, and one cloud mobile phone deployed locally by the cloud service can execute one test task, then 3 target cloud mobile phones can be selected to concurrently execute 3 test tasks for testing efficiency, i.e. the required number of cloud mobile phones is 3. The number of cloud mobile phone demands can also be determined in other ways, and the method is not limited.
S302, determining a target cloud mobile phone from locally deployed candidate cloud mobile phones according to the number of cloud mobile phone requirements.
Optionally, in this embodiment, according to the number of cloud mobile phones required, a target cloud mobile phone corresponding to the number of cloud mobile phones required may be selected from locally deployed candidate cloud mobile phones. For example, if the required number of cloud mobile phones is 2, 2 target cloud mobile phones are selected.
It should be noted that, if the number of locally deployed candidate cloud handsets is greater than or equal to the number of cloud handsets required, the operation of determining the target cloud handset from the locally deployed candidate cloud handsets may be directly performed, where the specific determining manner may be random selection, selection according to an idle condition of the candidate cloud handsets, selection according to a historical test success rate, selection according to a test software link and/or a test hardware environment, and so on. This embodiment is not limited.
Under the condition that the number of the candidate cloud mobile phones deployed locally does not meet the number of the cloud mobile phones required due to the fact that the number of the test tasks in the test request is more, the embodiment can also screen the test tasks according to the historical test frequency of the test tasks in the test request; updating the required quantity of the cloud mobile phone according to the screened test task; and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the updated cloud mobile phone demand quantity. The historical test frequency of the test task may be a ratio of the number of tests of the test task in a historical period to the total number of tests of all tasks in the period. According to the method and the device for testing the cloud mobile phone, a plurality of test tasks can be screened according to the test frequency of each test task in the test request in a historical period, the test task with higher historical test frequency is filtered, the required number of the cloud mobile phones is determined again according to the scheme based on the filtered test task, and the target cloud mobile phones are determined based on the re-determined required number of the cloud mobile phones. When the embodiment has the advantages, repeated testing of the same test task for a plurality of times within a period of time is avoided, so that the situation that other test tasks with lower test frequency cannot be tested is avoided, and the task testing equilibrium is improved under the situation that more test tasks cannot be processed.
Optionally, in this embodiment, the cloud server may further feed the filtered untested task back to the test requirement end, so that the test requirement end may arrange other cloud servers to test the untested task, or the test requirement end may arrange to test the untested task later.
S303, controlling the target cloud mobile phone to execute the test task in the test request.
S304, generating a test result according to test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end.
According to the scheme of the embodiment of the disclosure, the cloud server responds to the test request sent by the test demand end, determines the number of cloud mobile phones required for completing the test task of the test request, further selects a target cloud mobile phone from locally deployed candidate cloud mobile phones based on the number of cloud mobile phones, controls the target cloud mobile phone to execute the test task in the test request, further generates a test result according to test data fed back by the target cloud mobile phone, and feeds the test result back to the test demand end. According to the cloud mobile phone scheduling method and device, the required quantity of the cloud mobile phones is analyzed to determine the target cloud mobile phones, so that the problem that testing tasks cannot be successfully completed due to insufficient quantity of the target cloud mobile phones or cloud mobile phone resource waste is caused by excessive quantity of the target cloud mobile phones is avoided, and the cloud server scheduling accuracy of the cloud mobile phones is improved.
Fig. 4 is a flowchart of a task testing method provided according to an embodiment of the present disclosure. Based on the foregoing embodiments, the embodiments of the present disclosure further explain in detail how to "determine a target cloud mobile phone from locally deployed candidate cloud mobile phones in response to a test request sent by a test demand end", as shown in fig. 4, a task test method provided in this embodiment may include:
s401, responding to a test request sent by a test demand end, and determining a test cloud mobile phone designated by the test demand end.
