CN118152282A - Plug-in testing method, device, equipment and storage medium - Google Patents

Abstract

The invention discloses a plug-in testing method, device, equipment and storage medium. The method comprises the following steps: acquiring a parameter set of the updated first plugin, and determining a production environment set corresponding to the updated first plugin according to the parameter set of the updated first plugin; determining a target production environment according to the updated first plugin and a production environment set corresponding to the updated first plugin; acquiring operation parameters of the updated first plugin when the updated first plugin is deployed in the target production environment; if the operation parameters of the updated first plug-in meet the first preset parameter conditions, the updated first plug-in is deployed in each production environment in the production environment set, and the stable update of the plug-in can be realized and the stable operation of the system is ensured by the technical scheme of the invention.

Description

A plug-in testing method, device, equipment and storage medium

Technical Field

Embodiments of the present invention relate to the technical field of power systems, and in particular to a plug-in testing method, device, equipment and storage medium.

Background technique

In modern power systems, distributed artificial intelligence (AI) services are increasingly becoming a key technology for improving operational efficiency, ensuring safety and stability, and supporting intelligent decision-making. These services are usually embedded in the power system management software in the form of plug-ins. Plug-ins can be defined as software components that add specific functions. They enable the system to be easily expanded and upgraded as needed. In power distributed artificial intelligence services, plug-ins are usually responsible for performing tasks such as data analysis, pattern recognition, and load forecasting, which play a vital role in the performance and stability of the system.

However, with the advancement of technology and changes in system requirements, these plug-ins need to be updated regularly to maintain the optimal performance and safety of the power system; plug-in updates not only involve performance improvements, but also include security patches and function enhancements; improper updates may lead to incompatibility issues with existing systems; and even affect the stable operation of the entire power system. Therefore, it is extremely important to test and update the plug-ins.

Summary of the invention

The embodiments of the present invention provide a plug-in testing method, device, equipment and storage medium, which solve the problem of reduced stability of the power system due to improper update of the plug-in.

According to one aspect of the present invention, there is provided a plug-in testing method, comprising:

Obtaining a parameter set of the updated first plug-in, and determining a production environment set corresponding to the updated first plug-in according to the parameter set of the updated first plug-in;

Determine a target production environment according to the updated first plug-in and a set of production environments corresponding to the updated first plug-in;

Obtaining running parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment;

If the running parameters of the updated first plug-in meet the first preset parameter condition, the updated first plug-in is deployed in each production environment in the production environment set.

According to another aspect of the present invention, a plug-in testing device is provided, the plug-in testing device comprising:

An environment acquisition module, used to acquire a parameter set of the updated first plug-in, and determine a production environment set corresponding to the updated first plug-in according to the parameter set of the updated first plug-in;

An environment determination module, configured to determine a target production environment according to the updated first plug-in and a set of production environments corresponding to the updated first plug-in;

A parameter acquisition module, used to acquire the running parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment;

The plug-in deployment module is used to deploy the updated first plug-in in each production environment in the production environment set if the operating parameters of the updated first plug-in meet the first preset parameter conditions.

According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

at least one processor; and

a memory communicatively connected to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the plug-in testing method described in any embodiment of the present invention.

According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the plug-in testing method described in any embodiment of the present invention when executed.

The embodiment of the present invention obtains a parameter set of an updated first plug-in, and determines a production environment set corresponding to the updated first plug-in based on the parameter set of the updated first plug-in; determines a target production environment based on the updated first plug-in and the production environment set corresponding to the updated first plug-in; obtains operating parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment; if the operating parameters of the updated first plug-in meet the first preset parameter conditions, deploys the updated first plug-in in each production environment in the production environment set, thereby solving the problem of reduced stability of the power system due to improper updating of the plug-in, achieving stable updating of the plug-in, and ensuring stable operation of the power system.

It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

FIG1 is a flow chart of a plug-in testing method in Embodiment 1 of the present invention;

FIG2 is a schematic diagram of the structure of a plug-in testing device in Embodiment 2 of the present invention;

FIG3 is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

Embodiment 1

Figure 1 is a flow chart of a plug-in testing method in embodiment 1 of the present invention. This embodiment is applicable to the update of a distributed artificial intelligence service plug-in in a power system. The method can be executed by a plug-in testing device in an embodiment of the present invention, which can be implemented in software and/or hardware.

