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Journal articles on the topic 'Test automation'

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1

Pietschker, Andrej. "Automating test automation." International Journal on Software Tools for Technology Transfer 10, no. 4 (2008): 291–95. http://dx.doi.org/10.1007/s10009-008-0076-z.

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2

Polo, Macario, Pedro Reales, Mario Piattini, and Christof Ebert. "Test Automation." IEEE Software 30, no. 1 (2013): 84–89. http://dx.doi.org/10.1109/ms.2013.15.

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3

Gandhi, G. Mohan Doss, and Anitha S. Pillai. "Challenges in GUI Test Automation." International Journal of Computer Theory and Engineering 6, no. 2 (2014): 192–95. http://dx.doi.org/10.7763/ijcte.2014.v6.860.

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4

Green, Bradley S. "Software test automation." ACM SIGSOFT Software Engineering Notes 25, no. 3 (2000): 66. http://dx.doi.org/10.1145/505863.505892.

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5

Laplante, Phillip, Fevzi Belli, Jerry Gao, et al. "Software Test Automation." Advances in Software Engineering 2010 (February 17, 2010): 1–2. http://dx.doi.org/10.1155/2010/163746.

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Narendar, Kumar Ale. "Codeless Test Automation." European Journal of Advances in Engineering and Technology 10, no. 8 (2023): 59–65. https://doi.org/10.5281/zenodo.12754640.

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Codeless test automation is transforming the landscape of software testing by enabling the creation, maintenance, and execution of test cases without requiring extensive programming skills. This paper delves into the concept of codeless test automation, examining its key features, tools, and technologies. By leveraging visual interfaces, AI-driven mechanisms, and reusable components, codeless automation democratizes the testing process, making it accessible to a broader range of professionals. The paper also explores the benefits and challenges of this approach, supported by case studies and f
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Sujeeth Manchikanti Venkata Rama. "Universal Automation Framework: Revolutionizing Test Automation Architecture." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 1937–49. https://doi.org/10.32628/cseit251112215.

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The Universal Automation Framework (UAF) represents a transformative approach to test automation that addresses the persistent challenges faced by organizations in maintaining effective testing strategies. This comprehensive article explores how UAF's tool-agnostic architecture revolutionizes test automation by introducing a standardized, maintainable, and efficient framework that adapts to evolving technology stacks. Through its innovative object repository management, virtual application modeling, and unified test case structure, UAF enables organizations to overcome traditional automation l
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Twinkle, Joshi. "Breaking Down Automation Frameworks: Building Blocks for Better Testing." European Journal of Advances in Engineering and Technology 11, no. 11 (2024): 104–16. https://doi.org/10.5281/zenodo.15234713.

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Automation frameworks are the cornerstone of efficient and scalable software testing, providing structured methodologies and reusable components to enhance quality assurance and streamline processes. This article explores the essential building blocks of automation frameworks, highlighting their role in transforming testing practices through advanced tools, design patterns, and innovative approaches. By automating repetitive tasks, frameworks enable QA professionals to focus on high-value activities such as test design and usability evaluations, delivering benefits including improved accuracy,
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Wu, Zhong Qian, Jin Zhe Li, and Zeng Zeng Liao. "Keyword Driven Automation Test." Applied Mechanics and Materials 427-429 (September 2013): 652–55. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.652.

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In order to improve software reusability of automated test scripts, presents a keyword-driven test automation framework (KDTFA). First, the current existing automated testing framework for inductive analysis; then raised KDTFA system architecture; finally, an example of the android interface application framework and the existing framework for KDTFA actual contrast verification results show that the framework has a reduced scale of test scripts to improve the overall test efficiency and other advantages.
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Turlej, T. "Automation of sedimentation test." Water Science and Technology 77, no. 7 (2018): 1960–66. http://dx.doi.org/10.2166/wst.2018.076.

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Abstract This paper reports on the development of an automated method to perform sedimentation tests on a suspension, to study the settling and sedimentation behaviour of particle suspension. The standard method for measuring sedimentation rate is the jar test, but this is burdened with some errors: the possibility of misinterpretation of the interface or subjective readings by technicians. In order to overcome these problems, there are many different methods that exclude subjective mistakes. The proposed solution automatically detects the phase separation boundary and, by use of a moving came
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11

Kumar Ale, Narendar. "Enhancing Cybersecurity through Effective Test Automation Strategies." International Journal of Science and Research (IJSR) 10, no. 9 (2021): 1783–86. http://dx.doi.org/10.21275/sr24623093727.

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12

Eken, Süleyman, Ahmet Sayar, and Kürşat Topçuoğlu. "AutoTest: Automation to Test Tabular Data Quality." International Journal of Computer and Electrical Engineering 6, no. 4 (2014): 365–68. http://dx.doi.org/10.7763/ijcee.2014.v6.854.

