CN111831537A - High-efficiency performance test method for artificial intelligence development system - Google Patents
High-efficiency performance test method for artificial intelligence development system Download PDFInfo
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- CN111831537A CN111831537A CN201910312035.1A CN201910312035A CN111831537A CN 111831537 A CN111831537 A CN 111831537A CN 201910312035 A CN201910312035 A CN 201910312035A CN 111831537 A CN111831537 A CN 111831537A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3688—Test management for test execution, e.g. scheduling of test suites
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
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- G06F11/3684—Test management for test design, e.g. generating new test cases
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Abstract
A high-efficiency performance test method for an artificial intelligence development system relates to the technical field of artificial intelligence. The method comprises a test data acquisition step, wherein the test data acquisition step comprises the step of acquiring scene identification data, the scene identification data comprises a database file, and the database file comprises a picture and video combination; a test scene generation step, wherein the test scene generation step comprises the steps of extracting elements from a database file and generating a test scene by the elements according to a test system algorithm; generating a development system scene, wherein the development system scene generating step comprises the step of generating corresponding development scenes by elements in the database file according to an algorithm of a development system; and comparing, wherein the comparing step comprises the steps of acquiring artificial intelligence data in the test scene as comparison data, and judging whether the comparison data generated by the development scene and the comparison data generated by the test scene are compared in numerical value to obtain the accuracy. The intelligent artificial development system can be tested, the testing efficiency is high, the workload of testing personnel is reduced, and the working efficiency is improved.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a high-efficiency performance testing method of an artificial intelligence development system.
Background
Artificial Intelligence (Artificial Intelligence), abbreviated in english as AI. The method is a new technical science for researching and developing theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.
Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a manner similar to human intelligence, a field of research that includes robotics, language recognition, image recognition, natural language processing, and expert systems, among others. Since the birth of artificial intelligence, theories and technologies become mature day by day, and application fields are expanded continuously, so that science and technology products brought by the artificial intelligence in the future can be assumed to be 'containers' of human intelligence. The artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but can think like a human, and can also exceed human intelligence.
Artificial intelligence is a gate-challenging science that people who work must understand computer knowledge, psychology and philosophy. Artificial intelligence is a science that includes a very broad spectrum of fields, such as machine learning, computer vision, etc., and in general, one of the main goals of artificial intelligence research is to make machines competent for complex tasks that usually require human intelligence to complete. But the understanding of this "complex work" is different for different times and for different people.
At present, when an artificial intelligent development system is tested, the workload of testers is large, the time cost required to be spent is high, the limitation is large, and the testing working efficiency is low.
Disclosure of Invention
The invention aims to provide a high-efficiency performance testing method of an artificial intelligence development system, aiming at the defects and shortcomings of the prior art, and the method can be used for solving the defects that the workload of testers is large, the time cost required to be spent is high, the limitation is large, and the testing work efficiency is low when the artificial intelligence development system is tested at present.
In order to achieve the purpose, the invention adopts the following technical scheme: the method comprises a test data acquisition step, wherein the test data acquisition step comprises the step of acquiring a plurality of scene identification data, the scene identification data comprises at least one database file, and the database file comprises a plurality of combinations of pictures and videos;
generating a test scene, wherein the test scene generating step comprises the steps of sequentially extracting elements from the database file and generating corresponding test scenes by the elements according to an algorithm of a test system;
generating a development system scene, wherein the development system scene generating step comprises the step of generating corresponding development scenes by elements in a database file according to an algorithm of a development system;
and comparing, wherein the comparing step comprises the steps of acquiring artificial intelligence data in the test scene as comparison data, and judging that the comparison between the data generated by the development scene and the comparison data generated by the test scene is carried out to obtain the accuracy.
Further, the method also comprises a checking step, wherein the checking step carries out numerical value secondary comparison on the data generated by the development scene in the comparing step and the comparison data generated by the test scene, and confirms the accuracy rate obtained in the comparing step, and if the numerical value is consistent, the checking is finished.
Further, the test scene is created by logging in a browser, and pictures and videos in the database file are captured from the cloud database in an alternating mode, specifically, one picture is matched with one video.
Further, the test scenario generation step specifically includes acquiring a test account, acquiring a database file containing at least one problem requirement of the artificial intelligence development system, and matching the problem requirement with a related artificial intelligence development system.
Further, the comparing step specifically includes acquiring a comparison account, acquiring a corresponding comparison system including at least one of a requirement and a problem generated according to big data, and generating the requirement and the problem according to the requirement and the problem.
The working principle of the invention is as follows: after various pictures and videos are manually collected, the pictures and the videos are marked and then uploaded to a cloud server to produce a database file, a test scene system is logged in through a browser, and the test scene system captures related pictures and videos from the cloud server; logging in a development system and calling out the development scene corresponding to the test scene of the development system correspondingly, logging in a comparison system through a comparison account, obtaining at least one database file of problem requirements of the artificial intelligent development system by the comparison system, matching and comparing the problem requirements with the artificial intelligent development system and the test development scene, generating accuracy, and realizing high-efficiency performance test of the artificial intelligent development system.
After the technical scheme is adopted, the invention has the beneficial effects that: the test system is reasonable in design, can test the artificial intelligence development system, is high in test efficiency, can reduce the workload of testers, and effectively improves the work efficiency of the artificial intelligence development system.
