Automatic software test management system and method based on artificial intelligence

Abstract

The invention discloses a software automatic test management system and method based on artificial intelligence, and belongs to the technical field of artificial intelligence. A false propaganda module is arranged to identify commodities actually sold by merchants based on a deep learning algorithm, calculate differences between the commodities actually sold by the merchants and commodities propagandized by the merchants, and judge whether the merchants propagandize falsely; setting a merchant malicious drainage module to construct a malicious drainage judgment model, and judging whether the merchant is maliciously drained or not; an automatic test module is arranged to realize that one script adapts to multiple sets of environment scenes through a parameterization mechanism of the system and packaged diversified components; by setting a merchant false propaganda module and a merchant malicious drainage model to assess and monitor merchant behaviors and maintain the reputation of the platform, by setting an automatic test module and modularly managing test scenes, the scenes are combined according to specific test requirements to automatically output a test report, and normal operation of the system after multiple times of data debugging is guaranteed.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a software automatic test management system and method based on artificial intelligence. Background technique [0002] Due to the development of e-commerce such as Taobao, people are accustomed to online shopping without leaving home. In addition to the gradual development of various daily necessities and fresh food e-commerce, in 2019, the market transaction of China's fresh food e-commerce industry reached 270 billion yuan. In 2019 Year-on-year growth of 36% compared to the previous year, the large market environment promotes the rapid development of fresh food e-commerce platforms, resulting in the mushrooming of fresh food e-commerce platforms. The competition among fresh food e-commerce platforms is extremely high. It also puts forward high requirements. As a fresh food e-commerce platform, it needs to build a good ecological environment, effectively control ...

AI Technical Summary

Problems solved by technology

[0002] Due to the development of e-commerce such as Taobao, people are used to online shopping without leaving home. In addition to various daily necessities, fresh food e-commerce has gradually developed. In 2019, China's fresh food e-commerce industry market transactions hit 270 billion yuan. The year-on-year increase of 36% compared with the previous year. The large market environment promotes the rapid development of fresh food e-commerce platforms, resulting in the mushrooming of fresh food e-commerce platforms. The competition among fresh food e-commerce platforms is extremely high. It also puts forward high requirements. As a fresh food e-commerce platform, it needs to build a good ecological environment, effectively control the behavior of merchants, and ensure the interests of merchants and users in order to stand out among many fresh food e-commerce platforms. At the same time, because the platform The data flow is huge. Adjusting the data and logic of the platform function modules can easily cause system failures, requiring multiple adjustments to coefficients and data logic, which requires a huge amount of human resources; then how to build a good ecological environment, in the frequent data Reducing energy consumption in logic updates is an urgent problem for fresh food e-commerce platforms

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