CN119201739A - Automated testing API interface intelligent testing method - Google Patents
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Abstract
The invention belongs to the technical field of software testing and automatic testing, and discloses an intelligent testing method for an automatic testing API interface, which comprises the following specific steps: S1, information input and position identification S2, analysis system, data decomposition and data characteristic analysis S3, detection system, calculation of characteristic data weight and matching of a protocol S4, service system, request execution and response acquisition S5, packaging of system, data arrangement and return S6, user return S7, and monitoring and optimization. The invention provides remarkable benefits by adopting an automatic flow of executing requests and acquiring responses by a service system and combining an intelligent characteristic data weight calculation and protocol matching method, provides scientific basis for selecting the optimal protocol by accurately quantifying the importance of each parameter characteristic and distributing weights, constructs a weight evaluation system, ensures that the matching degree of different protocols and the requests is accurately evaluated, and is beneficial to improving the efficiency and accuracy of data transmission.
Description
Technical Field
The invention belongs to the technical field of software testing and automatic testing, and particularly relates to an intelligent testing method for an automatic testing API (application program interface).
Background
In single protocol API testing, while we can plan the testing strategy in detail, including full coverage from input condition validation to resource modification, the existing testing techniques still show significant shortcomings in practice. The testers need to have deep knowledge of the API interface protocol, which clearly increases the learning cost, and meanwhile, each test case and each assertion are independently written, which is tedious and time-consuming. The protocol definition test scenario and suite further exacerbates this problem, especially when interfacing with third party interfaces, inefficiency becomes a big pain point. Therefore, searching for a more efficient and automatic test scheme to reduce repetitive labor and improve test coverage and accuracy is a current urgent problem to be solved.
Disclosure of Invention
The invention aims to provide an intelligent testing method for an automatic testing API interface, which aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme that an intelligent testing method for automatically testing an API interface comprises the following specific steps:
s1, information input and position identification, namely, user input request, system analysis URL positioning service interface and extraction of service identification information;
s2, analyzing the system-decomposing data and analyzing the data characteristics, namely analyzing the request parameters, extracting characteristic data comprising types, formats, sizes, request heads and files, and preparing for protocol matching;
s3, detecting a system, namely calculating characteristic data weight and matching a protocol, namely calculating the characteristic weight, intelligently matching the protocol, combining the weight with the round-robin detection, and selecting an optimal protocol to process a request;
s4, a service system-executing request and acquiring response, wherein the service system-executing request and acquiring response is matched with a protocol access interface, sends the request and receives a server side status code, a header and volume data;
s5, packaging the system, namely finishing returned data, namely processing a response body, analyzing a format, packaging the data and ensuring the usability of a client;
S6, returning to a user, namely sending package data, recording log information, and analyzing the boosting performance and checking problems;
And S7, monitoring and optimizing, namely monitoring performance, optimizing protocol matching, and improving system efficiency and user experience.
Preferably, the specific steps of inputting the information and identifying the position in S1 are as follows:
step one, submitting a request, namely submitting a request comprising a request URL, a request method and a request parameter through an interface or an API interface by a user;
analyzing the URL and extracting information, namely after the system receives the request, analyzing the URL of the request to identify the specific service interface position, and extracting relevant service identification information in the process.
Preferably, the specific steps of analyzing the system-decomposed data and analyzing the data characteristics in S2 are as follows:
firstly, analyzing each parameter in the request one by a system, determining the data type and format of the request, and checking whether the size of the parameter accords with a preset limit (such as the upper limit of the size of a file);
Analyzing the request header, namely then, analyzing the request header information, such as Content-Type, by a system to know the media Type of the request body, and verifying the identity and authority of the requester by Author i zat i on;
Step three, processing the request files, wherein if the request contains files, the system can perform necessary processing on the files, such as verifying the file type, size and security;
and step four, extracting characteristic data, namely finally, based on the analyzed parameters and request header information, extracting key characteristic data by the system, evaluating the complexity of a data structure, and whether specific encryption processing is needed or not, and preparing for subsequent protocol matching and data processing.