As shown in FIG1 , the method specifically comprises the following steps:

S110, obtaining a parameter set of the updated first plug-in, and determining a production environment set corresponding to the updated first plug-in according to the parameter set of the updated first plug-in.

The first plug-in is a plug-in that needs to be updated, and the parameter set includes: quality score, compatibility score, and efficiency score. Each production environment in the production environment set corresponding to the first plug-in is a production environment in the power system where the first plug-in can be deployed.

Specifically, after obtaining the updated first plug-in, the test environment is detected based on the production environment in the actual power system, and the updated first plug-in on the created branch in the plug-in version control system is deployed to the test environment, that is, a new branch is created from the main development branch (master or main), and the naming should reflect its purpose, such as feature/update-plugin-x or hotfix/plugin-x-version-y. The method of obtaining the parameter set of the updated first plug-in is as follows: using CI tools (such as Jenkins, Travis CI, CircleCI) to automatically build and test the code, each time it is pushed to the branch, the CI tool runs the test and reports the results. During the code review process, the automated code review tool SonarQube is used to identify potential problems and areas for improvement, thereby obtaining the quality score of the updated first plug-in; performing integration testing by simulating the test environment of the real power system environment to ensure the compatibility and interaction of the updated first plug-in with other parts of the system, thereby obtaining the compatibility score of the updated first plug-in; using performance testing tools (such as LoadRunner, JMeter) to simulate user load and operation, thereby obtaining the efficiency score of the updated first plug-in.

Specifically, a parameter set of the updated first plug-in is obtained, and a production environment of the power system in which the updated first plug-in can be deployed is determined according to each parameter in the parameter set of the updated first plug-in, thereby determining a production environment set corresponding to the updated first plug-in.

By deploying the updated first plug-in to the test environment in a new branch, developers can develop and test new functions or updates to the first plug-in without affecting the main branch. Any update can be fully tested in the new branch to ensure that it will not cause damage to the power system, and the new branch can be continuously inherited or continuously deployed in the pipeline, so that each time the first plug-in is updated, it can be automatically built and tested to ensure that changes to the plug-in will not damage the existing power system.

Optionally, before obtaining the updated parameter set of the first plug-in, the following method is further included:

Obtain a target score for each test indicator of at least one plug-in to be updated and an updated plug-in;

Determining an update index of the updated plug-in according to a target score of each test indicator of the updated plug-in, a preset weight of each test indicator, and the number of test indicators;

The updated plug-in whose update index is greater than a preset index threshold is determined as an updated first plug-in.

The plug-in to be updated is the plug-in that needs to be updated, the test indicators can be security, reliability, performance and functionality, and the target score is the score of each test indicator. The preset weight of each test indicator, the number of test indicators and the preset index threshold can be set according to actual needs.

It should be noted that the target scores of the test indicators can be obtained in the following ways: the target score of security can be calculated by analyzing the code, documentation and configuration of the updated first plug-in, and the analysis process includes reviewing the security patches and fixes contained in the update to assess potential security, and detecting potential security vulnerabilities through static code analysis tools; the target score of reliability is calculated based on the update history and the information provided by the developer; the target score of performance is calculated based on running performance simulation tests, such as load tests and stress tests, to calculate the impact of the updated first plug-in on the performance of the power system, and analyze the performance change logs and performance benchmark data provided by the developer; the target score of functionality is calculated by analyzing the documentation and release notes of the updated first plug-in, determining the functions of the updated first plug-in and the specific content of the improvements, and running functional test cases, including unit tests and integration tests, to obtain the corresponding score of functionality.

Specifically, at least one plug-in to be updated, that is, a plug-in that needs to be updated, is obtained. The method of obtaining is not limited. After obtaining at least one plug-in to be updated, the updated plug-in and the test indicators corresponding to the updated plug-in and the quantitative scoring standard for each test indicator are obtained. Based on the quantitative scoring standard for each test indicator, the influencing factors of each test indicator of the updated plug-in are scored to obtain the target score of each test indicator of the updated plug-in. For example, the score of each test indicator can be normalized to between 0 and 1:

x _i = _ti /t _im ;

Among them, _xi represents the normalized score of test indicator i, that is, the target score, which is between 0 and 1, _ti represents the actual score of test indicator i, and _tim represents the total score of test indicator i.

