The development history of software quality, large models open a new era of intelligent testing​

Since the dawn of computer science, the development of software quality has experienced a series of turns and milestones. From the initial functional requirements to the current comprehensive considerationfunctionality, performance efficiency, compatibility, ease of use, reliability, information security, maintainabilityand portability Wait, the definition and importance of software quality have improved significantly.

In the 1960s and 1970s, software development was mainly to meet functional requirements without much consideration for the quality of the software. As computer systems become more and more complex, people begin to realize the importance of software quality. At this stage, people mainly rely on manual testing, but this testing method is costly and inefficient.

#In the 1980s and 1990s, with the advancement of technology, software testing methods also improved significantly. People started using testing tools that could detect a large number of bugs in a short period of time. At the same time, people have also begun to pay attention to quality management in the software development process, such as the introduction of the software development life cycle model.

##At the beginning of the 21st century, the importance of software quality has been recognized globally. Global standardization organizations have begun to develop standards and best practices for software quality. Nowadays, software quality has become one of the key factors for enterprise competitiveness. With the popularity of DevOps and agile development, software quality is no longer just a task in the testing phase, but runs throughout the entire software development life cycle. It provides development and operations teams with a new way to manage and improve software quality. With the development of artificial intelligence and machine learning technology, software testing methods are also constantly improving. Leading companies represented by Testin Cloud Test have introduced artificial intelligence technology into the testing process,## The era of #intelligent testing has officially begun.

It is understood that Testin Cloud Testing is currently exploring the use of large models to assist in code generation, which is expected to increase software development efficiency by 20% to 30%. At the same time, Testin Cloud Testing is still testing and evaluating the capabilities of domestic and foreign open source large-scale models, and trying to apply them to software testing links such as test case analysis, test requirements analysis, and test report interpretation. According to the test results, this can also achieve an efficiency improvement of 20% to 30%

At the World Artificial Intelligence Conference in 2023, we have already begun to see The technical trend of using large models for large model testing has arrived. The advantage of introducing large models is that most of the testing work can be completed through machine automation, thus significantly improving work efficiency. In addition, large models can also help us understand the functions and performance of the software more deeply and comprehensively, so as to more accurately identify potential problems and errors

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