CN113656324B

CN113656324B - Full-link test method, device, equipment and medium for disease input and decision

Info

Publication number: CN113656324B
Application number: CN202111012757.9A
Authority: CN
Inventors: 周珍珠; 彭晶
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2021-08-31
Filing date: 2021-08-31
Publication date: 2023-08-22
Anticipated expiration: 2041-08-31
Also published as: CN113656324A

Abstract

The invention relates to the field of artificial intelligence and testing, and provides a full-link testing method, device, equipment and medium for disease input and decision, which can realize the configurability of a testing environment by creating a configuration file, realize the unified management of case pictures through a dictionary, lead the disease test to be more universal, directly locate corresponding interfaces through uniform resource locator information to execute AI auxiliary input, avoid the problem that the normal execution of the test is influenced by overlarge byte stream objects, and further avoid the problem that the return time consumption is greatly different from the time consumption of actual link use, thereby improving the testing effect, realizing the full-link test for AI auxiliary input and intelligent decision by building a common interface testing framework, realizing the multiplexing of data between the AI auxiliary input test and the intelligent decision test, and further improving the testing efficiency. In addition, the present invention relates to blockchain techniques, and the mapping table may be stored in a blockchain node.

Description

Full-link test method, device, equipment and medium for disease input and decision

Technical Field

The invention relates to the technical field of artificial intelligence and testing, in particular to a full-link testing method, device, equipment and medium for disease input and decision.

Background

In the nuclear insurance claim project, AI (Artificial Intelligence ) technologies such as OCR (Optical Character Recognition ), NLP (Natural Language Processing, natural language processing), knowledge maps and the like are deeply fused with big data to create an intelligent solution of nuclear insurance claim, support functions such as intelligent collection, intelligent input, intelligent audit, intelligent air control and the like, and construct a new generation nuclear insurance claim system with better customer experience, more accurate risk recognition and higher operation efficiency.

The most core functions are AI auxiliary input and intelligent decision, so that full-link test is needed to be carried out on the AI auxiliary input and intelligent decision in order to ensure the effectiveness of the AI auxiliary input and intelligent decision.

However, in the existing test scheme, the Postman or Jmeter interface test tool is mainly used for recording operation, when the number of pictures is relatively large, the produced byte stream is relatively large, and if the maximum value of the Postman request content limit is exceeded, the test cannot be continuously executed. In addition, the AI auxiliary input and the intelligent decision are respectively tested, and the sharing of data is not realized in the test process, so that the mapping relation between the byte stream and the original image cannot be automatically recorded, manual maintenance is needed, and the byte stream object is required to be regenerated each time the diseases of different medical records are tested. In addition, in the testing process, along with the increase of the number of diseases, the manual testing working amount of carrying out full link on each disease is large, the testing efficiency is low, and meanwhile, the time consumed by Postman test in return is greatly different from the time consumed by actual link use, so that the testing efficiency is further influenced.

Disclosure of Invention

The embodiment of the invention provides a full-link test method, device, equipment and medium for disease input and decision, which aim to solve the problems of poor test effect and low efficiency of full-link test for disease AI auxiliary input and intelligent decision.

In a first aspect, an embodiment of the present invention provides a full link testing method for disease entry and decision, including:

responding to a test request, and determining a test environment and a disease to be tested according to the test request;

acquiring a pre-established configuration file, and generating target uniform resource locator information according to the test environment and the configuration file;

obtaining a pre-configured dictionary, and generating a target address according to the disease to be tested and the dictionary;

the method comprises the steps of connecting to the target address, and acquiring a picture set to be processed from the target address according to the test request;

converting each picture to be processed in the picture set to be processed into a byte stream object;

determining an AI auxiliary input interface and an intelligent decision interface according to the target uniform resource locator information;

transmitting a byte stream object of each picture to be processed to the AI auxiliary input interface, receiving data returned by the AI auxiliary input interface as a target AI auxiliary input result of each picture to be processed, and recording a target identifier of the picture to be processed corresponding to the target AI auxiliary input result of each picture to be processed;

Transmitting a target AI auxiliary input result and a target identifier of each picture to be processed to the intelligent decision interface, and receiving data returned by the intelligent decision interface as a target intelligent decision result of each picture to be processed;

and calling a pre-configured mapping table, checking the target AI auxiliary input result and the target intelligent decision result according to the mapping table, and generating a test result.