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13

Popov, Andrei, Myroslav Momot, and Alina Yelizieva. "CHOOSING THE TEST AUTOMATION SYSTEM ACCORDING TO CUSTOMER REQUIREMENTS." Innovative Technologies and Scientific Solutions for Industries, no. 1 (19) (April 26, 2022): 40–46. http://dx.doi.org/10.30837/itssi.2022.19.040.

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The subject of the research are methods and technologies for automating the process of software product testing. The aim of the work is to optimize the time and costs for performing automated testing of software products. The following tasks were solved: analysis of existing software testing automation systems; formation of system of selection criteria for testing automation systems; development of formalized model of selection process; development of automation system selection algorithm considering customer's requirements; development of UML diagrams for presentation of functional capabiliti
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14

O'Shea, Donna, Francisco Ortin, and Kevin Geary. "A virtualized test automation framework: A DellEMC case study of test automation practice." Software: Practice and Experience 49, no. 2 (2018): 329–37. http://dx.doi.org/10.1002/spe.2658.

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15

Garousi, Vahid, and Frank Elberzhager. "Test Automation: Not Just for Test Execution." IEEE Software 34, no. 2 (2017): 90–96. http://dx.doi.org/10.1109/ms.2017.34.

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16

Amit, Gupta. "Unique Challenges to Test and Automate Mobile Device Management Application on Multiple Devices." European Journal of Advances in Engineering and Technology 7, no. 7 (2020): 66–72. https://doi.org/10.5281/zenodo.12789616.

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Mobile Device Management (MDM) suites, such as VMware Airwatch, MobileIron, and SOTI, are essential for managing and securing mobile devices in enterprises. Testing and automating these suites across multiple devices presents unique challenges due to the diverse range of hardware, operating systems, and configurations. This paper explores these challenges in detail, focusing on issues such as automating device unlocking after reboot, maintaining active sessions post-reboot, and addressing network and connectivity problems. Furthermore, it proposes a comprehensive solution using an advanced aut
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17

Banerjee, Debdeep, Kevin Yu, and Garima Aggarwal. "Object Removal Software Test Automation." IEEE Access 8 (2020): 12967–75. http://dx.doi.org/10.1109/access.2020.2965947.

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18

Kato, H., M. Hara, S. Kogiso, and I. Nakatsuka. "Automation of the Ames test." Mutation Research/Environmental Mutagenesis and Related Subjects 334, no. 3 (1995): 399. http://dx.doi.org/10.1016/0165-1161(95)90106-x.

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19

Zhang, Ning, Chao Li, Xuechen Dou, Yaohua Du, and Feng Tian. "Test Article for automation purposes." Critical Reviews in Analytical Chemistry 53, no. 1 (2022): 1969–89. http://dx.doi.org/10.1080/10408347.2022.2042999.

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20

Liao, Hsiu-Li, Chen-Huei Chou, and Wan-Chun Chao. "Functional Validation and Test Automation for Android Apps." International Journal of Machine Learning and Computing 4, no. 6 (2014): 553–58. http://dx.doi.org/10.7763/ijmlc.2014.v6.472.

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21

Kumar Ale, Narendar. "Enhancing Digital Transformation through Effective Test Automation Strategies." International Journal of Science and Research (IJSR) 10, no. 4 (2021): 1394–97. http://dx.doi.org/10.21275/sr24620103400.

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22

Kumar Ale, Narendar. "Machine Learning: A New Era in Test Automation." International Journal of Science and Research (IJSR) 9, no. 3 (2020): 1675–77. http://dx.doi.org/10.21275/sr24617015431.

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23

Khankhoje, Rohit. "AI - Based Test Automation for Intelligent Chatbot Systems." International Journal of Science and Research (IJSR) 12, no. 12 (2023): 1302–9. http://dx.doi.org/10.21275/sr231216065308.

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24

Kumar Ale, Narendar. "Transforming Test Automation - The Role of Machine Learning." International Journal of Science and Research (IJSR) 8, no. 10 (2019): 1872–75. http://dx.doi.org/10.21275/sr24615033013.

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25

Kantibhai Gohel, Keyurkumar. "IoT-Enabled Smart Fixtures for Adaptive Test Automation." International Journal of Science and Research (IJSR) 14, no. 1 (2025): 1308–15. https://doi.org/10.21275/sr25018084546.

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26

Dachepelly, Sridhar. "SELF-HEALING AUTOMATION SCRIPTS: THE FUTURE OF SUSTAINABLE TEST AUTOMATION." INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY AND MANAGEMENT INFORMATION SYSTEMS 16, no. 1 (2025): 202–15. https://doi.org/10.34218/ijitmis_16_01_016.