Detailed Description
The technical scheme adopted by the specific implementation mode is as follows: it comprises
Step 1:
a test data acquisition step, wherein the test data acquisition step comprises the steps of acquiring a plurality of scene identification data, the scene identification data comprises at least one database file, and the database file comprises a plurality of combinations of pictures and videos; the database file is stored in the cloud server, the related data are uploaded through intelligent marking of pictures and videos, and the cloud server can access the related data;
step 2:
generating a test scene, wherein the test scene generating step comprises the steps of sequentially extracting elements from the database file and generating corresponding test scenes by the elements according to an algorithm of a test system;
and step 3:
generating a development system scene, wherein the development system scene generating step comprises the step of generating corresponding development scenes by elements in a database file according to an algorithm of a development system;
and 4, step 4:
and comparing, wherein the comparing step comprises the steps of acquiring artificial intelligence data in the test scene as comparison data, and judging that the comparison between the data generated by the development scene and the comparison data generated by the test scene is carried out to obtain the accuracy.
And 5:
and a checking step, wherein the data generated by the development scene in the comparing step and the comparison data generated by the test scene are subjected to numerical value secondary comparison, and are confirmed with the accuracy obtained in the comparing step, and if the numerical values are consistent, the checking is finished.
When the test scene is created, the created test scene is logged in a test scene system through a login browser, the test scene system accesses a cloud database, and pictures and videos in a database file are captured alternately from the cloud database, specifically, one picture is matched with one video.
When a test scene is created, the test scene generation step specifically comprises the steps of obtaining a test account number, logging in and creating the test scene through the test account number, obtaining a database file containing at least one problem requirement of the artificial intelligence development system, and matching the problem requirement with a related artificial intelligence development system.
When data comparison is carried out, the comparison step specifically comprises the steps of obtaining a comparison account number, obtaining at least one requirement and problem generated according to big data, and obtaining a corresponding comparison system generated according to the requirement and the problem.
After various pictures and videos are manually collected, the pictures and the videos are marked and then uploaded to a cloud server to produce a database file, a test scene system is logged in through a browser, and the test scene system captures related pictures and videos from the cloud server; logging in a development system and calling out the development scene corresponding to the test scene of the development system correspondingly, logging in a comparison system through a comparison account, obtaining at least one database file of problem requirements of the artificial intelligent development system by the comparison system, matching and comparing the problem requirements with the artificial intelligent development system and the test development scene, generating accuracy, and realizing high-efficiency performance test of the artificial intelligent development system.
The above description is only for the purpose of illustrating the technical solutions of the present invention and not for the purpose of limiting the same, and other modifications or equivalent substitutions made by those skilled in the art to the technical solutions of the present invention should be covered within the scope of the claims of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (5)
1. A high-efficiency performance test method of an artificial intelligence development system is characterized by comprising the following steps: the method comprises a test data acquisition step, wherein the test data acquisition step comprises the step of acquiring a plurality of scene identification data, the scene identification data comprises at least one database file, and the database file comprises a plurality of combinations of pictures and videos;
generating a test scene, wherein the test scene generating step comprises the steps of sequentially extracting elements from the database file and generating corresponding test scenes by the elements according to an algorithm of a test system;
generating a development system scene, wherein the development system scene generating step comprises the step of generating corresponding development scenes by elements in a database file according to an algorithm of a development system;
and comparing, wherein the comparing step comprises the steps of acquiring artificial intelligence data in the test scene as comparison data, and judging that the comparison between the data generated by the development scene and the comparison data generated by the test scene is carried out to obtain the accuracy.
2. The method for testing the high efficiency performance of the artificial intelligence development system according to claim 1, wherein: the method also comprises a checking step, wherein the checking step carries out secondary comparison of numerical values on the data generated by the development scene in the comparing step and the comparison data generated by the test scene, and confirms the numerical values with the accuracy obtained in the comparing step, and if the numerical values are consistent, the checking is finished.
3. The method for testing the high efficiency performance of the artificial intelligence development system according to claim 1, wherein: the test scene is created by logging in a browser, and pictures and videos in the database file are captured alternately from the cloud database, specifically, one picture is matched with one video.
4. The method for testing the high efficiency performance of the artificial intelligence development system according to claim 1, wherein: the test scene generation step specifically comprises the steps of obtaining a test account, obtaining a database file containing at least one problem requirement of the artificial intelligence development system, and matching the problem requirement with a related artificial intelligence development system.
5. The method for testing the high efficiency performance of the artificial intelligence development system according to claim 1, wherein: the comparing step specifically comprises the steps of obtaining a comparison account number, obtaining at least one requirement and problem generated according to big data, and generating a corresponding comparison system according to the requirement and the problem.
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Citations (3)
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| CN104809062A (en) * | 2015-04-22 | 2015-07-29 | 北京京东尚科信息技术有限公司 | Test method and system of artificial intelligence answering system |
| CN109447384A (en) * | 2018-08-27 | 2019-03-08 | 深圳壹账通智能科技有限公司 | Verification method, device, equipment and the storage medium of air control system |
| CN109542765A (en) * | 2018-10-18 | 2019-03-29 | 深圳壹账通智能科技有限公司 | Database script verification method, device, computer equipment and storage medium |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104809062A (en) * | 2015-04-22 | 2015-07-29 | 北京京东尚科信息技术有限公司 | Test method and system of artificial intelligence answering system |
| CN109447384A (en) * | 2018-08-27 | 2019-03-08 | 深圳壹账通智能科技有限公司 | Verification method, device, equipment and the storage medium of air control system |
| CN109542765A (en) * | 2018-10-18 | 2019-03-29 | 深圳壹账通智能科技有限公司 | Database script verification method, device, computer equipment and storage medium |
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