According to a preferred embodiment of the present invention, the generating target url information according to the test environment and the configuration file includes:

reading a target field from the configuration file by using a read-write configuration class as a target IP and a target port corresponding to the test environment;

extracting general interface information from the configuration file;

and splicing the universal interface information, the target IP and the target port to obtain the target uniform resource locator information.

According to a preferred embodiment of the present invention, before the acquiring the pre-configured dictionary, the method further comprises:

obtaining case pictures from a configuration database at preset time intervals, and obtaining disease names corresponding to the case pictures;

dividing case pictures with the same disease name into a group to obtain at least one case picture group;

Storing the at least one case picture group to a designated folder, naming each case picture group according to the disease name corresponding to each case picture group, and obtaining at least one subfolder;

configuring codes of case pictures contained under each subfolder;

and acquiring a catalog corresponding to each case picture, and generating the dictionary according to the catalog.

According to a preferred embodiment of the invention, the method further comprises:

acquiring the response time of the AI auxiliary input interface to the byte stream object of each picture to be processed from an execution log as the first response time of each picture to be processed, and acquiring the response time of the intelligent decision interface to the target AI auxiliary input result and the target identifier of each picture to be processed as the second response time of each picture to be processed;

when the first response time of the picture to be processed is detected to be greater than or equal to a first configuration time threshold value and/or the second response time of the picture to be processed is detected to be greater than or equal to a second configuration time threshold value, determining the detected picture to be processed as a target picture;

and skipping verification of the target AI auxiliary input result and the target intelligent decision result of the target picture, and generating early warning information according to the target picture.

According to a preferred embodiment of the present invention, before the retrieving the pre-configured mapping table, the method further comprises:

acquiring historical test data according to a configured time period;

acquiring a mapping relation between an AI auxiliary input result and an intelligent decision result from the historical test data;

establishing a mapping table according to the mapping relation between the acquired AI auxiliary input result and the intelligent decision result;

when a test result of a new disease is detected, acquiring a mapping relation between an AI auxiliary input result and an intelligent decision result corresponding to the new disease from the test result of the new disease;

and maintaining a mapping relation between the AI auxiliary input result and the intelligent decision result corresponding to the newly added disease to the mapping table.

According to a preferred embodiment of the present invention, after the generating of the test result, the method further comprises:

acquiring an execution log in the test process;

acquiring the total response time of the AI auxiliary input interface in the data transmission process from the execution log, and acquiring the total response time of the intelligent decision interface in the data transmission process;

calculating the sum of the total response time of the AI auxiliary input interface in the data transmission process and the total response time of the intelligent decision interface in the data transmission process as the total interface consuming time;

Recording a byte stream object of each picture to be processed and a target identifier of each picture to be processed;

generating a visual target file according to each picture to be processed, the byte stream object of each picture to be processed, the target identifier of each picture to be processed, the total interface time consumption and the test result;

and calling a configuration library to send the target file to a designated mailbox.

when the test result shows that the target AI auxiliary input result and the corresponding target intelligent decision result do not pass the verification, obtaining a picture to be processed which does not pass the verification;

and deleting the picture to be processed which does not pass the verification from the dictionary.

In a second aspect, embodiments of the present invention provide a full link testing device for disease entry and decision making, comprising:

the determining unit is used for responding to the test request, determining a test environment and a disease to be tested according to the test request;

the generating unit is used for acquiring a pre-created configuration file and generating target uniform resource locator information according to the test environment and the configuration file;

the generating unit is further used for acquiring a pre-configured dictionary and generating a target address according to the disease to be tested and the dictionary;

