CN116187014A

CN116187014A - Heterogeneous-based parameter template generation method and device

Info

Publication number: CN116187014A
Application number: CN202211711059.2A
Authority: CN
Inventors: 伍航; 张忠华; 高勇钧; 孙达文
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-12-29
Filing date: 2022-12-29
Publication date: 2023-05-30

Abstract

The disclosure provides a heterogeneous-based parameter template generation method and a heterogeneous-based parameter template generation device, relates to the technical field of artificial intelligence, and particularly relates to the technical field of automatic driving and data processing. The method comprises the following steps: carrying out structuring treatment on the data source to generate a parameter pool comprising multiple types of parameter sets; selecting partial parameter items from each type of parameter set according to the historical test task of the test service aiming at each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set; and acquiring a test task of the template management object aiming at the test service, updating the basic parameter template according to the test task, and generating a target parameter template matched with the test task. The method and the device can flexibly meet the test requirements of different automatic driving modules and the iteration test requirements of the service extension period, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test and avoid time waste.

Description

Heterogeneous-based parameter template generation method and device

Technical Field

The present disclosure relates to the field of artificial intelligence, and in particular, to the field of autopilot and data processing techniques.

Background

The automatic driving simulation test is a low-cost and high-efficiency test means except the automatic driving drive test, in the related technology, the effectiveness of algorithm verification can be improved by continuously improving the simulation test capability, but because the automatic driving simulation test process involves the simulation test requirement of each algorithm module, the massive parameter verification requirement is derived, the module parameter types of the automatic driving simulation test are numerous (such as map parameter types, perception parameter types, PNC parameter types, decision parameter types, planning parameter types, resource configuration parameter types and the like), and the parameter quantity expansion can lead to the problems of high learning cost and great use difficulty of test users.

Therefore, how to flexibly meet the test requirements of different autopilot modules, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test, avoid wasting time, and become one of important research directions.

Disclosure of Invention

The disclosure provides a heterogeneous-based parameter template generation method and a heterogeneous-based parameter template generation device.

According to an aspect of the present disclosure, there is provided a heterogeneous-based parameter template generation method, including:

carrying out structuring treatment on the data source to generate a parameter pool comprising multiple types of parameter sets;

selecting partial parameter items from each type of parameter set according to the historical test task of the test service aiming at each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set;

and acquiring a test task of the template management object aiming at the test service, updating the basic parameter template according to the test task, and generating a target parameter template matched with the test task.

The method and the device can flexibly meet the test requirements of different automatic driving modules and the iteration test requirements of the service extension period, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test and avoid time waste.

According to another aspect of the present disclosure, there is provided a heterogeneous-based parameter template generating apparatus, including:

the first generation module is used for carrying out structuring processing on the data source and generating a parameter pool comprising multiple types of parameter sets;

the second generation module is used for selecting partial parameter items from each type of parameter set according to the historical test task of the test service aiming at each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set;

and the third generation module is used for acquiring a test task of the template management object aiming at the test service, updating the basic parameter template according to the test task and generating a target parameter template matched with the test task.

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 liquid crystal display device comprises a liquid crystal display device,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a heterogeneous parameter template generation method of an embodiment of the first aspect 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 a heterogeneous parameter template generation method of an embodiment of the first aspect of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a heterogeneous parameter template generation method of an embodiment of the first aspect of the present disclosure.

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. 1 is a flow chart of a heterogeneous based parameter template generation method according to one embodiment of the present disclosure;

FIG. 2 is a flow chart of a heterogeneous based parameter template generation method according to one embodiment of the present disclosure;

FIG. 3 is a flow chart of a heterogeneous based parameter template generation method according to one embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a heterogeneous based parametric template generation method according to one embodiment of the present disclosure;

FIG. 5 is a block diagram of a heterogeneous based parameter template generation apparatus according to one embodiment of the present disclosure;

fig. 6 is a block diagram of an electronic device for implementing a heterogeneous based parameter template generation 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.

