CN114157701A - Task testing method, device, equipment and storage medium - Google Patents
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Abstract
The disclosure provides a task testing method and device, electronic equipment and a storage medium, and relates to the technical field of cloud computing, in particular 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 the test result back to the test demand side. The scheme that the test demand end is matched with the cloud server and the cloud mobile phone arranged by the cloud server to perform task testing is provided, and a new solution is provided for performing task testing 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, equipment and storage medium.
Background
With the development of computer technology, various artificial intelligence tasks, such as voice interaction tasks, model prediction tasks, image recognition tasks and the like, have been applied to aspects of our lives. The quality of the artificial intelligence task effect directly influences the user experience. Therefore, testing of human intelligence tasks is critical.
Disclosure of Invention
The disclosure provides a task testing method, a task testing device, an electronic device and a storage medium.
According to an aspect of the present disclosure, there is provided a task testing method, the 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 the test result back to the test demand side.
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 content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of task testing of any 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 having stored thereon computer instructions for causing a computer to perform the method of task testing of any of the embodiments of the present disclosure.
According to the technology disclosed by the invention, a scheme for performing task testing by matching a test demand end with a cloud server and a cloud mobile phone deployed by the cloud server is provided, and a new solution is provided for performing task testing with low cost and high efficiency.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide 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 according to an embodiment of the present disclosure;
FIG. 1B is a system architecture diagram of task testing 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 structural diagram of a task testing apparatus provided in accordance with 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 with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those 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 voice interaction tasks, model prediction tasks, image recognition tasks and the like, have been applied to aspects of our lives. The quality of the artificial intelligence task effect directly influences the user experience. At present, the scheme adopted when testing the artificial intelligence task is that a test demand 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 deployed test task. Under the condition of more tasks to be tested, the number of intelligent terminals for deploying the tasks to be tested is also increased correspondingly, so that the testing cost is higher. In addition, the requirements of concurrent testing of a large number of tasks cannot be met due to the influence of the actual number of the intelligent terminals. Based on this, the embodiment provides a scheme for performing task testing by matching the test demand side 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 according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for testing the artificial intelligence task. The whole set of method can be executed by the cloud mobile phone end, the cloud server end for deploying the cloud mobile phone and the test demand end in a matched mode. 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 manner. As shown in fig. 1B, the cloud server 11 in the system 1 for task testing in this embodiment may be a server device providing cloud mobile phone services, such as an ARM (Advanced RISC Machine) server or an X86 server. The cloud server 11 may be deployed with at least one cloud handset 12 in the form of a virtual machine or an available container. The cloud server 11 may control the cloud handsets 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 may be a user end having a requirement for a test task, or a service end providing a test service. As shown in fig. 1B, the testing client 10 generally includes two parts, 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, and may be used for a user to input a testing task; the back end 120 may be a central control server, such as a central control system in ice flower, and is configured to interact with the cloud server 11, so that the cloud mobile phone 12 deployed in the cloud server 11 executes a test task.
The test request can be a test request which is initiated by the front end of the test demand end to the back end and contains a test task when a user has a test demand, 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 speech 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: testing environment of testing task, testing sample or appointed testing cloud cell phone, etc. 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 the 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 the cloud handsets deployed by the cloud server can be candidate cloud handsets, and the target cloud handset can be a cloud handset executing the test request. 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 requirement end forwards the test request 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 demand side may select one or more test requests from the multiple optional cloud servers based on the working state of the cloud phone deployed by each cloud server, the performance of the cloud server, and the like. The cloud server receiving the test task responds to the test request, and a target cloud mobile phone capable of executing the test task in the test request is searched from the locally deployed candidate cloud mobile phones.
Specifically, there are many ways to determine 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 locally deployed, the candidate cloud mobile phone may be directly used as the target cloud mobile phone. If the test request specifies information of the cloud mobile phone (i.e., the test cloud mobile phone) executing the test task, such as an identifier of the test cloud mobile phone, the test cloud mobile phone can be searched for in the locally deployed candidate cloud mobile phones based on the information of the test cloud mobile phone and is used as the target cloud mobile phone. If a plurality of candidate cloud mobile phones are locally deployed and no test cloud mobile phone is specified in the test request, one or more candidate cloud mobile phones can be randomly selected as a target cloud mobile phone; the idle condition of each candidate cloud mobile phone can be checked, one or more idle candidate cloud mobile phones can be randomly selected to serve as the target cloud mobile phone, and the like. Other ways may also be used for determining, which is not limited in this embodiment.