The acquisition unit is used for being connected to the target address and acquiring a picture set to be processed from the target address according to the test request;

the conversion unit is used for converting each picture to be processed in the picture set to be processed into a byte stream object;

the determining unit is also used for determining an AI auxiliary input interface and an intelligent decision interface according to the target uniform resource locator information;

the transmission unit is used for transmitting the byte stream object of each picture to be processed to the AI auxiliary input interface, receiving data returned by the AI auxiliary input interface as a target AI auxiliary input result of each picture to be processed, and recording a target identifier of the picture to be processed corresponding to the target AI auxiliary input result of each picture to be processed;

the transmission unit is further used for transmitting a target AI auxiliary input result and a target identifier of each picture to be processed to the intelligent decision interface, and receiving data returned by the intelligent decision interface as a target intelligent decision result of each picture to be processed;

and the verification unit is used for calling a pre-configured mapping table, verifying the target AI auxiliary input result and the target intelligent decision result according to the mapping table, and generating a test result.

In a third aspect, an embodiment of the present invention further provides a computer apparatus, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the full link test method for disease entry and decision as described in the first aspect when the computer program is executed.

In a fourth aspect, embodiments of the present invention further provide a computer readable storage medium, wherein the computer readable storage medium stores a computer program, which when executed by a processor, causes the processor to perform the full link test method for disease entry and decision as described in the first aspect above.

The embodiment of the invention provides a full-link test method, device, equipment and medium for disease input and decision, which can respond to a test request, determine a test environment and diseases to be tested according to the test request, acquire a pre-established configuration file, generate target uniform resource locator information according to the test environment and the configuration file, realize the configurability of the test environment by creating the configuration file, open different test environments, enable different test environments to share a uniform test frame, acquire a pre-configured dictionary, generate a target address according to the diseases to be tested and the dictionary, realize uniform management of case pictures through the pre-established dictionary, enable the disease test to be more universal, support the test of various diseases through maintaining the dictionary, reduce the test time, further accelerate the efficiency of test and production verification, connect to the target address, acquire a picture set to be processed from the target address according to the test request, convert each picture to be processed in the picture set into a byte stream, enable the different test environments to share a uniform test frame, acquire a pre-configured dictionary, generate a target address according to the diseases and the target address, enable the AI to be processed, and send the AI to the auxiliary interface as an auxiliary interface, and the AI to be processed by the auxiliary interface, the AI is used as an auxiliary interface, the auxiliary interface to be directly used for the AI input and the auxiliary interface, and the AI input and the AI is used as an auxiliary interface to be processed to be directly corresponding to the auxiliary interface to be processed, the method and the device can effectively avoid the problem that the normal execution of the test is influenced by oversized byte stream objects, simultaneously avoid the problem that the time consumption returned by using the Postman test is greatly different from the time consumption used by an actual link, further improve the test effect, transmit the target AI auxiliary input result and the target identifier of each picture to be processed to the intelligent decision interface, receive the data returned by the intelligent decision interface as the target intelligent decision result of each picture to be processed, call a pre-configured mapping table, check the target AI auxiliary input result and the target intelligent decision result according to the mapping table, generate the test result, realize the full-link test of AI auxiliary input and intelligent decision by constructing a common interface test frame, and realize the multiplexing of data between the AI auxiliary input test and the intelligent decision test, thereby improving the test efficiency.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flow chart of a full-link test method for disease input and decision according to an embodiment of the present invention;

FIG. 2 is a schematic block diagram of a full-link testing device for disease entry and decision making provided by an embodiment of the present invention;

fig. 3 is a schematic block diagram of a computer device according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. 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.

It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

Referring to fig. 1, a flow chart of a full-link testing method for disease input and decision according to an embodiment of the present invention is shown.

S10, responding to a test request, and determining a test environment and a disease to be tested according to the test request.

In this embodiment, the test request may be triggered by an associated worker, such as a tester, developer, or the like.

In this embodiment, the test environment may include, but is not limited to: an environment corresponding to a test task, an environment corresponding to a production task, and the like.

In this embodiment, the diseases to be tested may include, but are not limited to, thyroiditis, appendicitis, and the like.

S11, acquiring a pre-created configuration file, and generating target uniform resource locator information according to the test environment and the configuration file.

In this embodiment, the configuration file is configured according to different test environments and interfaces.

By creating the configuration file, the embodiment realizes the configurability of the test environment, opens up different test environments, and enables different test environments to share a unified test framework.