The embodiment of the disclosure relates to the technical field of artificial intelligence such as computer vision, deep learning and the like.

Artificial intelligence (Artificial Intelligence), english is abbreviated AI. It is a new technical science for researching, developing theory, method, technology and application system for simulating, extending and expanding human intelligence.

Autopilot generally refers to an autopilot system that employs advanced communication, computer, network and control techniques to achieve real-time, continuous control of a train. The method adopts modern communication means, directly faces the train, can realize bidirectional data communication between the train and the ground, has high transmission rate and large information quantity, and can timely obtain the exact position of the front train by the follow-up train and the control center, so that the operation management is more flexible, the control is more effective, and the method is more suitable for the automatic driving requirement of the train.

Data processing is a fundamental link of system engineering and automatic control. Data processing extends throughout various areas of social production and social life. The development of data processing technology and the breadth and depth of application thereof greatly influence the progress of human society development. Data (Data) is a representation of facts, concepts, or instructions that may be processed by manual or automated means. After the data is interpreted and given a certain meaning, the data becomes information. Data processing (data processing) is the collection, storage, retrieval, processing, transformation, and transmission of data. The basic purpose of data processing is to extract and derive data that is valuable and meaningful to some particular person from a large, possibly unorganized, unintelligible, data.

The isomerism-based parameter template generation method and apparatus of the present disclosure are described below with reference to the accompanying drawings.

FIG. 1 is a flow chart of a heterogeneous based parameter template generation method according to one embodiment of the present disclosure, as shown in FIG. 1, including the steps of:

s101, carrying out structuring processing on the data source to generate a parameter pool comprising multiple types of parameter sets.

In the embodiment of the disclosure, heterogeneous parameter templates represent different types of parameter templates, the data sources are data sources of automatic driving simulation tests, the data sources can be derived from the test requirements of all simulation modules, and the data sources can be split into high-precision map data sources, test scene data sources, algorithm data sources and simulation operation resource data sources according to common test items. And carrying out structuring treatment on the multi-class data sources to generate multi-class parameter sets, namely parameter pools.

In some implementations, the map class parameter set is generated by performing structured indexing processing on the high-precision map class data source, and may include parameter items such as identification ID, version number, area name, release time, test mark, map application type, road network mileage, and the like.

In some implementations, the test scene data source is derived from an actual drive test, and after the test scene data source is structured, a test scene parameter set is generated, which may include parameter items such as an area where a scene is located, a duration, a start-stop time stamp of the scene, and a map version used by the scene.

In some implementations, by performing structured parameter indexing on the algorithm-class data source, an algorithm-class parameter set is generated, which may include parameter items in various directions such as automatic driving (Planning and Control, PNC), perception, decision, planning, etc., and the algorithm parameters have a strong business background, so that the algorithm parameters need to have business-configurable capabilities.

In some implementations, by performing a structured process on a simulation run resource class data source, a simulation run resource class parameter set is generated, where the simulation run resource class parameter set mainly includes available parameter items of a computing cluster such as a central processing unit (central processing unit, CPU), a memory MEM, and the like that are available when supporting an algorithm test. And the dynamic allocation and scheduling of the test resources are completed through parameter configurability.

The structuring process refers to a process performed on collected big data before analysis mining, and particularly to unstructured data such as text types, and the structuring process is a precondition of analysis and calculation.

S102, selecting partial parameter items from each type of parameter set according to the historical test task of the test service aiming at each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set.

Alternatively, the test services may include a map quality inspection test service, a perception verification test service, a PNC verification test service, a scene quality inspection test service, and the like.

In some implementations, according to the historical test tasks of each type of test service, partial parameter items are selected from each type of parameter set, for example, partial parameter items are selected from a map type parameter set, a map type parameter subset is obtained, partial parameter items are selected from an algorithm type parameter set, an algorithm type parameter subset is obtained, partial parameter items are selected from a test scene type parameter set, a test scene type parameter subset is obtained, partial parameter items are selected from a simulation operation resource type parameter set, and a simulation operation resource type parameter subset is obtained.