Optionally, in this embodiment, for each test task in the test request, the corresponding one or more target cloud handsets may be determined. For example, when a test task is small, a target cloud mobile phone can be determined for the test task; when the test task is large, a plurality of target cloud mobile phones are determined for the test task, and the test task is executed by cooperation of the target cloud mobile phones, so that the test efficiency is improved. The method can also be used for determining a plurality of target cloud mobile phones for each test task, and then determining the final test result of the test task based on the test data of the target cloud mobile phones on the same test task so as to keep the accuracy of the test result.
And S102, controlling the target cloud mobile phone to execute the test task in the test request.
Optionally, a specific manner in which the cloud server controls the target cloud mobile phone to execute the test task in the test request may be: the method comprises the steps of firstly obtaining an identification of a target cloud mobile phone, such as an Internet Protocol (IP) address, starting the target cloud mobile phone according to the IP address, then sending a test task in a test request, a test sample related to the test task and a test program to the target cloud mobile phone so as to control the target cloud mobile phone to test the test task based on the test sample by calling the test program, and feeding obtained test data back to a cloud server.
The test task is obtained from the test request, the test sample and the test program can be obtained from the test request, and the test task can also be obtained from a local or external test sample library and a test program library without limitation. Preferably, in order to improve the testing efficiency, the testing demand side can collect different testing samples aiming at different types of testing tasks in advance and send the testing samples to the cloud server in advance, correspondingly, before the cloud server receives the testing tasks, the testing samples corresponding to the different testing tasks are stored locally, and when the testing samples need to be obtained, the testing samples can be directly obtained locally, so that the testing sample obtaining efficiency is improved, and further the task testing efficiency is improved. Optionally, the test program may also be pre-stored in the cloud server locally in a similar manner, which is not described herein again.
Optionally, in this embodiment, if a plurality of target cloud handsets are determined in S101, the target cloud handsets may be concurrently controlled to execute the relevant test tasks of the test request at the same time, so as to improve the test efficiency of the test tasks.
S103, generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding the test result back to the test demand side.
Optionally, in this embodiment, after the target cloud mobile phone performs the test task to obtain the test data, the test task is fed back to the cloud server, and the cloud server may directly use the test data as the test result when generating the test result based on the test data of the target cloud mobile phone; the test result can also be encoded 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 groups of test data belong to different test tasks or different test stages of the same test task, the multiple groups of test data can be integrated to obtain all test tasks or a test result for completing the test task; if the multiple groups of test data are obtained after all links of the same test task are tested by each target cloud mobile phone, the difference between the groups of test data can be analyzed, 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 first, and then the test result is transmitted from the back end to the front end for display.
According to the technical scheme of the embodiment, 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 the test result is generated according to the test data obtained by the target cloud mobile phone executing the test task and fed back to the test demand end. According to the scheme, the test demand end is matched with the cloud server and the cloud mobile phones deployed by the cloud server to perform task testing, and as a plurality of cloud mobile phones can be deployed in one cloud server, the plurality of cloud mobile phones can concurrently execute the test tasks based on one cloud server, so that 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 locally deployed by the cloud server and the test cloud handset is not specified in the test request, the determining the target cloud handset from the locally deployed candidate cloud handsets may further include: 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. The historical test success rate may be a probability of successfully completing a test task when the candidate cloud mobile phone historically executes the test task. Specifically, the cloud server may analyze a historical test success rate of each candidate cloud mobile phone locally deployed by the cloud server, and select one or more candidate cloud mobile phones with a high success rate as the target cloud mobile phone. 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 cloud server and the test requirement terminal preferably establish a communication connection through a remote login manner based on a Secure Shell (SSH) protocol. Correspondingly, the step of feeding back the test result to the test demand side includes: and encrypting the test result, and feeding back the encrypted test result to the test demand end. Specifically, the test result may be encrypted based on an encryption rule corresponding to the SSH protocol, and the encrypted test result is fed back to the test requirement side; other encryption algorithms may be used to encrypt the test result, which is not limited in this regard. The embodiment encrypts the test result and transmits the encrypted test result, so that the safety and the privacy of the test result in the transmission process are improved.
Fig. 2 is a flowchart of a task testing method provided according to an embodiment of the present disclosure. On the basis of the above embodiments, the embodiment of the present disclosure further explains in detail how to "determine a target cloud mobile phone from locally deployed candidate cloud mobile phones", as shown in fig. 2, the task testing method provided by 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, which is composed of a computer and peripheral devices thereof required for completing a test task. Specifically, the environment may be constructed by a sum of physical conditions and tangible conditions necessary for the propagation of the 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 for completing a test task, peripheral software required for software running, and the like. For example, it may be the software running the corresponding operating system environment.