In at least one embodiment of the present invention, the generating target uniform resource locator information according to the test environment and the configuration file includes:

Extracting general interface information from the configuration file;

The read-write configuration class may be a configparer class.

For example: assuming that the configuration file is cfg_trace.ini, configuring environment information of a test environment and interface information required by a test in the file, wherein the configuration file is divided into three parts: a common portion for storing general interface information such as URI (Uniform Resource Identifier ) of various core claim item interfaces (e.g.,/vas/ai_plane/media_report_recg_elis_ uws); a test part for configuring the IP and port of the test environment; prd section for configuring IP and ports of the production environment. The required fields are parsed from the configuration file by using a read-write configuration class, and then the target uniform resource locator information, for example, the target uniform resource locator information generated according to the test request, such as the medical_recg_els_uws_url=http:// 192.168.16.123/vas/ai_planar/media_report_recg_elis_ UWS, is spliced.

S12, acquiring a pre-configured dictionary, and generating a target address according to the disease to be tested and the dictionary.

In at least one embodiment of the present invention, before the obtaining the pre-configured dictionary, the method further includes:

configuring codes of case pictures contained under each subfolder;

The preset time interval may be configured in a user-defined manner, for example: every 30 days.

The configuration database may be a database of a designated hospital, etc., and the present invention is not limited thereto.

Through the embodiment, unified management of case pictures can be realized through the pre-constructed dictionary, so that disease tests are more generalized, and tests on various diseases can be supported through maintaining the dictionary, so that the test time is shortened, and the test and production verification efficiency is further improved.

Through verification, through universalization of disease test, the test time can be effectively reduced, the full link of one disease can be tested after the original 13 minutes is reduced to 25 seconds, and the efficiency of test and production verification is improved.

In at least one embodiment of the present invention, the generating the target address according to the disease to be tested and the dictionary includes:

acquiring a disease name corresponding to the disease to be tested;

and inquiring in the dictionary according to the disease name corresponding to the disease to be tested to obtain the target address.

For example: by the destination address { 'basePath': 'D: users, documents, kernel, image-test, upper respiratory tract infection', 'dirInfo' [ '1', '2', '3', '4', '10' ], 1, 2, 3, 4, 10 case pictures under the upper respiratory tract infection subfolder can be obtained; by the destination address { ' basePath ': ' D: 1 st, 2 nd, 3 rd, 4 th, 5 th, 6 th, 7 th, 8 th, 9 th, 10 th, 11 th, 12 th case pictures under the thyrotropin subfolder can be obtained.

S13, connecting to the target address, and acquiring a picture set to be processed from the target address according to the test request.

In this embodiment, the image to be processed may be a medical image, and the type of the object included in the image to be processed is a focus, that is, a part of the body where a lesion occurs. Medical images refer to images of internal tissues taken in a non-invasive manner for medical or medical research, e.g., stomach, abdomen, heart, knee, brain, such as CT (Computed Tomography, electronic computed tomography), MRI (Magnetic Resonance Imaging ), US (ultra sonic), X-ray images, electroencephalograms, and images generated by medical instruments by optical photography lamps.

In at least one embodiment of the present invention, the obtaining the to-be-processed picture set from the target address according to the test request includes:

determining the number of case pictures to be acquired as a target number according to the test request;

and acquiring the case pictures of the target number from the target address as the pictures to be processed.

For example: when three case pictures need to be tested, the first three pictures or any three pictures can be obtained from the target address as the pictures to be processed.

S14, converting each picture to be processed in the picture set to be processed into a byte stream object.

In at least one embodiment of the present invention, the converting each of the set of pictures to be processed into a byte stream object includes:

starting a standard library base64 tool of python, and opening each picture to be processed in a binary mode;

and reading the file content of each picture to be processed, converting the file content of each picture to be processed into base64 codes, and converting each picture to be processed into byte stream objects.

S15, determining an AI auxiliary input interface and an intelligent decision interface according to the target uniform resource locator information.

In this embodiment, interface information may be obtained through the target url information, that is, the AI-assisted input interface and the intelligent decision interface may be further determined according to the interface information.

In this embodiment, the AI-assisted entry interface is capable of performing AI-assisted entry tasks, i.e., entering risk information for a case.

