Browsing by Author "Talasbek A."

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    ARTIFICIAL AI IN TEST AUTOMATION: SOFTWARE TESTING OPPORTUNITIES WITH OPENAI TECHNOLOGY - CHATGPT
    (СДУ хабаршысы - 2023, 2023) Talasbek A.
    Abstract. One of the most important and significant stages of the software development life cycle is software testing. Automated testing reduces testing costs and increases productivity, resulting in a high-quality and stable end product. To ensure that software is bug-free and delivers the desired user experience, test automation is critical. As technology advances, test automation becomes more complex. However, advanced Al technologies will soon become commonplace thanks to powerful tools like ChatGPT that, among countless other things, can chat with you and teach you how to read and write code like a human. In this article, we will try to consider the possibilities of automation with chatgpt. Starting with writing test plans, and test scripts by using Python and Selenium WebDriver. How ChatGPT can improve our tasks and make them more feasible. By leveraging the capabilities of ChatGPT, software testing engineers can enhance their skills, improve testing capabilities, and achieve better quality and accuracy of test results. The opportunities presented by ChatGPT can lead to improved efficiency, productivity, and overall performance in the field of software testing engineering.
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    DESIGNING A RECOMMENDATION SYSTEM FOR SPECIALIZED COURSES FOR THE UNIVERSITY
    (СДУ хабаршысы - 2021, 2021) Anefiyayev N. ; Anefiyayeva D. ; Talasbek A.
    Abstract. Each university has compulsory subjects and there are subjects that the student must choose for themselves. This choice affects the further path of the student because he chooses not only the subject that he will study but also what he will work within the near future. I know from myself how difficult it is to choose a subject yourself. The recommendation engine is one of the most popular artificial intelligence applications, attracting many researchers from all over the world. From the moment we switched to the Internet, the recommendation system has become widely used in our daily life, even when we do not notice it. Many machine learning techniques can be used to implement a recommendation system, but in this work, we consider the KNN method for classification.
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    The Automation capabilities in the software testing field
    (2023) Talasbek A.
    Automated log analysis and anomaly detection play a crucial role in raising software quality.As modern systems grow in size and complexity, the number of journals grows exponentially makes manual testing impossible. Automated log analysis and anomaly detection approaches can uncover anomalies that might go undetected by manual examination by analyzing and monitoring log data produced by software programs. This preventative strategy enables prompt issue identification and resolving, improving software quality and user satisfaction. In order to find and fix problems that can have an impact on the functionality, dependability, and user experience of software systems, automated log analysis and anomaly detection play a crucial role in raising software quality. Also the system helpful for real customers experiencing problems in real time, the system provides a quick resolution of current errors and warnings on system server, by logging each client request, we detect anomalies in the product software. The system also has a real-time notification function to attract testers, developers to fix bugs in a timely manner, which leads to better software quality and better user experience.