By combining different parameter types and parameter items, a basic parameter template based on a certain application purpose is generated. The basic parameter templates may include one or more parameter items in a map class parameter subset, an algorithm class parameter subset, a test scene class parameter subset, and a simulation run resource class parameter subset.

For example, the basic parameter templates may include parameter items such as area name, release time, test mark, map application type, road network mileage, etc. in the map class parameter subset, and parameter items such as area, duration, start-stop time stamp, etc. of the scene in the test scene class parameter subset.

The algorithm class parameter subset uses the algorithm module name, version number and the like as main parameters, aligns the drive test capability, and supports iteration of a new algorithm input by taking the directory address as a parameter; the map type parameter subset takes parameters such as an area, a version, a release state and the like of a test scene as input; the test scene type parameter subset takes semantic scene type parameters as input; the simulation running resource class parameter subset is mainly based on the allocation parameters of the computing resources.

S103, obtaining a test task of the template management object aiming at the test service, updating the basic parameter template according to the test task, and generating a target parameter template matched with the test task.

Alternatively, the template management object may be a developer of the simulation test, or may be a user using a parameter template, which is not limited in this application. In some implementations, the template management object may be a federated template management object, such as a community user; in some implementations, the template management object may be an individual user, which is not limited by the present disclosure.

In the embodiment of the disclosure, the basic parameter template of the test service is a template generated based on the characteristics of the historical test task, and includes parameters of the test task demand direction extracted from the parameter pool.

In some implementations, the target parameter template is updated by the template management object and the updated target parameter template is verified. After verification is passed, an updated target parameter template is issued to the computing cluster bound by the template management object so as to perform simulation test, for example, the updated target parameter template is sent to an external device (such as an external computer) so as to support the external device to perform simulation test according to parameter items in the target parameter template.

In the embodiment of the disclosure, a data source is structured to generate a parameter pool comprising multiple types of parameter sets; selecting partial parameter items from each type of parameter set according to the historical test task of the test service aiming at each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set; and acquiring a test task of the template management object aiming at the test service, updating the basic parameter template according to the test task, and generating a target parameter template matched with the test task. The method and the device can flexibly meet the test requirements of different automatic driving modules and the iteration test requirements of the service extension period, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test and avoid time waste.

FIG. 2 is a flow chart of a heterogeneous based parameter template generation method according to one embodiment of the present disclosure, as shown in FIG. 2, including the steps of:

s201, structuring the data source to generate a parameter pool comprising multiple types of parameter sets.

S202, selecting partial parameter items from each type of parameter set according to the historical test task of the test service aiming at each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set.

S203, a test task of the template management object aiming at the test service is obtained.

The description of step S201 to step S203 may be referred to the content of the above embodiment, and will not be repeated here.

S204, analyzing the test task to obtain parameter items to be updated.

In some implementations, the test task is parsed, the test task includes a parameter item identifier, and a parameter item to be updated can be determined according to the parameter item identifier.

In some implementations, the test task is parsed, a description text corresponding to the test task is obtained, the description text is matched with the parameter items in the parameter pool, so that the similarity between the description text and each parameter item is obtained, and the parameter item with the similarity greater than the similarity threshold value is determined as the parameter item to be updated.

S205, obtaining parameter items to be updated from the multi-class parameter set.

And acquiring parameter items to be updated from the multi-class parameter set of the parameter pool. Optionally, the parameter items to be updated may be one or more parameter items in a map class parameter set, an algorithm class parameter set, a test scene class parameter set, and a simulation run resource class parameter set.

S206, updating the basic parameter templates based on the parameter items to be updated to generate target parameter templates.

In some implementations, the parameter items to be updated are added to the basic parameter template, updating of the basic parameter template is achieved, and the target parameter template is generated. In some implementations, the parameter items to be updated are deleted from the base parameter template, the updating of the base parameter template is achieved, and the target parameter template is generated.