In this embodiment, the intelligent decision interface is configured to perform an intelligent decision task, that is, predict the disease level through the risk information of the entered case, and further determine the risk level of the application, so as to determine whether the application requirement of the insurance to be purchased is met.

S16, transmitting the byte stream object of each picture to be processed to the AI auxiliary input interface, receiving data returned by the AI auxiliary input interface as a target AI auxiliary input result of each picture to be processed, and recording a target identifier of the picture to be processed corresponding to the target AI auxiliary input result of each picture to be processed.

It should be noted that, in the conventional AI-assisted entry test scenario, the request body is filled with a testman or Jmeter interface test tool to perform AI-assisted entry operation, when the data volume of the case picture is large, if the generated byte stream is also large, the maximum value of the content limitation requested by the testman or Jmeter is exceeded, which results in the failure to execute the test.

In this embodiment, the generated url information is directly located to the corresponding interface, and the corresponding interface is used to perform AI auxiliary input, so that the problem that the normal execution of the test is affected due to the oversized byte stream object can be effectively avoided, and meanwhile, the problem that the return time consumption is greatly different from the time consumption of the actual link use when the Postman test is used is also avoided, and further the test effect is improved.

S17, transmitting the target AI auxiliary input result and the target identifier of each picture to be processed to the intelligent decision interface, and receiving data returned by the intelligent decision interface as a target intelligent decision result of each picture to be processed.

In the prior test scheme, the AI auxiliary input test and the intelligent decision test are separately executed, and the data of the AI auxiliary input test and the intelligent decision test are not universal, so that the test time is long and the efficiency is low.

According to the method, the common interface test framework is built, so that full-link testing of AI auxiliary input and intelligent decision making is realized, data sharing is performed between the AI auxiliary input test and the intelligent decision making test, multiplexing of data is realized, and further, the test efficiency is improved.

In at least one embodiment of the invention, the method further comprises:

The first configuration time threshold is an upper limit value of the response time of the AI auxiliary input interface, and if the upper limit value exceeds the first configuration time threshold, the response abnormality of the AI auxiliary input interface is indicated.

And the second configuration time threshold is an upper limit value of the response time of the intelligent decision interface, and if the second configuration time threshold is exceeded, the abnormal response of the intelligent decision interface is indicated.

Through the embodiment, the interface time consumption can be detected in real time in the test process, and the interface time consumption can be timely processed when the influence abnormality is found, so that the influence on the test time is avoided, and the test efficiency is further improved.

S18, a pre-configured mapping table is called, and the target AI auxiliary input result and the target intelligent decision result are checked according to the mapping table to generate a test result.

For example: the target AI auxiliary input result is hyperglycemia, the target intelligent decision is that diabetes mellitus is at risk, and the target AI auxiliary input result is applicable to the disclaimer of serious diseases. And if the test result is the same as the data in the mapping table, determining that the test result is the AI auxiliary input result and the intelligent decision result passes the test.

In at least one embodiment of the present invention, before the retrieving the pre-configured mapping table, the method further comprises:

acquiring historical test data according to a configured time period;

Through the implementation mode, the established mapping table is periodically maintained, and the mapping table is updated in time when new diseases exist, so that complete full-link testing is assisted.

Of course, in other embodiments, when the newly added disease does not respond to the test data, prompt information may be sent to the terminal device of the designated contact person, where the prompt information is used to prompt the designated contact person to upload the mapping relationship between the AI auxiliary input result and the intelligent decision result corresponding to the newly added disease.

In at least one embodiment of the present invention, the verifying the target AI-assisted entry result and the target intelligent decision result according to the mapping table includes:

inquiring a mapping relation between the target AI auxiliary input result and the target intelligent decision result from the mapping table;

when the mapping relation between the target AI auxiliary input result and the target intelligent decision result is queried in the mapping table, determining that the target AI auxiliary input result and the target intelligent decision result pass verification; or alternatively

And when the mapping relation between the target AI auxiliary input result and the target intelligent decision result is not queried in the mapping table, determining that the target AI auxiliary input result and the target intelligent decision result are not checked.