The test cloud mobile phone can be a cloud mobile phone designated by the test requirement end and used for executing the test task. The specification may be performed by a test request or may be performed by a test request end interacting with the cloud server in advance, which is not limited. Optionally, the test requirement end may designate one or more candidate cloud mobile phones fixed in the cloud server as the test cloud mobile phone, and may further designate different candidate cloud mobile phones as the test cloud mobile phone in combination with different test tasks. This is not limited.
Optionally, in this embodiment, the cloud server responds to a test request sent by the test request end, and determines whether the test request end adds a specified test cloud mobile phone in the test request, if yes, the specified test cloud mobile phone is directly obtained; otherwise, the testing cloud mobile phone of the testing demand end instruction is tested when interacting with the testing demand end before local searching.
S402, if the test cloud mobile phone is in a working state, selecting the cloud mobile phone of the same type as the target cloud mobile phone from the locally deployed candidate cloud mobile phones.
Optionally, in this embodiment, if the test cloud mobile phone is in an idle state, the example may directly use the test cloud mobile phone as the target cloud mobile phone to execute the subsequent operation. If the test cloud mobile phone is in a working state, in order to improve the test efficiency, other cloud mobile phones capable of replacing the test cloud mobile phone can be selected from the locally deployed candidate cloud mobile phones as target cloud mobile phones to execute subsequent operations.
Specifically, in order to meet the specified requirements of the test requirement end as far as possible, when selecting other cloud mobile phones replacing the test cloud mobile phone, the cloud mobile phones of the same type as the target cloud mobile phone can be selected, wherein the same type can be the same deployed hardware environment and/or software environment.
S403, controlling the target cloud mobile phone to execute the test task in the test request.
S404, generating a test result according to test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end.
According to the scheme of the embodiment of the disclosure, if the test cloud mobile phone specified by the test demand end is in a working state, the cloud server selects the cloud mobile phone of the same type as the target cloud mobile phone from the locally deployed candidate cloud mobile phones, controls the target cloud mobile phone to execute the test task in the test request, and further generates a test result according to the test data fed back by the target cloud mobile phone, and feeds the test result back to the test demand end. According to the embodiment, when the test cloud mobile phone specified by the test demand end is in the working state, the target cloud mobile phone which replaces the test cloud mobile phone is selected from other locally deployed cloud mobile phones to execute the test task, the test task does not need to be executed after the test cloud mobile phone works, and the task test efficiency is improved. In addition, the target cloud mobile phone determined by the embodiment and the test cloud mobile phone belong to the same type, so that the target cloud mobile phone for actually executing the test task can meet the appointed requirement of a user as far as possible.
Fig. 5 is a schematic structural diagram of a task testing device according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for testing artificial intelligence tasks. The device can be realized by software and/or hardware and is configured at a cloud server side, and the device can realize the task testing method of any embodiment of the disclosure. As shown in fig. 5, the task testing device includes:
the cloud mobile phone determining module 501 is configured to determine a target cloud mobile phone from locally deployed candidate cloud mobile phones in response to a test request sent by a test demand end;
the cloud mobile phone control module 502 is configured to control the target cloud mobile phone to execute a test task in the test request;
the test result generating module 503 is configured to generate a test result according to test data obtained by the target cloud mobile phone executing the test task;
and the test result sending module 504 is configured to feed back a test result to the test demand end.
According to the technical scheme, after the cloud server responds to the test request sent by the test demand end, the target cloud mobile phone is determined from the locally deployed candidate cloud mobile phones, the target cloud mobile phone is controlled to execute the test task in the test request, and then a test result is generated according to the test data obtained by the target cloud mobile phone executing the test task and is fed back to the test demand end. According to the scheme, the test requirement end and the cloud server and the cloud mobile phone deployed by the cloud server are matched to perform task test, and because a plurality of cloud mobile phones can be deployed in one cloud server, the plurality of cloud mobile phones can concurrently execute test tasks based on one cloud server, the execution cost of the test tasks is reduced, and the task execution efficiency is improved.