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27

Jiau, Hewijin Christine, and Jinghong Cox Chen. "Test code differencing for test-driven refactoring automation." ACM SIGSOFT Software Engineering Notes 34, no. 1 (2009): 1–10. http://dx.doi.org/10.1145/1457516.1457524.

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28

Dr. Ajay Roy, Srinivas Perala,. "A Novel Framework Design for Test Case Authoring and Auto Test Scripts Generation." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (2021): 1479–87. http://dx.doi.org/10.17762/turcomat.v12i6.2686.

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Every product has defects and identifying defects in the process of development and rectifying them before the launch of the product is very important. Embedded software testing process find the bugs in the software and report to the developer to fix issues. Sometimes to meet the product release deadlines, test engineers will not get much time to cover all test cases. That is why most software testing depends on test automation. In this paper, we focused on the area of automotive and home appliances embedded software test automation. Test automation is the only solution to improve the test pha
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29

Vorochek, Olga, and Illia Solovei. "RESEARCH ON ARTIFICIAL INTELLIGENCE TOOLS FOR AUTOMATING THE SOFTWARE TESTING PROCESS." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 1 (11) (July 30, 2024): 58–64. http://dx.doi.org/10.20998/2079-0023.2024.01.09.

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The subject matter of the article is artificial intelligence (AI) tools for automating the software testing process. The rapid development of the software development industry in recent decades has led to a significant increase in competition in the IT technology market and, as a result, stricter requirements for corresponding products and services. AI-driven test automation is becoming increasingly relevant due to its ability to solve complex tasks that previously required significant human resources. The goal of the work is to investigate the possibilities of using AI technologies to automat
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30

Lalit, Mishra, and Nayak Saroj. "Advanced test automation techniques for DevOps: Bridging the gap between test-driven development and continuous deployment in agile environments." World Journal of Advanced Research and Reviews 23, no. 3 (2024): 855–67. https://doi.org/10.5281/zenodo.14931894.

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As software development continues to change, it becomes more important to incorporate modern test automation approaches in DevOps to support efficient deployment. This work investigates TDD and CD in Agile to critically appraise advanced automation technologies and practices to fill existing deficits. This research demonstrates that the brighter Test Automation Framework approaches could improve code quality and deployment time, along with the culture of embracing best practices. The results can help practitioners who want to make their DevOps practices even more efficient and focused on quick
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31

Sroka, Michal, Roman Nagy, and Dominik Fisch. "Genetic Algorithms in Test Design Automation." Applied Mechanics and Materials 693 (December 2014): 153–58. http://dx.doi.org/10.4028/www.scientific.net/amm.693.153.

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Automation in the software testing process has significant impact on the overall software development in industry. Therefore, any automation in software testing has huge influence on overall development costs. The present article reviews the current state of the art of test case design automation via genetic algorithms. Three approaches applied in software testing are described with regards to their applicability in the testing of embedded software.
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32

Shailendra, S., Prakash A. M. Vijaya, and Ravindranth Nishanth. "Automation of Tester Diagnostics." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 6 (2020): 170–76. https://doi.org/10.35940/ijeat.F1315.089620.

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Tester needs to test software in ECU or implement changes in it and then test software depending on the client’s requirement. To test many real time scenarios, he makes use of ETAS Labcar which helps us to read and write different variables and validate test cases. He needs to set up the different tools and software to flash and validate the software which takes more time. For this we make use of ECU-Test tool which helps us to automate the process and we can run everything in one place. It has workspace which is specific to specific client project. Here we introduce new standard workspa
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33

Amit, Gupta. "On Device - Utilizing UI Elements to Capture Logs in Test Automation for Apple Applications." Journal of Scientific and Engineering Research 6, no. 11 (2019): 305–10. https://doi.org/10.5281/zenodo.12792680.

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XCUITest is a robust tool for automating UI tests for Apple platform’s applications. It offers a comprehensive framework for simulating user interactions and verifying UI behaviours. However, a significant challenge arises from Apple's sandboxing mechanism, which restricts access to the application container and, consequently, the logs generated by the application. This limitation can hinder effective debugging and validation of application behaviour. This paper explores a method to overcome this restriction by using a UI element within the application itself to capture and retrieve logs
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34

R, Mysiuk, Yuzevych V, and Mysiuk I. "Api test automation of search functionality with artificial intelligence." Artificial Intelligence 27, jai2022.27(1) (2022): 269–74. http://dx.doi.org/10.15407/jai2022.01.269.