Optionally, in this embodiment, the cloud server responds to the test request, and may determine whether the test request includes a test hardware environment and/or a test software environment corresponding to the test task, and if so, directly obtain the test hardware environment and/or the test software environment from the test request; if the test request does not contain the hardware environment, a target intelligent terminal actually applied by the test task of the test request can be determined, 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 demand end to determine the target intelligent terminal and the software environment and/or the hardware environment of the target intelligent terminal.
And S202, 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.
Optionally, in this embodiment, the cloud server may search at least one candidate cloud mobile phone whose hardware environment meets the test hardware environment and/or whose software environment meets the test software environment from the locally deployed candidate cloud mobile phones, as the target cloud mobile phone.
And S203, controlling the target cloud mobile phone to execute the test task in the test request.
And S204, generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding the test result back to the test demand side.
According to the technical scheme of the embodiment, 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, then the 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 as the target cloud mobile phones, the target cloud mobile phones are controlled to execute the test tasks in the test request, and then the test result is 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 executing the test task is determined by combining the hardware environment and/or the software environment which are adapted to the test task, the matching between the target cloud mobile phone and the intelligent terminal which is actually applied to the test task is guaranteed, 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. On the basis of the above embodiments, the embodiment of the present disclosure further explains 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 requirement end", and as shown in fig. 3, the task testing method provided by the embodiment may include:
s301, responding to a test request sent by a test demand end, and determining the quantity of the cloud mobile phone demands.
The required number of the cloud mobile phones may be the number of the cloud mobile phones required for testing the test tasks in the test request.
Optionally, in this embodiment, the required number of the cloud mobile phones may be determined according to the number of the test tasks in the test request, for example, if one cloud mobile phone executes one test task, the number of the test tasks included in the test request at this time is the required number of the cloud mobile phone. For example, if the test request includes 2 test tasks, the test task 1 includes 2 test links, and the test task 2 includes 3 test links, then 2 cloud phones are needed to complete the test task 1, and 3 cloud phones are needed to complete the test task 2, that is, the number of the required cloud phones is 5. But also according to the test requirements in the test request. For example, if the test request requires that at least 3 tests are performed on the test task to obtain a final test result, and one cloud mobile phone locally deployed by the cloud service can execute one test task, then 3 target cloud mobile phones may be selected to concurrently execute the test tasks for 3 times for the purpose of testing efficiency, that is, the required number of the cloud mobile phones is 3. The required number of the cloud mobile phones can be determined in other ways, which is not limited.
S302, determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the required quantity of the cloud mobile phones.
Optionally, in this embodiment, according to the required number of cloud mobile phones, a target cloud mobile phone corresponding to the required number of cloud mobile phones is selected from candidate cloud mobile phones deployed locally. For example, if the required number of cloud handsets is 2, 2 target cloud handsets are selected.
It should be noted that, if the number of the locally deployed candidate cloud handsets is greater than or equal to the required number of the cloud handsets, the operation of determining the target cloud handset from the locally deployed candidate cloud handsets may be directly performed, and the specific determination 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 the like. This embodiment is not limited to this.
Under the condition that the number of the candidate cloud mobile phones deployed locally does not meet the required number of the cloud mobile phones due to more test tasks in the test request, the test tasks can be screened 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 tasks; and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the updated required quantity of the cloud mobile phones. 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 of time to the total number of tests of all tasks in the period of time. According to the method and the device, the plurality of test tasks can be screened according to the test frequency of each test task in the test request within a historical period of time, the test tasks with higher historical test frequency are filtered, the cloud mobile phone demand quantity is determined again according to the scheme based on the filtered test tasks, and the target cloud mobile phone is determined based on the re-determined cloud mobile phone demand quantity. When the advantage that this embodiment set up like this, avoid a period of time within a lot of to same test task repeated test, lead to the unable circumstances of testing of the test task that other test frequencies are lower to appear, under the more circumstances of not coming of processing of test task, improved task test's equilibrium.
Optionally, in this embodiment, the cloud server may further feed back the untested tasks that are screened out by the cloud server to the test requirement end, so that the test requirement end arranges another cloud server to test the untested tasks, or so that the test requirement end arranges the untested tasks for testing at a later time.
And S303, controlling the target cloud mobile phone to execute the test task in the test request.
S304, generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding the test result back to the test demand side.