In the embodiment of the disclosure, a test task is parsed to obtain parameter items to be updated, the parameter items to be updated are obtained from a plurality of types of parameter sets, and a basic parameter template is updated based on the parameter items to be updated to generate a target parameter template. The method and the device can flexibly meet the test requirements of different automatic driving modules and the iteration test requirements of the service extension period, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test, avoid wasting time and improve the accuracy of generating parameter templates.

In some implementations, an object type of the template management object is identified. And updating the basic parameter template according to the object type and the parameter item to be updated to generate a target parameter template matched with the object type and the test task at the same time. If the template management object is a joint template management object, joint verification is carried out on the updated target parameter template of each template management object in the joint template management object, and the target parameter template is obtained after the joint verification is passed. Optionally, after the joint verification is passed, issuing respective updated target parameter templates to the respective bound computing clusters for the joint template management object to perform simulation test.

In some implementations, management rights for the template management object are obtained and the target parameter template is managed based on the management rights. For example, if the template management object is a personal user, the management rights of the template management object may include a new right, a query right, a sharing right, and a deletion right, where the new right is used to create a parameter template; the query authority is used for querying the existing parameter templates; the sharing authority is used for sending the parameter templates to other servers or electronic equipment; the deletion authority is used for deleting the parameter template. For example, if the template management object is a team user, the management authority of the template management object may include a new authority, a label authority, a copy authority, a sharing authority, and a visibility control authority, where the label authority is used to mark a test requirement or a test task of the parameter template; the copying authority is used for copying the existing parameter templates; the sharing authority is used for sharing the parameter templates to other servers or electronic equipment so as to carry out cooperative processing; the visibility control rights are used to control the presentable objects of the parameter templates.

In some implementations, after generating the base parameter template or the target parameter template, one of the parameter templates is sent to a target template management object, wherein the target template management object has authority to update the parameter template, an update operation of the target template management object on the one of the parameter templates is received, and the one of the parameter templates is updated based on the update operation. Alternatively, the updating operation may include an adding operation, a deleting operation, or the like, and the parameter item of one of the parameter templates may be operated on, deleted, or the like, based on the updating operation.

The method and the device can rapidly improve the initiation efficiency of the verification task, effectively improve the iteration speed of the team level, avoid the verification result difference introduced by different configuration parameters, improve the iteration efficiency of the simulation test, avoid wasting time and improve the accuracy of generating the parameter template.

FIG. 3 is a flow chart of a heterogeneous based parameter template generation method according to one embodiment of the present disclosure, as shown in FIG. 3, including the steps of:

s301, carrying out structuring processing on the data source to generate a parameter pool comprising multiple types of parameter sets.

The description of step S301 may be referred to the content of the above embodiment, and will not be repeated here.

S302, aiming at the historical test tasks of each type of test service, determining candidate historical test tasks with test results meeting test requirements from the historical test tasks.

In some implementations, each historical test task has a corresponding test result, and the test result can be matched with the test requirement, so that candidate historical test tasks with test results meeting the test requirement are determined from the historical test tasks. Optionally, matching the test result with the test requirement to obtain similarity, and determining the historical test task with similarity higher than a preset similarity threshold as a candidate historical test task.

S303, obtaining a test parameter combination of each candidate historical test task, and selecting partial parameter items from each type of parameter set based on the test parameter combination of the candidate historical test task.

In some implementations, a test parameter combination of each candidate historical test task is obtained, a test parameter combination with an optimal test result is determined from the test parameter combinations of the candidate historical test tasks and is used as a target test parameter combination, and then partial parameter items are selected from each type of parameter set according to the target test parameter combination.

In some implementations, a test parameter combination of each candidate historical test task is obtained, a test parameter combination with highest use frequency is determined from the test parameter combinations of the candidate historical test tasks and is used as a target test parameter combination, and then partial parameter items are selected from each type of parameter set according to the target test parameter combination.

S304, generating a basic parameter template of the test service based on part of parameter items in each type of parameter set.