Specifically, the update index of the updated plug-in may be determined according to the target score of each test indicator of the updated plug-in, the preset weight of each test indicator, and the number of test indicators:

Among them, N is the update index, w _i is the preset weight of test indicator i, n is the number of test indicators,

Specifically, if the update index of the updated plug-in is greater than the preset index threshold, it means that the update of the plug-in is a necessary update, and the updated plug-in is determined as the first plug-in after the update; if the update index of the updated plug-in is less than or equal to the preset index threshold, it means that the update of the plug-in is not a necessary update, and no update is performed this time.

By determining the update index of the updated plug-in according to the target score of each test indicator of the updated plug-in, the preset weight of each test indicator and the number of test indicators; determining the updated plug-in whose update index is greater than the preset index threshold as the first updated plug-in, the necessity of plug-in update can be evaluated according to the impact of the plug-in to be updated on the operation of the power system, and whether the update is necessary can be determined, and some updates with less optimization for the power system after the update can be excluded, thereby ensuring the stability of the power system.

Optionally, determining a production environment set corresponding to the updated first plug-in according to the parameter set of the updated first plug-in includes:

If each parameter in the parameter set of the updated first plug-in satisfies the second preset parameter condition, the production environment set corresponding to the updated first plug-in is determined according to the attribute information of the updated first plug-in.

The parameters in the parameter set of the updated first plug-in include: a quality score, a compatibility score, and an efficiency score, and the second preset parameter condition is that the score is greater than a preset score threshold.

The property information of the updated first plug-in may include compatibility, version information, dependencies, configuration methods, management interfaces, logs, and deployment strategies of the updated first plug-in.

Specifically, if each parameter in the parameter set of the updated first plug-in satisfies the second preset parameter condition, that is, each parameter meets the update requirement, all production environments in the power system are judged according to the attribute information of the updated first plug-in, and a set of production environments in which the updated first plug-in can be deployed in the power system is obtained. It should be noted that if there is at least one parameter in the set parameters of the updated first plug-in that does not meet the second preset parameter condition, the updated first plug-in is further optimized until each parameter of the optimized first plug-in meets the second preset parameter condition.

By determining the production environment set corresponding to the updated first plug-in according to the attribute information of the updated first plug-in if each parameter in the parameter set of the updated first plug-in satisfies the second preset parameter condition, a preliminary evaluation can be performed on the updated first plug-in to determine whether the updated first plug-in is qualified; if qualified, the production environment set corresponding to the updated first plug-in is determined according to the attribute information of the updated first plug-in, thereby improving the accuracy of deploying the updated first plug-in in the production environment of the power system.

S120: Determine a target production environment according to the updated first plug-in and a set of production environments corresponding to the updated first plug-in.

The target production environment is the production environment on which the impact of the updated first plug-in is the lowest.

Specifically, the influence of the updated first plug-in on each production environment in the production environment set corresponding to the updated first plug-in is obtained according to the updated first plug-in, and the production environment with the smallest influence is determined as the target production environment.

Optionally, determining the target production environment according to the updated first plug-in and a production environment set corresponding to the updated first plug-in includes:

Obtaining the impact of the updated first plug-in on each production environment when the updated first plug-in is deployed in each production environment in the production environment set;

The production environment set is screened according to the impact of the updated first plug-in on each production environment to obtain a target production environment.

Specifically, the updated first plug-in is deployed to each production environment in the production environment set for testing, and the impact of the updated first plug-in on each production environment is obtained.

Specifically, the production environment set is screened according to the impact of the updated first plug-in on each production environment, and the production environment with the smallest impact is determined as the target production environment.

Optionally, obtaining the impact of the updated first plug-in on each production environment when the updated first plug-in is deployed in each production environment in the production environment set includes:

Obtaining a score for each impact evaluation indicator when the updated first plug-in is deployed in each production environment in the production environment set;

The impact of the updated first plug-in on each production environment in the production environment set is determined based on the score of each impact evaluation indicator, the number of impact evaluation indicators, and the preset weight of each impact evaluation indicator when the updated first plug-in is deployed in each production environment in the production environment set.

Among them, each impact evaluation indicator, the number of impact evaluation indicators and the preset weight of each impact evaluation indicator can be set according to actual needs.