Through the implementation mode, the automatic full-link test for the AI auxiliary input and intelligent decision can be realized.

Through verification, since each link in the scheme shortens the test time, the test originally for 3 days can be shortened to be completed within 2 hours as a whole.

In at least one embodiment of the present invention, after the generating the test result, the method further comprises:

Acquiring an execution log in the test process;

The target file may be in an excel format.

For example: and storing each picture to be processed, the byte stream object of each picture to be processed, the target identifier of each picture to be processed, the total interface time consumption and the test result in excel by using an xlwt extension tool of python to obtain the target file.

The configuration library may be a third party library, such as an email.

The specified mailbox may include a mailbox of a tester, a mailbox of a developer, and the like, and may be configured in a customized manner according to different test scenarios.

In the embodiment, a series of log information in the test process is acquired, so that the problem is conveniently checked and positioned; the recorded total interface time consumption can effectively reflect the performance of the interface in the test process; the recorded byte stream object of each picture to be processed and the target identifier of each picture to be processed can realize multiplexing of the generated byte stream object, so that time loss caused by regeneration during each test is avoided; meanwhile, data such as test results are stored in a visual file format and sent to an execution mailbox, so that a user can check the data conveniently.

Through the implementation mode, the picture with problems can be prevented from being reused, and further the problem of recurrence on-line recurrence in the production process is effectively avoided.

It should be noted that, in order to further improve the security of the data and avoid the data from being tampered maliciously, the mapping table may be stored in the blockchain node.

According to the technical scheme, the invention responds to the test request, determines the test environment and the diseases to be tested according to the test request, acquires the pre-created configuration file, generates the target uniform resource locator information according to the test environment and the configuration file, realizes the configurability of the test environment by creating the configuration file, opens up different test environments, enables different test environments to share the unified test framework, acquires the pre-configured dictionary, generates the target address according to the diseases to be tested and the dictionary, realizes the unified management of case pictures through the pre-built dictionary, leads the disease test to be more universal, can support the test of various diseases by maintaining the dictionary, reduces the test time, further accelerates the efficiency of test and production verification, is connected to the target address, acquiring a to-be-processed picture set from the target address according to the test request, converting each to-be-processed picture in the to-be-processed picture set into byte stream objects, determining an AI auxiliary input interface and an intelligent decision interface according to the target uniform resource locator information, transmitting the byte stream object of each to-be-processed picture to the AI auxiliary input interface, receiving data returned by the AI auxiliary input interface as a target AI auxiliary input result of each to-be-processed picture, recording a target identifier of the to-be-processed picture corresponding to the target AI auxiliary input result of each to-be-processed picture, directly positioning the to the corresponding interface through the generated uniform resource locator information, executing AI auxiliary input by utilizing the corresponding interface, effectively avoiding the problem that the normal execution of the test is influenced by overlarge byte stream objects, meanwhile, the problem that the time consumption returned by using the Postman test is greatly different from the time consumption used by an actual link is avoided, the test effect is further improved, the target AI auxiliary input result and the target identifier of each picture to be processed are transmitted to the intelligent decision interface, the data returned by the intelligent decision interface are received as the target intelligent decision result of each picture to be processed, a pre-configured mapping table is called, the target AI auxiliary input result and the target intelligent decision result are checked according to the mapping table, the test result is generated, the common interface test framework is built, the full-link test of AI auxiliary input and intelligent decision is realized, the data sharing is realized between the AI auxiliary input test and the intelligent decision test, and the data multiplexing is further improved.

The embodiment of the invention also provides a disease input and decision all-link testing device which is used for executing any embodiment of the disease input and decision all-link testing method. Specifically, referring to fig. 2, fig. 2 is a schematic block diagram of a full-link testing device for disease entry and decision making according to an embodiment of the present invention.

As shown in fig. 2, the full-link test device 100 for disease entry and decision-making comprises: a determining unit 101, a generating unit 102, an acquiring unit 103, a converting unit 104, a transmitting unit 106, and a verifying unit 107.

In response to the test request, the determination unit 101 determines a test environment and a disease to be tested according to the test request.

The generating unit 102 obtains a pre-created configuration file, and generates target uniform resource locator information according to the test environment and the configuration file.