S305, acquiring a test task of the template management object aiming at the test service, updating the basic parameter template according to the test task, and generating a target parameter template matched with the test task.

The descriptions of step S304 to step S305 may be referred to the content in the above embodiments, and are not repeated here.

In the embodiment of the disclosure, for each type of historical test task of a test service, candidate historical test tasks with test results meeting test requirements are determined from the historical test tasks, test parameter combinations of each candidate historical test task are obtained, and partial parameter items are selected from each type of parameter sets based on the test parameter combinations of the candidate historical test tasks. The method and the device can flexibly meet the test requirements of different automatic driving modules and the iteration test requirements of the service extension period, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test, avoid wasting time and improve the accuracy of generating parameter templates.

Fig. 4 is a schematic diagram of a heterogeneous parameter template generating method according to an embodiment of the present disclosure, where, as shown in fig. 4, a high-precision map class data source, a test scene class data source, an algorithm class data source, and a simulation operation resource class data source are acquired, and various data sources are structured to generate a parameter pool including a map class parameter set, an algorithm class parameter set, a test scene class parameter set, and a simulation operation resource class parameter set. Aiming at any one of a plurality of types of test services such as a map quality inspection test service, a perception verification test service, a PNC verification test service, a scene quality inspection test service and the like, according to the historical test task of the test service, selecting partial parameter items from each type of parameter set, generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set, and further generating a target parameter template. And acquiring the management authority of the template management object, and managing the target parameter template based on the management authority. And after the verification of the target parameter template is passed, issuing an updated target parameter template to the computing cluster bound by the template management object so as to carry out simulation test.

The method and the device can flexibly meet the test requirements of different automatic driving modules and the iteration test requirements of the service extension period, improve the coupling efficiency of various module types, improve the iteration efficiency of simulation test, avoid wasting time and improve the accuracy of generating parameter templates.

Fig. 5 is a block diagram of a heterogeneous based parameter template generating apparatus according to an embodiment of the present disclosure, and as shown in fig. 5, a heterogeneous based parameter template generating apparatus 500 includes:

a first generating module 510, configured to perform a structuring process on the data source, and generate a parameter pool including multiple types of parameter sets;

the second generating module 520 is configured to select, for each type of test service, a part of parameter items from each type of parameter set according to a historical test task of the test service, and generate a basic parameter template of the test service based on the part of parameter items in each type of parameter set;

and a third generating module 530, configured to obtain a test task of the template management object for the test service, update the basic parameter template according to the test task, and generate a target parameter template matched with the test task.

In some implementations, the third generation module 530 is further configured to:

analyzing the test task to obtain parameter items to be updated;

acquiring parameter items to be updated from a plurality of types of parameter sets;

and updating the basic parameter template based on the parameter items to be updated to generate the target parameter template.

identifying the object type of the template management object;

and updating the basic parameter template according to the object type and the parameter item to be updated to generate a target parameter template matched with the object type and the test task at the same time.

updating the target parameter template by the template management object, and checking the updated target parameter template;

and after the verification is passed, issuing an updated target parameter template to the computing cluster bound by the template management object so as to perform simulation test.

In some implementations, if the template management object is a federated template management object, the third generation module 530 is further configured to:

performing joint verification on the updated target parameter templates of each template management object in the joint template management objects;

after the joint verification is passed, the joint template management object issues respective updated target parameter templates to the respective bound computing clusters for simulation test.

and acquiring the management authority of the template management object, and managing the target parameter template based on the management authority.

In some implementations, the second generation module 520 is further configured to:

determining candidate historical test tasks with test results meeting test requirements from the historical test tasks;

and acquiring a test parameter combination of each candidate historical test task, and selecting partial parameter items from each type of parameter set based on the test parameter combination of the candidate historical test task.

determining a test parameter combination with an optimal test result from the test parameter combinations of the candidate historical test tasks as a target test parameter combination; or alternatively, the process may be performed,

determining a test parameter combination with highest use frequency from test parameter combinations of candidate historical test tasks as a target test parameter combination;

and selecting partial parameter items from each type of parameter set according to the target test parameter combination.