Specifically, when the updated first plug-in is deployed in each production environment in the production environment set, the score of each impact evaluation indicator, the number of impact evaluation indicators, and the preset weight of each impact evaluation indicator determine the impact of the updated first plug-in on each production environment when the updated first plug-in is deployed in each production environment in the production environment set. The manner may be:

Among them, _TI is the impact of the updated first plug-in on the I-th production environment, m is the number of impact evaluation indicators, _wz is the preset weight of the z-th impact evaluation indicator, and _yz is the score of the z-th impact evaluation indicator.

By obtaining the impact of the updated first plug-in on each production environment and determining the production environment with the least impact as the target production environment, the impact of the updated first plug-in on the system can be minimized, and the problem of reduced stability of the power system due to plug-in problems can be minimized.

S130, obtaining running parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment.

The updated operating parameters of the first plug-in are key performance indicators, which can be set according to actual conditions.

Specifically, the operating parameters of the updated first plug-in when it is deployed in the target production environment can be monitored in real time through a performance monitoring tool.

S140: If the running parameters of the updated first plug-in meet the first preset parameter condition, deploy the updated first plug-in in each production environment in the production environment set.

The first preset parameter condition may be that a current compliance rate corresponding to the updated running parameter of the first plug-in is greater than a historical compliance rate.

Specifically, if the running parameters of the updated first plug-in meet the first preset parameter condition, indicating that the updated first plug-in is a qualified plug-in version, the updated first plug-in is deployed in each production environment in the production environment set.

Optionally, if the running parameter of the updated first plug-in satisfies the first preset parameter condition, deploying the updated first plug-in in each production environment in the production environment set includes:

Obtaining historical records and historical application cycles of the first plug-in, and determining a historical compliance rate according to the historical records and historical application cycles;

Determine the current compliance rate according to the updated operating parameters of the first plug-in and the preset monitoring period;

If the current compliance rate is greater than the historical compliance rate, it is determined that the operating parameters of the updated first plug-in meet the first preset parameter condition, and the updated first plug-in is deployed in each production environment in the production environment set.

Among them, the preset monitoring period can be set according to actual needs.

Specifically, the historical records and historical application cycles of the first plug-in are obtained, the number of times the key performance indicators included in the operating parameters are lower than the key performance indicator threshold is obtained based on the historical application cycle, and the historical compliance rate is obtained based on the historical application cycle and the number of times the key performance indicators are lower than the historical key performance indicator threshold.

Specifically, the current key performance indicator threshold of the updated first plug-in is set, and when the monitored key performance indicator is lower than the current key performance indicator threshold, it is recorded and an alert is issued; the number of times the current key performance indicator is lower than the current key performance indicator threshold within the preset monitoring period is obtained, and the current compliance rate is obtained based on the number and the preset monitoring period.

Specifically, if the current compliance rate is greater than the historical compliance rate, it is determined that the operating parameters of the updated first plug-in meet the first preset parameter conditions, and it is considered that the performance and stability of the current updated first plug-in meet the standards, then the updated first plug-in is deployed in each production environment in the production environment set; if the current compliance rate is less than or equal to the historical compliance rate, it is considered that the performance and stability of the current updated first plug-in do not meet the standards, and the first plug-in needs to be modified.

If the current compliance rate is greater than the historical compliance rate, it is determined that the operating parameters of the updated first plug-in meet the first preset parameter conditions, and the updated first plug-in is deployed in each production environment in the production environment set. The first plug-in that meets both performance and stability requirements can be accurately deployed in the production environment, thereby improving the stability of the system.

Optionally, after deploying the updated first plug-in in each production environment in the production environment set, the method further includes:

Acquire actual monitoring indicators of the updated first plug-in when it is deployed in each production environment, wherein the monitoring indicators include: response time, throughput, and error rate;

If the actual monitoring indicator satisfies at least one of the following: the actual response time is less than the preset time threshold, the actual throughput is less than the preset throughput threshold, and the actual error rate is greater than the preset error rate, an early warning is issued.

Specifically, a monitoring tool is deployed to monitor actual monitoring indicators when the updated first plug-in is deployed in each production environment, such as one of Nagios, Zabbix, and Prometheus, and customized monitoring indicators. The monitoring indicators include response time, throughput, and error rate, and the thresholds of each monitoring indicator are obtained, including a preset time threshold, a preset throughput threshold, and a preset error rate.