According to the scheme of the embodiment, the cloud server responds to the test request sent by the test demand end, the number of the cloud mobile phones required by the test task of the test request is determined, then the target cloud mobile phone is selected from the locally deployed candidate cloud mobile phones based on the number of the cloud mobile phones, the target cloud mobile phone is controlled to execute the test task in the test request, and then the test result is generated according to the test data fed back by the target cloud mobile phone and fed back to the test demand end. According to the cloud mobile phone scheduling method and device, the required number of the cloud mobile phones is analyzed to determine the target cloud mobile phones, the situation that the testing task cannot be completed smoothly due to the fact that the number of the target cloud mobile phones is insufficient, or the situation that cloud mobile phone resources are wasted due to the fact that the number of the target cloud mobile phones is too large is avoided, and the accuracy of the cloud server scheduling 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. On the basis of the above embodiments, the embodiment of the present disclosure further explains 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 requirement end", and as shown in fig. 4, the task testing method provided by the embodiment may include:
s401, responding to a test request sent by a test demand end, and determining a test cloud mobile phone appointed by the test demand end.
The test cloud mobile phone can be a cloud mobile phone which is specified by the test demand end and executes the test task. The specification may be performed by a test request, or may be performed by the test requirement side interacting with the cloud server in advance, which is not limited herein. Optionally, the test demand side may designate one or more candidate cloud handsets fixed in the cloud server as the test cloud handsets, and may also designate different candidate cloud handsets as the test cloud handsets by combining different test tasks. This is not limitative.
Optionally, in this embodiment, the cloud server responds to the test request sent by the test demand end, and determines whether the test demand end adds a specified test cloud mobile phone in the test request, and if so, directly obtains the specified test cloud mobile phone; otherwise, when interaction with the test demand end is carried out before local search, the test cloud mobile phone of the test demand end instruction is tested.
S402, if the test cloud mobile phones are in a working state, the same type of cloud mobile phones of the test cloud mobile phones are selected as target cloud mobile phones from the locally deployed candidate cloud mobile phones.
Optionally, in this embodiment, if the test cloud mobile phone is in the idle state, the example may directly use the test cloud mobile phone as the target cloud mobile phone to perform 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 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 demand side as much as possible, when other cloud cell phones are selected to replace the test cloud cell phone, the same type of cloud cell phones of the test cloud cell phone may be selected as the target cloud cell phone, where the same type may be the same deployed hardware environment and/or software environment.
And S403, controlling the target cloud mobile phone to execute the test task in the test request.
S404, generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding the test result back to the test demand side.
According to the scheme of the embodiment, if the test cloud mobile phones specified by the test demand end are in a working state, the cloud server selects the same type of cloud mobile phones of the test cloud mobile phones as the target cloud mobile phones from the locally deployed candidate cloud mobile phones, controls the target cloud mobile phones to execute the test tasks in the test requests, generates the test results according to the test data fed back by the target cloud mobile phones, and feeds back the test results to the test demand end. According to the embodiment, when the test cloud mobile phone specified by the test demand end is in a working state, the target cloud mobile phone replacing the test cloud mobile phone is selected from other locally deployed cloud mobile phones to execute the test task, the test cloud mobile phone does not need to be executed after working, 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 which actually executes the test task can meet the specified requirements of the user as much 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 the artificial intelligence task. The device can be realized by adopting software and/or hardware and configured at a cloud server end, and the device can realize the task testing method of any embodiment of the disclosure. As shown in fig. 5, the task testing apparatus 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 side;
a cloud mobile phone control module 502, configured to control the target cloud mobile phone to execute a test task in the test request;
the test result generation module 503 is configured to generate a test result according to test data obtained by the target cloud mobile phone executing the test task;
the test result sending module 504 is configured to feed back the test result to the test requiring end.
According to the technical scheme of the embodiment, 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 the test result is generated according to the test data obtained by the target cloud mobile phone executing the test task and fed back to the test demand end. According to the scheme, the test demand end is matched with the cloud server and the cloud mobile phones deployed by the cloud server to perform task testing, and as a plurality of cloud mobile phones can be deployed in one cloud server, the plurality of cloud mobile phones can concurrently execute the test tasks based on one cloud server, so that 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 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.
Further, the cloud mobile phone determining module 501 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.
Further, the cloud phone determining module 501 includes:
the demand quantity determining unit is used for responding to a test request sent by a test demand end and determining the demand quantity of the cloud mobile phone;
and 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 candidate cloud mobile phones deployed locally does not meet the required number of the cloud mobile phones, screening the test tasks according to the historical test frequency of the test tasks in the test requests;
updating the required quantity of the cloud mobile phone according to the screened test tasks;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the updated required quantity of the cloud mobile phones.