In some implementations, the heterogeneous based parameter template generation apparatus 500 further includes an update module 540 to:

after generating a basic parameter template or a target parameter template, transmitting one of the parameter templates to a target template management object, wherein the target template management object has the authority to update the parameter template;

and receiving an updating operation of the target template management object on one of the parameter templates, and updating one of the parameter templates based on the updating operation.

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 is a block diagram of an electronic device for implementing a heterogeneous based parameter template generation method of an embodiment 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 various methods and processes described above, such as the heterogeneous-based parametric template generation method. For example, in some embodiments, the heterogeneous based parametric template generation 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 the computing unit 601, one or more steps of the heterogeneous based parameter template generation method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the heterogeneous based parameter template generation method in any other suitable manner (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), 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 may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

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 or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure 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

1. A heterogeneous-based parametric template generation method, comprising:

selecting partial parameter items from each type of parameter set according to the historical test task of each type of test service, and generating a basic parameter template of the test service based on the partial parameter items in each type of parameter set;

and acquiring a test task of a template management object aiming at the test service, updating the basic parameter template according to the test task, and generating a target parameter template matched with the test task.

2. The method of claim 1, wherein the updating the base parameter template according to the test task to generate a target parameter template that matches the test task comprises:

analyzing the test task to obtain parameter items to be updated;

acquiring the parameter items to be updated from the multi-class parameter set;

updating the basic parameter template based on the parameter item to be updated to generate the target parameter template.

3. The method of claim 2, wherein the method further comprises:

identifying the object type of the template management object;

and updating the basic parameter template according to the object type and the parameter item to be updated so as to generate a target parameter template matched with the object type and the test task at the same time.

4. A method according to claim 3, wherein after generating the target parameter template, the method further comprises:

and after the verification is passed, issuing the updated target parameter template to the computing cluster bound by the template management object so as to perform simulation test.

5. The method of claim 4, wherein if the template management object is a federated template management object, the method further comprises:

and after the joint verification is passed, issuing the updated target parameter templates to the respectively bound computing clusters by the joint template management object to perform simulation test.

6. The method of claim 2, wherein after generating the target parameter templates that match the object type and the test task simultaneously, further comprising:

7. The method according to any one of claims 1-6, wherein selecting partial parameter items from each class of parameter sets according to the historical test tasks of the test service comprises:

8. The method of claim 7, wherein the selecting partial parameter items from each class of parameter sets based on the test parameter combinations of the candidate historical test tasks comprises:

determining a test parameter combination with highest use frequency from the test parameter combinations of the candidate historical test tasks as the target test parameter combination;

9. The method of any of claims 1-6, wherein the method further comprises:

after the basic parameter template or the target parameter template is generated, one parameter template is sent to a target template management object, wherein the target template management object has the authority of updating the parameter template;

and receiving an updating operation of the target template management object on one of the parameter templates, and updating the one of the parameter templates based on the updating operation.

10. A heterogeneous-based parameter template generation apparatus, comprising:

11. The apparatus of claim 10, wherein the third generation module is further configured to:

analyzing the test task to obtain parameter items to be updated;

acquiring the parameter items to be updated from the multi-class parameter set;

12. The apparatus of claim 11, wherein the third generation module is further configured to:

identifying the object type of the template management object;

13. The apparatus of claim 12, wherein the third generation module is further configured to:

14. The apparatus of claim 13, wherein if the template management object is a federated template management object, the third generation module is further configured to:

15. The apparatus of claim 11, wherein the third generation module is further configured to:

16. The apparatus of any of claims 10-15, wherein the second generation module is further to:

17. The apparatus of claim 16, wherein the second generation module is further configured to:

18. The apparatus of any of claims 10-15, wherein the apparatus further comprises an update module to:

19. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.

20. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-9.

21. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any of claims 1-9.