Preferably, the specific steps of detecting the system-calculating the characteristic data weight and matching the protocol in S3 are as follows:
firstly, carrying out quantitative evaluation on each analyzed parameter characteristic, and distributing corresponding weight values according to importance of the parameter characteristic;
Step two, a weight evaluation system is established, the calculated characteristic weight is compared with the protocol characteristic, and the matching degree score of each protocol and the current request is calculated;
And step three, intelligent protocol matching, namely intelligently selecting a protocol mode with highest matching degree by using the weight information and a first round of detection mode in a protocol set so as to process the current request.
Preferably, in the step S4, the service system-executing the request and obtaining the response means that based on the matched best protocol mode, the system initiates the request to the service end through the corresponding application layer interface and the transport layer interface, and then, the system listens and receives the response data from the service end, where the data includes the status code in detail to indicate the result of the request processing, the response header provides additional metadata information, and the response body includes actual data content.
Preferably, the step S5 of packaging the system-sorting the returned data means that after receiving the response from the server, the system first processes the content of the response body in detail, performs corresponding parsing operation according to the actual format of the response body, and after finishing content sorting, the system further packages the sorted data according to a format agreed in advance, and in the packaging process, adds a custom response header to transmit additional information, adjusts the data structure, so as to be convenient to better adapt to the processing logic of the client.
Preferably, the returning to the user in S6 refers to returning the processing result to the user through HTTP, RPC and TCP high-efficiency protocols immediately after the system completes data encapsulation, and at the same time, optimizing the system performance and improving the maintenance efficiency, the system thoroughly records the key information in the whole request processing process, such as the initiation time of the request, the processing time of the server and the final response state.
Preferably, the specific steps of monitoring and optimizing in S7:
the performance monitoring method comprises the steps of implementing a comprehensive performance monitoring system, collecting and analyzing response time and processing efficiency data of the system in real time, and timely finding potential performance bottlenecks or abnormal behaviors through setting a threshold value and an alarm mechanism;
Step two, problem analysis and bottleneck positioning, namely after the performance problem is found, deep problem analysis is carried out, and specific links or components causing the performance bottleneck are accurately positioned by using log, stack tracking and performance analysis tool means;
and step three, protocol and service optimization, namely, carrying out targeted optimization on a protocol matching algorithm and a service calling mode according to a performance monitoring result and a problem analysis conclusion, wherein the targeted optimization comprises the steps of improving algorithm logic, optimizing a data transmission format, adjusting a service deployment architecture or introducing a new high-efficiency technical stack.
The beneficial effects of the invention are as follows:
The invention provides remarkable benefits by adopting an automatic flow of executing requests and acquiring responses by a service system and combining an intelligent characteristic data weight calculation and protocol matching method, provides scientific basis for selecting the optimal protocol by accurately quantifying the importance of each parameter characteristic and distributing weights, constructs a weight evaluation system, ensures that the matching degree of different protocols and the requests is accurately evaluated, the intelligent protocol matching mechanism is beneficial to improving the efficiency and accuracy of data transmission, combines the first round of inspection and optimizes the strategy, can rapidly locate and apply the protocol mode most suitable for the current request, effectively reduces delay and error, improves the user experience, has high flow automation degree, reduces human intervention, and improves the stability and reliability of the system.
Drawings
FIG. 1 is a flow chart of the intelligent test method of the present invention;
FIG. 2 is a flow chart illustrating an intelligent test scheme for an API interface according to the present invention;
fig. 3 is a diagram of the relationship between Web API protocols of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1 to 3, the embodiment of the invention provides an intelligent testing method for an automated testing API interface, which comprises the following specific steps:
s1, information input and position identification, namely, user input request, system analysis URL positioning service interface and extraction of service identification information;
s2, analyzing the system-decomposing data and analyzing the data characteristics, namely analyzing the request parameters, extracting characteristic data comprising types, formats, sizes, request heads and files, and preparing for protocol matching;
s3, detecting a system, namely calculating characteristic data weight and matching a protocol, namely calculating the characteristic weight, intelligently matching the protocol, combining the weight with the round-robin detection, and selecting an optimal protocol to process a request;
s4, a service system-executing request and acquiring response, wherein the service system-executing request and acquiring response is matched with a protocol access interface, sends the request and receives a server side status code, a header and volume data;
s5, packaging the system, namely finishing returned data, namely processing a response body, analyzing a format, packaging the data and ensuring the usability of a client;
S6, returning to a user, namely sending package data, recording log information, and analyzing the boosting performance and checking problems;
And S7, monitoring and optimizing, namely monitoring performance, optimizing protocol matching, and improving system efficiency and user experience.