In at least one embodiment of the present invention, the generating unit 102 generating target uniform resource locator information according to the test environment and the configuration file includes:

extracting general interface information from the configuration file;

The read-write configuration class may be a configparer class.

The generating unit 102 acquires a pre-configured dictionary, and generates a target address according to the disease to be tested and the dictionary.

In at least one embodiment of the present invention, before the pre-configured dictionary is acquired, acquiring case pictures from a configuration database at intervals of a preset time, and acquiring disease names corresponding to the case pictures;

configuring codes of case pictures contained under each subfolder;

In at least one embodiment of the present invention, the generating unit 102 generates a target address according to the disease to be tested and the dictionary includes:

acquiring a disease name corresponding to the disease to be tested;

The obtaining unit 103 is connected to the target address, and obtains a to-be-processed picture set from the target address according to the test request.

In at least one embodiment of the present invention, the obtaining unit 103 obtaining the to-be-processed picture set from the target address according to the test request includes:

The conversion unit 104 converts each of the pictures to be processed in the picture set to a byte stream object.

In at least one embodiment of the present invention, the converting unit 104 converts each of the to-be-processed pictures in the to-be-processed picture set into a byte stream object includes:

The determining unit 101 determines an AI-assisted entry interface and an intelligent decision interface according to the target uniform resource locator information.

The transmission unit 106 transmits the byte stream object of each to-be-processed picture to the AI-assisted input interface, receives the data returned by the AI-assisted input interface as a target AI-assisted input result of each to-be-processed picture, and records a target identifier of the to-be-processed picture corresponding to the target AI-assisted input result of each to-be-processed picture.

The transmission unit 106 transmits the target AI auxiliary input result and the target identifier of each picture to be processed to the intelligent decision interface, and receives the data returned by the intelligent decision interface as the target intelligent decision result of each picture to be processed.

In at least one embodiment of the present invention, the response time of the AI-assisted entry interface to the byte stream object of each to-be-processed picture is obtained from the execution log as the first response time of each to-be-processed picture, and the response time of the intelligent decision interface to the target AI-assisted entry result and the target identifier of each to-be-processed picture is obtained as the second response time of each to-be-processed picture;

The verification unit 107 invokes a pre-configured mapping table, verifies the target AI-assisted entry result and the target intelligent decision result according to the mapping table, and generates a test result.

In at least one embodiment of the present invention, before the retrieving the pre-configured mapping table, historical test data is obtained according to a configured time period;

In at least one embodiment of the present invention, the verifying unit 107 verifies the target AI-assisted entry result and the target intelligent decision result according to the mapping table includes:

In at least one embodiment of the present invention, after the test result is generated, an execution log in the test process is obtained;

The target file may be in an excel format.

The configuration library may be a third party library, such as an email.

In at least one embodiment of the present invention, after the test result is generated, when the test result shows that the target AI auxiliary input result and the corresponding target intelligent decision result do not pass the verification, a picture to be processed which does not pass the verification is obtained;

According to the technical scheme, the invention responds to the test request, determines the test environment and the diseases to be tested according to the test request, acquires the pre-created configuration file, generates target uniform resource locator information according to the test environment and the configuration file, realizes the configurability of the test environment by creating the configuration file, opens different test environments, enables different test environments to share a unified test framework, acquires the pre-configured dictionary, generates a target address according to the diseases to be tested and the dictionary, realizes the unified management of case pictures through the pre-built dictionary, enables the disease test to be more universal, can support the test of various diseases by maintaining the dictionary, reduces the test time, further accelerates the efficiency of test and production verification, is connected to the target address, acquires a picture set to be processed according to the test request, converts each picture to be processed in the picture set into a word throttle object, determines an auxiliary interface and an intelligent interface according to the target uniform resource locator information, enables each picture to be processed to be transmitted to the corresponding AI and the auxiliary interface to be used as a main input interface, and the auxiliary interface is prevented from being used as a normal input result of the auxiliary interface, and the auxiliary interface is directly processed by the auxiliary interface, and the auxiliary input interface is prevented from being used as a normal input result of the input interface of the auxiliary interface to be executed, meanwhile, the problem that the time consumption returned by using the Postman test is greatly different from the time consumption used by an actual link is avoided, the test effect is further improved, the target AI auxiliary input result and the target identifier of each picture to be processed are transmitted to the intelligent decision interface, the data returned by the intelligent decision interface are received as the target intelligent decision result of each picture to be processed, a pre-configured mapping table is called, the target AI auxiliary input result and the target intelligent decision result are checked according to the mapping table, the test result is generated, the common interface test framework is built, the full-link test of AI auxiliary input and intelligent decision is realized, the data sharing is realized between the AI auxiliary input test and the intelligent decision test, and the data multiplexing is further improved.