Further, the cloud mobile phone determining module 501 is specifically configured to:
determining a test hardware environment and/or a test software environment according to the test task in the test request;
and determining the target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the test hardware environment and/or the test software environment.
Further, the cloud mobile phone determining module 501 is further specifically configured to:
and determining the target cloud mobile phone from the candidate cloud mobile phones according to the historical test success rate of the locally deployed candidate cloud mobile phones.
Further, the cloud mobile phone determining module 501 includes:
the demand quantity determining unit is used for responding to the test request sent by the test demand end and determining the demand quantity of the cloud mobile phone;
the cloud mobile phone determining unit is used for determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the required quantity of the cloud mobile phones.
Further, the cloud mobile phone determining unit is specifically configured to
If the number of the locally deployed candidate cloud mobile phones does not meet the number of the cloud mobile phones required, screening the test tasks according to the historical test frequency of the test tasks in the test request;
updating the required quantity of the cloud mobile phone according to the screened test task;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the updated cloud mobile phone demand quantity.
Further, the cloud mobile phone determining module 501 is further specifically configured to:
responding to a test request sent by a test demand end, and determining a test cloud mobile phone appointed by the test demand end;
if the test cloud mobile phone is in a working state, selecting the cloud mobile phone of the same type as the target cloud mobile phone from the locally deployed candidate cloud mobile phones.
Further, the test result sending module 504 is specifically configured to:
encrypting the test result and feeding the encrypted test result back to the test demand end.
The product can execute the method provided by any embodiment of the disclosure, and has the corresponding functional modules and beneficial effects of executing the method.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related test data all conform to the regulations of related laws and regulations and do not violate the popular regulations of the public order.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
Fig. 6 illustrates a schematic block diagram of an example electronic device 600 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the apparatus 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 may also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other by a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Various components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, mouse, etc.; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the respective methods and processes described above, for example, a task test method. For example, in some embodiments, the task testing method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM 603 and executed by computing unit 601, one or more steps of the task testing method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the task testing method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome. The server may also be a server of a distributed system or a server that incorporates a blockchain.
Artificial intelligence is the discipline of studying the process of making a computer mimic certain mental processes and intelligent behaviors (e.g., learning, reasoning, thinking, planning, etc.) of a person, both hardware-level and software-level techniques. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, and the like; the artificial intelligent software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge graph technology and the like.
Cloud computing (cloud computing) refers to a technical system that a shared physical or virtual resource pool which is elastically extensible is accessed through a network, resources can comprise servers, operating systems, networks, software, applications, storage devices and the like, and resources can be deployed and managed in an on-demand and self-service mode. Through cloud computing technology, high-efficiency and powerful data processing capability can be provided for technical application such as artificial intelligence and blockchain, and model training.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (12)
1. A task testing method comprising:
responding to a test request sent by a test demand end, and determining a target cloud mobile phone from locally deployed candidate cloud mobile phones;
controlling the target cloud mobile phone to execute the test task in the test request;
generating a test result according to test data obtained by the target cloud mobile phone executing the test task, and feeding back the test result to the test demand end;
the determining, in response to the test request sent by the test requirement end, the target cloud mobile phone from the locally deployed candidate cloud mobile phones includes:
responding to a test request sent by a test demand end, and determining the demand quantity of the cloud mobile phone;
determining a target cloud mobile phone from locally deployed candidate cloud mobile phones according to the number of the cloud mobile phone demands;
The determining, according to the number of cloud mobile phone requirements, a target cloud mobile phone from locally deployed candidate cloud mobile phones includes:
if the number of the locally deployed candidate cloud mobile phones does not meet the number of the cloud mobile phone demands, screening the test tasks according to the historical test frequency of the test tasks in the test request;
updating the required quantity of the cloud mobile phone according to the screened test task;
according to the updated cloud mobile phone demand quantity, determining a target cloud mobile phone from locally deployed candidate cloud mobile phones;
the screening the test task according to the historical test frequency of the test task in the test request comprises the following steps:
and screening the plurality of test tasks according to the test frequency of each test task in the test request in a historical period of time, and filtering out the test tasks with higher historical test frequency.