The specific steps of information input and position identification in the S1 are as follows:
step one, submitting a request, namely submitting a request comprising a request URL, a request method (such as GET and POST) and request parameters through an interface or an API (application program interface).
Analyzing the URL and extracting information, namely after the system receives the request, analyzing the URL of the request to identify a specific service interface position (namely an API path), and extracting relevant service identification information in the process.
A user submits a request through an visual interface or an API interface, and the system responds quickly and accurately to analyze the URL to locate the service interface and extract key information. The process simplifies the user operation and improves the efficiency and accuracy of request processing. Through automatic analysis and information extraction, the system can understand the user demands more quickly, and lays a solid foundation for subsequent service call and data processing, thereby improving the overall user experience and the system response speed.
The specific steps of analyzing the system-decomposed data and analyzing the data characteristics in the step S2 are as follows:
Firstly, analyzing parameters of a request one by a system, determining the data type (Stri ng, int) and format (such as JSON, XML) of the request, and checking whether the size of the parameters accords with preset limits (such as upper limit of file size);
Analyzing the request header, namely then, analyzing the request header information, such as Content-Type, by a system to know the media Type of the request body, and verifying the identity and authority of the requester by Author i zat i on;
And step three, processing the request file, wherein if the request contains files (such as pictures, documents and the like), the system can perform necessary processing on the files, such as verifying the file type, the file size and the security.
And step four, extracting characteristic data, namely finally, based on the analyzed parameters and request header information, extracting key characteristic data by the system, evaluating the complexity of a data structure (such as nested layer number), and whether specific encryption processing (such as HTTPS (hypertext transfer protocol secure system) and TLS (transport layer security) encryption) is needed or not, and preparing subsequent protocol matching and data processing.
The analysis system decomposes and analyzes the data characteristics through detailed steps, and ensures the accuracy and the safety of data processing. From the parameter type and format to request header information, to file processing and characteristic data extraction, each step is strictly controlled and the data processing flow is optimized. The process not only improves the efficiency and accuracy of data processing, but also lays a solid foundation for subsequent protocol matching and data processing, and enhances the overall performance and user experience of the system.
Wherein, the specific steps of detecting the system-calculating the characteristic data weight and matching the protocol in the S3 are as follows:
Firstly, carrying out quantitative evaluation on each analyzed parameter characteristic, and distributing corresponding weight values according to importance of each analyzed parameter characteristic, wherein the weights are used for subsequently evaluating matching degrees of different protocols and current requests.
Step two, a weight evaluation system is established, the calculated characteristic weight is compared with the protocol characteristic, and the matching degree score of each protocol and the current request is calculated;
And step three, intelligent protocol matching, namely intelligently selecting a protocol mode with highest matching degree in an available protocol set by utilizing weight information and a first round of detection modes (such as interface identification hash searching, latest use of cache and other optimization strategies) so as to process the current request.
The detection system remarkably improves service efficiency and accuracy by accurately calculating characteristic data weight and intelligently matching with a protocol. The weight evaluation system ensures that the characteristics of each parameter are properly considered, and the protocol matching accuracy is optimized. And the intelligent matching is combined with a first round-robin strategy to quickly locate the optimal protocol, so that the processing delay is reduced. The flexibility and adaptability of the system are enhanced, the resource utilization is optimized, and smoother and efficient service experience is brought to users.
Wherein, in S4, the service system-executing the request and obtaining the response means that based on the matched best protocol mode, the system initiates the request to the service end through the corresponding application layer interface (for example RESTfu l API) and the transport layer interface (for example, TCP connection or WebSocket session), and then, the system listens and receives the response data from the service end, where the data includes the status code in detail to indicate the request processing result, the response header provides additional metadata information, and the response body includes actual data content for subsequent processing.