Specifically, if the actual monitoring indicator satisfies at least one of the following: the actual response time is less than a preset time threshold, the actual throughput is less than a preset throughput threshold, and the actual error rate is greater than a preset error rate, an early warning is issued.

The technical solution of this embodiment obtains a parameter set of the updated first plug-in, and determines a production environment set corresponding to the updated first plug-in based on the parameter set of the updated first plug-in; determines a target production environment based on the updated first plug-in and the production environment set corresponding to the updated first plug-in; obtains the operating parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment; if the operating parameters of the updated first plug-in meet the first preset parameter conditions, deploys the updated first plug-in in each production environment in the production environment set, thereby solving the problem of reduced stability of the power system due to improper update of the plug-in, and can achieve stable update of the plug-in to ensure stable operation of the power system.

Embodiment 2

FIG2 is a schematic diagram of the structure of a plug-in testing device in Embodiment 2 of the present invention. This embodiment is applicable to the case of updating a distributed artificial intelligence service plug-in in a power system. The device can be implemented in software and/or hardware, and can be integrated in any device that provides plug-in testing functions. As shown in FIG2 , the plug-in testing device specifically includes: an environment acquisition module 210, an environment determination module 220, a parameter acquisition module 230, and a plug-in deployment module 240.

The environment acquisition module 210 is used to acquire a parameter set of the updated first plug-in, and determine a production environment set corresponding to the updated first plug-in according to the parameter set of the updated first plug-in;

An environment determination module 220, configured to determine a target production environment according to the updated first plug-in and a set of production environments corresponding to the updated first plug-in;

The parameter acquisition module 230 is used to acquire the running parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment;

The plug-in deployment module 240 is configured to deploy the updated first plug-in in each production environment in the production environment set if the operating parameters of the updated first plug-in meet the first preset parameter condition.

Optionally, also include:

A score acquisition module, used to acquire a target score for each test indicator of at least one plug-in to be updated and an updated plug-in;

An index determination module, configured to determine an update index of the updated plug-in according to a target score of each test indicator of the updated plug-in, a preset weight of each test indicator, and the number of test indicators;

The plug-in determination module is used to determine the updated plug-in whose update index is greater than a preset index threshold as the updated first plug-in.

Optionally, the environment acquisition module is specifically used for:

If each parameter in the parameter set of the updated first plug-in satisfies the second preset parameter condition, the production environment set corresponding to the updated first plug-in is determined according to the attribute information of the updated first plug-in.

Optionally, the environment determination module is specifically used to:

Obtaining the impact of the updated first plug-in on each production environment when the updated first plug-in is deployed in each production environment in the production environment set;

The production environment set is screened according to the impact of the updated first plug-in on each production environment to obtain a target production environment.

Optionally, the environment determination module is specifically used to:

Obtaining a score for each impact evaluation indicator when the updated first plug-in is deployed in each production environment in the production environment set;

The impact of the updated first plug-in on each production environment in the production environment set is determined based on the score of each impact evaluation indicator, the number of impact evaluation indicators, and the preset weight of each impact evaluation indicator when the updated first plug-in is deployed in each production environment in the production environment set.

Optionally, the plug-in deployment module is specifically used to:

Obtaining historical records and historical application cycles of the first plug-in, and determining a historical compliance rate according to the historical records and historical application cycles;

Determine the current compliance rate according to the updated operating parameters of the first plug-in and the preset monitoring period;

If the current compliance rate is greater than the historical compliance rate, it is determined that the operating parameters of the updated first plug-in meet the first preset parameter condition, and the updated first plug-in is deployed in each production environment in the production environment set.

Optionally, also include:

An indicator acquisition module, used to acquire actual monitoring indicators when the updated first plug-in is deployed in each production environment, wherein the monitoring indicators include: response time, throughput and error rate;

The indicator warning module is used to issue an early warning if the actual monitoring indicator meets at least one of the following conditions: the actual response time is less than a preset time threshold, the actual throughput is less than a preset throughput threshold, and the actual error rate is greater than a preset error rate.

The above-mentioned product can execute the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

Embodiment 3

FIG3 is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and/or required herein.