The above-described disease entry and decision making full link test apparatus may be embodied in the form of a computer program which may be run on a computer device as shown in fig. 3.

Referring to fig. 3, fig. 3 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device 500 is a server, and the server may be a stand-alone server or a server cluster formed by a plurality of servers. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.

Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.

With reference to FIG. 3, the computer device 500 includes a processor 502, a memory, and a network interface 505, connected by a system bus 501, where the memory may include a storage medium 503 and an internal memory 504.

The storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, causes the processor 502 to perform the full link test method of disease entry and decision making.

The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.

The internal memory 504 provides an environment for the execution of a computer program 5032 in the storage medium 503, which computer program 5032, when executed by the processor 502, causes the processor 502 to perform the full link test method of disease entry and decision making.

The network interface 505 is used for network communication, such as providing for transmission of data information, etc. It will be appreciated by those skilled in the art that the architecture shown in fig. 3 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting of the computer device 500 to which the present inventive arrangements may be implemented, and that a particular computer device 500 may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

The processor 502 is configured to run a computer program 5032 stored in a memory, so as to implement the full-link test method for disease entry and decision according to the embodiment of the present invention.

Those skilled in the art will appreciate that the embodiment of the computer device shown in fig. 3 is not limiting of the specific construction of the computer device, and in other embodiments, the computer device may include more or less components than those shown, or certain components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may include only a memory and a processor, and in such embodiments, the structure and function of the memory and the processor are consistent with the embodiment shown in fig. 3, and will not be described again.

It should be appreciated that in an embodiment of the invention, the processor 502 may be a central processing unit (CentralProcessing Unit, CPU), the processor 502 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application SpecificIntegrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a nonvolatile computer readable storage medium or a volatile computer readable storage medium. The computer readable storage medium stores a computer program, wherein the computer program when executed by a processor implements the full-link test method for disease entry and decision-making disclosed by the embodiment of the invention.

The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus, device and unit described above may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein. Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the units is merely a logical function division, there may be another division manner in actual implementation, or units having the same function may be integrated into one unit, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.

The invention is operational with numerous general purpose or special purpose computer system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units may be stored in a storage medium if implemented in the form of software functional units and sold or used as stand-alone products. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, an optical disk, or other various media capable of storing program codes.

While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims

1. The full-link test method for disease input and decision-making is characterized by comprising the following steps:

2. The full link testing method of disease entry and decision making according to claim 1, wherein said generating target uniform resource locator information from said testing environment and said configuration file comprises:

extracting general interface information from the configuration file;

3. The full link test method of disease entry and decision making according to claim 1, wherein prior to the obtaining a pre-configured dictionary, the method further comprises:

configuring codes of case pictures contained under each subfolder;

4. The disease entry and decision making full link test method of claim 1, further comprising:

5. The full link testing method of disease entry and decision making according to claim 1, wherein prior to said retrieving a pre-configured mapping table, the method further comprises:

acquiring historical test data according to a configured time period;

6. The full link test method of disease entry and decision making according to claim 1, wherein after the generating test results, the method further comprises:

Acquiring an execution log in the test process;

7. The full link test method of disease entry and decision making according to claim 1, wherein after the generating test results, the method further comprises:

8. A full link testing device for disease entry and decision making, comprising:

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the full link test method of disease entry and decision making according to any of claims 1 to 7 when executing the computer program.

10. A computer readable storage medium, characterized in that it stores a computer program which, when executed by a processor, causes the processor to perform the full link test method of disease entry and decision making according to any of claims 1 to 7.