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 designated by the test demand end;
and if the test cloud mobile phone is in a working state, selecting the same type of cloud mobile phone of the test cloud mobile phone as a target cloud mobile phone from the locally deployed candidate cloud mobile phones.
Further, the test result sending module 504 is specifically configured to:
and encrypting the test result, and feeding back the encrypted test result to the test demand end.
The product can execute the method provided by any embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related test data all accord with the regulations of related laws and regulations, and do not violate the good custom of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can 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 phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples 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, which 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 can also be stored. The calculation unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, or the like; 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 the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation 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 in 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 the RAM 603 and executed by the 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 circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a 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 that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes 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 codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. 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. A 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 a pointing device (e.g., a mouse or a 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 can 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, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a 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 back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. 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 host and VPS service are overcome. The server may also be a server of a distributed system, or a server incorporating a blockchain.
Artificial intelligence is the subject of research that makes computers simulate some human mental processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both at the hardware level and at the software level. 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 intelligence 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 map technology and the like.
Cloud computing (cloud computing) refers to a technology system that accesses a flexibly extensible shared physical or virtual resource pool through a network, where resources may include servers, operating systems, networks, software, applications, storage devices, and the like, and may be deployed and managed in a self-service manner as needed. Through the cloud computing technology, high-efficiency and strong data processing capacity can be provided for technical application and model training of artificial intelligence, block chains and the like.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (17)
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;
and generating a test result according to the test data obtained by the target cloud mobile phone executing the test task, and feeding the test result back to the test demand end.
2. The method of claim 1, wherein the determining a target cloud handset from the 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 the 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 a target cloud handset from the locally deployed candidate cloud handsets in response to a test request sent by a test demander comprises:
responding to a test request sent by a test demand end, and determining the quantity of the cloud mobile phone demands;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the required quantity of the cloud mobile phones.
5. The method of claim 4, wherein the determining a target cloud handset from the locally deployed candidate cloud handsets according to the cloud handset demand number comprises:
if the number of the candidate cloud mobile phones deployed locally does not meet the required number of the cloud mobile phones, screening the test tasks according to the historical test frequency of the test tasks in the test requests;
updating the required quantity of the cloud mobile phone according to the screened test tasks;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the updated required quantity of the cloud mobile phones.
6. The method of claim 1, wherein the determining a target cloud handset from the locally deployed candidate cloud handsets in response to a test request sent by a test demander comprises:
responding to a test request sent by a test demand end, and determining a test cloud mobile phone appointed by the test demand end;
and if the test cloud mobile phones are in a working state, selecting the same type of cloud mobile phones of the test cloud mobile phones as target cloud mobile phones from locally deployed candidate cloud mobile phones.
7. The method of claim 1, wherein the feeding back the test result to the test demand side comprises:
and encrypting the test result, and feeding back the encrypted test result to the test demand end.
8. A task testing device comprising:
the cloud mobile phone determining module is used for 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 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;
and the test result sending module is used for feeding back the test result to the test requirement end.
9. The apparatus of claim 8, 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.
10. The apparatus of claim 8, 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.
11. The apparatus of claim 8, wherein the cloud handset determination module comprises:
the demand quantity determining unit is used for responding to a test request sent by a test demand end and determining the demand quantity of the cloud mobile phone;
and 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.
12. The apparatus of claim 11, wherein the cloud handset determination unit is specifically configured to
If the number of the candidate cloud mobile phones deployed locally does not meet the required number of the cloud mobile phones, screening the test tasks according to the historical test frequency of the test tasks in the test requests;
updating the required quantity of the cloud mobile phone according to the screened test tasks;
and determining a target cloud mobile phone from the locally deployed candidate cloud mobile phones according to the updated required quantity of the cloud mobile phones.
13. The apparatus of claim 8, 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 appointed by the test demand end;
and if the test cloud mobile phones are in a working state, selecting the same type of cloud mobile phones of the test cloud mobile phones as target cloud mobile phones from locally deployed candidate cloud mobile phones.
14. The apparatus according to claim 8, wherein the test result sending module is specifically configured to:
and encrypting the test result, and feeding back the encrypted test result to the test demand end.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
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 1-7.
16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the task testing method of any of claims 1-7.
17. A computer program product comprising a computer program which, when executed by a processor, implements a method of task testing according to any one of claims 1-7.
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