2. The method of claim 1, wherein the determining a target cloud handset from locally deployed candidate cloud handsets comprises:
determining a test hardware environment and/or a test software environment according to the test task in the test request;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the test hardware environment and/or the test software environment.
3. The method of claim 1, wherein the determining a target cloud handset from locally deployed candidate cloud handsets comprises:
and determining a target cloud mobile phone from the candidate cloud mobile phones according to the historical test success rate of the locally deployed candidate cloud mobile phones.
4. The method of claim 1, wherein the determining, in response to the test request sent by the test requirement end, the target cloud handset from the locally deployed candidate cloud handsets comprises:
responding to a test request sent by a test demand end, and determining a test cloud mobile phone designated by the test demand end;
and if the test cloud mobile phone is in a working state, selecting the cloud mobile phones of the same type as the target cloud mobile phone from the locally deployed candidate cloud mobile phones.
5. The method of claim 1, wherein the feeding back the test result to the test requirement end comprises:
encrypting the test result and feeding the encrypted test result back to the test demand end.
6. A task testing device comprising:
the cloud mobile phone determining module is used for responding to a test request sent by the test demand end and determining a target cloud mobile phone from locally deployed candidate cloud mobile phones;
The cloud mobile phone control module is used for controlling the target cloud mobile phone to execute the test task in the test request;
the test result generation module is used for generating a test result according to test data obtained by the target cloud mobile phone executing the test task;
the test result sending module is used for feeding back the test result to the test demand end;
wherein, cloud cell phone determination module includes:
the demand quantity determining unit is used for responding to the test request sent by the test demand end and determining the demand quantity of the cloud mobile phone;
the cloud mobile phone determining unit is used for determining a target cloud mobile phone from locally deployed candidate cloud mobile phones according to the required quantity of the cloud mobile phones;
wherein the cloud mobile phone determining unit is specifically configured to
If the number of the locally deployed candidate cloud mobile phones does not meet the number of the cloud mobile phone demands, screening the test tasks according to the historical test frequency of the test tasks in the test request;
updating the required quantity of the cloud mobile phone according to the screened test task;
according to the updated cloud mobile phone demand quantity, determining a target cloud mobile phone from locally deployed candidate cloud mobile phones;
the screening the test task according to the historical test frequency of the test task in the test request comprises the following steps:
And screening the plurality of test tasks according to the test frequency of each test task in the test request in a historical period of time, and filtering out the test tasks with higher historical test frequency.
7. The apparatus of claim 6, wherein the cloud handset determination module is specifically configured to:
determining a test hardware environment and/or a test software environment according to the test task in the test request;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the test hardware environment and/or the test software environment.
8. The apparatus of claim 6, wherein the cloud handset determination module is further specifically configured to:
and determining a target cloud mobile phone from the candidate cloud mobile phones according to the historical test success rate of the locally deployed candidate cloud mobile phones.
9. The apparatus of claim 6, wherein the cloud handset determination module is further specifically configured to:
responding to a test request sent by a test demand end, and determining a test cloud mobile phone designated by the test demand end;
and if the test cloud mobile phone is in a working state, selecting the cloud mobile phones of the same type as the target cloud mobile phone from the locally deployed candidate cloud mobile phones.
10. The apparatus of claim 6, wherein the test result sending module is specifically configured to:
encrypting the test result and feeding the encrypted test result back to the test demand end.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the task testing method of any one of claims 1-5.
12. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the task testing method of any one of claims 1-5.
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| CN115314541A (en) * | 2022-10-12 | 2022-11-08 | 阿里巴巴（中国）有限公司 | Remote debugging method, communication system, electronic device, and storage medium |
| CN116208622B (en) * | 2023-04-28 | 2023-07-07 | 江苏北弓智能科技有限公司 | Batch cloud mobile phone synchronous operation method |
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