Service system-executing request and obtaining response, accurately initiating request by optimal protocol, ensuring high-efficiency data transmission. And receiving detailed response data, including a status code, a response head and a body, and providing comprehensive information support. The flow optimizes the request processing efficiency, enhances the communication capacity between systems, lays a solid foundation for the subsequent processing of data, and improves the overall service quality and the user experience.
The step S5 of packaging the system, which is to arrange the returned data, is to firstly process the content of the response body in detail after receiving the response of the server, and to perform corresponding analysis operation according to the actual format (such as JSON or XML) of the response body so as to ensure the accuracy and usability of the data, and after finishing the arrangement of the content, the system further packages the arranged data according to the format agreed in advance, and in the packaging process, adds a custom response head to transmit additional information, or adjusts the data structure to better adapt to the processing logic of the client. The series of operations aim to optimize the presentation mode of the data and improve the use convenience and the data processing efficiency of the client.
Packaging system-collating returned data ensures that data accuracy is available, optimizing content accuracy by parsing the response body format (e.g., JSON/XML). And a custom response head and an adjustment structure are added during packaging, so that the data adaptability is enhanced, and the client processing is facilitated. The process not only improves the data processing efficiency, but also promotes seamless butt joint between systems, and enhances the user experience and the system flexibility.
The step of returning the user in S6 means that after the system finishes data encapsulation, the processing result is returned to the user through HTTP, RPC and TCP high-efficiency protocols immediately, so that timely transmission and availability of the data are ensured. Meanwhile, the system performance is optimized, the maintenance efficiency is improved, the system thoroughly records key information in the whole request processing process, such as the request initiating time, the server processing time and the final response state, the log information provides precious data support for subsequent performance analysis, the complexity of problem investigation is greatly simplified, and the system is protected for stable operation.
After data encapsulation, the system returns the processing result in time through the high-efficiency protocol, and the data aging and usability are ensured. The whole process of log record request is thoroughly recorded, data support is provided for performance optimization, problem investigation is simplified, and system stability is enhanced. The measures not only promote user experience, but also optimize system performance and maintenance efficiency, and provide solid guarantee for stable operation of the system.
Wherein, the specific steps of monitoring and optimizing in S7 are as follows:
the performance monitoring method comprises the steps of implementing a comprehensive performance monitoring system, collecting and analyzing response time and processing efficiency data of the system in real time, and timely finding potential performance bottlenecks or abnormal behaviors through setting a threshold value and an alarm mechanism;
Step two, problem analysis and bottleneck positioning, namely after the performance problem is found, deep problem analysis is carried out, and specific links or components causing the performance bottleneck are accurately positioned by using log, stack tracking and performance analysis tool means;
And step three, protocol and service optimization, namely carrying out targeted optimization on a protocol matching algorithm and a service calling mode according to the performance monitoring result and the problem analysis conclusion. This may include improving the algorithm logic, optimizing the data transmission format, adjusting the service deployment architecture or introducing new efficient technology stacks, etc., to improve overall performance and user experience.
By implementing three steps of performance monitoring, problem analysis and bottleneck positioning and protocol and service optimization, the response speed and processing efficiency of the system can be remarkably improved, the performance bottleneck can be rapidly positioned and solved by real-time monitoring and early warning, protocol matching and service calling are optimized, the stability and reliability of the system are enhanced, technical iteration and innovation are promoted, and smoother and efficient use experience is brought to users.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The intelligent testing method for the automatic testing API interface is characterized by comprising the following specific steps of:
s1, information input and position identification, namely, user input request, system analysis URL positioning service interface and extraction of service identification information;
s2, analyzing the system-decomposing data and analyzing the data characteristics, namely analyzing the request parameters, extracting characteristic data comprising types, formats, sizes, request heads and files, and preparing for protocol matching;
s3, detecting a system, namely calculating characteristic data weight and matching a protocol, namely calculating the characteristic weight, intelligently matching the protocol, combining the weight with the round-robin detection, and selecting an optimal protocol to process a request;
s4, a service system-executing request and acquiring response, wherein the service system-executing request and acquiring response is matched with a protocol access interface, sends the request and receives a server side status code, a header and volume data;
s5, packaging the system, namely finishing returned data, namely processing a response body, analyzing a format, packaging the data and ensuring the usability of a client;
S6, returning to a user, namely sending package data, recording log information, and analyzing the boosting performance and checking problems;
And S7, monitoring and optimizing, namely monitoring performance, optimizing protocol matching, and improving system efficiency and user experience.