As shown in FIG3 , the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11 in communication, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.

A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the plug-in testing method.

In some embodiments, the plug-in testing method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed on the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the plug-in testing method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the plug-in testing method in any other appropriate manner (e.g., by means of firmware).

Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and/or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions/operations specified in the flow chart and/or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the 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, voice input, or tactile input).

The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A method for testing a plug-in, comprising:

acquiring a parameter set of the updated first plugin, and determining a production environment set corresponding to the updated first plugin according to the parameter set of the updated first plugin;

determining a target production environment according to the updated first plugin and a production environment set corresponding to the updated first plugin;

Acquiring operation parameters of the updated first plugin when the updated first plugin is deployed in the target production environment;

And if the running parameters of the updated first plug-in meet the first preset parameter conditions, deploying the updated first plug-in each production environment in the production environment set.

2. The method of claim 1, further comprising, prior to obtaining the updated parameter set for the first plug-in:

obtaining target scores of each test index of at least one plug-in to be updated and the plug-in after updating;

Determining an updated index of the updated plug-in according to the target score of each test index of the updated plug-in, the preset weight of each test index and the number of the test indexes;

and determining the updated plug-in with the updated index being greater than a preset index threshold as the updated first plug-in.

3. The method of claim 1, wherein determining the updated set of production environments corresponding to the first plug-in from the updated set of parameters for the first plug-in comprises:

If each parameter in the updated parameter set of the first plugin meets the second preset parameter condition, determining a production environment set corresponding to the updated first plugin according to the attribute information of the updated first plugin.

4. The method of claim 1, wherein determining the target production environment from the updated first plug-in and the set of production environments corresponding to the updated first plug-in comprises:

Acquiring the influence degree of the updated first plug-in on each production environment when the updated first plug-in is deployed in each production environment in the production environment set;

And screening the production environment set according to the influence degree of the updated first plug-in on each production environment to obtain a target production environment.

5. The method of claim 4, wherein obtaining the impact of the updated first plug-in on each production environment as the updated first plug-in is deployed in each production environment in the set of production environments comprises:

Obtaining the score of each influence evaluation index when the updated first plug-in is deployed in each production environment in the production environment set;

Determining the influence degree of the updated first plug-in on each production environment in the production environment set according to the score of each influence degree evaluation index, the number of the influence degree evaluation indexes and the preset weight of each influence degree evaluation index when the updated first plug-in is deployed in each production environment in the production environment set.

6. The method of claim 1, wherein deploying the updated first plug-in each production environment in the set of production environments if the updated first plug-in's operating parameters satisfy a first preset parameter condition comprises:

Acquiring a history record and a history application period of a first plug-in, and determining a history standard rate according to the history record and the history application period;

determining the current standard rate according to the updated operation parameters of the first plug-in unit and a preset monitoring period;

If the current standard reaching rate is larger than the historical standard reaching rate, determining that the running parameters of the updated first plug-in meet the first preset parameter conditions, and disposing the updated first plug-in each production environment in the production environment set.

7. The method of claim 1, further comprising, after deploying the updated first plug-in each production environment in a set of production environments:

Acquiring an updated actual monitoring index of the first plug-in when being deployed in each production environment, wherein the monitoring index comprises: response time, throughput, and error rate;

And if the actual monitoring index meets at least one of that the actual response time is smaller than the preset time threshold, the actual throughput is smaller than the preset throughput threshold and the actual error rate is larger than the preset error rate, early warning is carried out.

8. A card testing apparatus, comprising:

The environment acquisition module is used for acquiring the updated parameter set of the first plugin and determining a production environment set corresponding to the updated first plugin according to the updated parameter set of the first plugin;

The environment determining module is used for determining a target production environment according to the updated first plug-in and the production environment set corresponding to the updated first plug-in;

The parameter acquisition module is used for acquiring the operation parameters of the updated first plug-in when the updated first plug-in is deployed in the target production environment;

and the plug-in deployment module is used for deploying the updated first plug-in each production environment in the production environment set if the operation parameters of the updated first plug-in meet the first preset parameter conditions.

9. An electronic device, the electronic device comprising:

At least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the plug-in test method of any one of claims 1-7.

10. A computer readable storage medium storing computer instructions for causing a processor to implement the plug-in test method of any one of claims 1-7 when executed.