2. The intelligent testing method of the automated testing API interface of claim 1, wherein the specific steps of information input and location identification in S1 are as follows:
step one, submitting a request, namely submitting a request comprising a request URL, a request method and a request parameter through an interface or an API interface by a user;
analyzing the URL and extracting information, namely after the system receives the request, analyzing the URL of the request to identify the specific service interface position, and extracting relevant service identification information in the process.
3. The method for intelligently testing the automated test API according to claim 1, wherein the specific steps of analyzing the system-decomposed data and analyzing the data characteristics in S2 are as follows:
firstly, analyzing each parameter in the request one by a system, determining the data type and format of the request, and checking whether the size of the parameter accords with a preset limit;
analyzing the request header, namely analyzing request header information such as Content-Type by a system to know the media Type of a request body, and verifying the identity and authority of the requester by Authorization;
Step three, processing the request files, wherein if the request contains files, the system can perform necessary processing on the files, such as verifying the file type, size and security;
and step four, extracting characteristic data, namely finally, based on the analyzed parameters and request header information, extracting key characteristic data by the system, evaluating the complexity of a data structure, and whether specific encryption processing is needed or not, and preparing for subsequent protocol matching and data processing.
4. The intelligent testing method for the automated testing API according to claim 1, wherein the specific steps of detecting the system-calculating the characteristic data weight and matching the protocol in S3 are as follows:
firstly, carrying out quantitative evaluation on each analyzed parameter characteristic, and distributing corresponding weight values according to importance of the parameter characteristic;
Step two, a weight evaluation system is established, the calculated characteristic weight is compared with the protocol characteristic, and the matching degree score of each protocol and the current request is calculated;
And step three, intelligent protocol matching, namely intelligently selecting a protocol mode with highest matching degree by using the weight information and a first round of detection mode in a protocol set so as to process the current request.
5. The intelligent testing method of the automated testing API according to claim 1, wherein the step S4 of servicing the system-executing the request and obtaining the response means that the system initiates the request to the service terminal through the corresponding application layer interface and transport layer interface based on the matched best protocol mode, and then the system listens to and receives the response data from the service terminal, wherein the data includes the status code in detail to indicate the result of the request processing, the response header provides additional metadata information, and the response body includes actual data content.
6. The intelligent testing method of the automated testing API interface of claim 1, wherein the step S5 of packaging the system-sorting the returned data is characterized in that after receiving the response of the server, the system firstly carries out detailed processing on the content of the response body, carries out corresponding analysis operation according to the actual format of the response body, packages the sorted data according to the format appointed in advance after finishing content sorting, and adds a custom response head to transmit additional information in the packaging process to adjust the data structure so as to be convenient for better adapting to the processing logic of the client.
7. The intelligent testing method of the automated testing API interface of claim 1, wherein the returning to the user in S6 means that the processing result is returned to the user through HTTP, RPC and TCP high-efficiency protocols immediately after the system completes data encapsulation, and meanwhile, the system performance is optimized, the maintenance efficiency is improved, and the system thoroughly records key information in the whole request processing process, such as the request initiating time, the server processing time and the final response state.
8. The intelligent test method for the automated test API according to claim 1, wherein the specific steps of monitoring and optimizing in S7 are as follows:
the performance monitoring method comprises the steps of implementing a comprehensive performance monitoring system, collecting and analyzing response time and processing efficiency data of the system in real time, and timely finding potential performance bottlenecks or abnormal behaviors through setting a threshold value and an alarm mechanism;
Step two, problem analysis and bottleneck positioning, namely after the performance problem is found, deep problem analysis is carried out, and specific links or components causing the performance bottleneck are accurately positioned by using log, stack tracking and performance analysis tool means;
and step three, protocol and service optimization, namely, carrying out targeted optimization on a protocol matching algorithm and a service calling mode according to a performance monitoring result and a problem analysis conclusion, wherein the targeted optimization comprises the steps of improving algorithm logic, optimizing a data transmission format, adjusting a service deployment architecture or introducing a new high-efficiency technical stack.
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