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One of the steps in software development is to test the software product. With the development of technology, the testing process has improved to automated testing, which reduces the impact of the human factor on error and speeds up testing. The main software products for testing are considered to be web applications, web services, mobile applications and performance testing. According to the testing pyramid, when testing web services, you need to develop more test cases than when testing a web application. Because automation involves writing software code for testing, the use of ready-made to
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35

Khankhoje, Rohit. "The Power of AI Driven Reporting in Test Automation." International Journal of Science and Research (IJSR) 7, no. 11 (2018): 1956–59. http://dx.doi.org/10.21275/sr231208194832.

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36

Rauf, E. M. Abdul, and E. Madhusudhana Reddy. "Software Test Automation: An Algorithm for Solving System Management Automation Problems." Procedia Computer Science 46 (2015): 949–56. http://dx.doi.org/10.1016/j.procs.2015.01.004.

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37

Reshma, Sudra. "Regulatory compliance with AI and risks involved in finance and banking sectors." Journal of Scientific and Engineering Research 11, no. 1 (2024): 276–85. https://doi.org/10.5281/zenodo.12794295.

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Artificial intelligence is an essential part of the world and acts as a powerful catalyst driving transformative modifications in various industries. AI encompasses different technologies such as computer vision, language processing, and machine learning. The financial sector has integrated AI technology into services and products. The introduction of artificial intelligence in banking services has transformed the sector into more customer-oriented and technologically relatable. Regulatory compliance is considered armor since it protects financial institutions from vulnerabilities that can lea
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38

Khankhoje, Rohit. "Quantifying Success: Measuring ROI in Test Automation." Journal of Technology and Systems 5, no. 2 (2023): 1–14. http://dx.doi.org/10.47941/jts.1512.

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Purpose: The purpose of this paper to provide strategic decision to implement test automation with measurable ROI is a favoured approach for organizations seeking to improve the quality of their software, expedite delivery, and mitigate testing expenses.
 Methodology: The present paper, titled "Quantifying Success: Measuring ROI in Test Automation," delves deeply into the fundamental aspects of ROI evaluation within the realm of test automation. It outlines the methodology behind ROI calculation, explores the cost factors and advantages associated with automation, and sheds light on the o
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39

Chitti, Sridevi, P. Chandrasekhar, and M. Asharani. "A Unique Test Bench for Various System-on-a-Chip." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3318. http://dx.doi.org/10.11591/ijece.v7i6.pp3318-3322.

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This paper discusses a standard flow on how an automated test bench environment which is randomized with constraints can verify a SOC efficiently for its functionality and coverage. Today, in the time of multimillion gate ASICs, reusable intellectual property (IP), and system-on-a-chip (SoC) designs, verification consumes about 70 % of the design effort. Automation means a machine completes a task autonomously, quicker and with predictable results. Automation requires standard processes with well-defined inputs and outputs. By using this efficient methodology it is possible to provide a genera
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40

Sridevi, Chitti, Chandrasekhar P., and Asharani M. "A Unique Test Bench for Various System-on-a-Chip." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3318–22. https://doi.org/10.5281/zenodo.4079992.

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This paper discusses a standard flow on how an automated test bench environment which is randomized with constraints can verify a SOC efficiently for its functionality and coverage. Today, in the time of multimillion gate ASICs, reusable intellectual property (IP), and system-ona-chip (SoC) designs, verification consumes about 70 % of the design effort. Automation means a machine completes a task autonomously, quicker and with predictable results. Automation requires standard processes with welldefined inputs and outputs. By using this efficient methodology it is possible to provide a general
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41

Walker, Joshua T. "Software Test Automation with Robot Framework." International Journal of Computer Applications 175, no. 25 (2020): 8–14. http://dx.doi.org/10.5120/ijca2020920784.

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42

Ajayi, Wumi. "IMPROVING TEST AUTOMATION USING GENETIC ALGORITHM." International Journal of Advanced Research in Computer Science 13, no. 2 (2022): 55–63. http://dx.doi.org/10.26483/ijarcs.v13i2.6814.

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43

McGee, Pat, and Cem Kaner. "Experiments with high volume test automation." ACM SIGSOFT Software Engineering Notes 29, no. 5 (2004): 1–3. http://dx.doi.org/10.1145/1022494.1022536.

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44

Shetty, Vijayashree. "Test Automation Framework-A Comparative Study." International Journal for Research in Applied Science and Engineering Technology 8, no. 6 (2020): 1031–33. http://dx.doi.org/10.22214/ijraset.2020.6167.

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45

AMARICAI, Sabina, and Radu CONSTANTINESCU. "Designing a Software Test Automation Framework." Informatica Economica 18, no. 1/2014 (2014): 152–61. http://dx.doi.org/10.12948/issn14531305/18.1.2014.14.

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46

Zybin, R. S., V. V. Kuliamin, A. V. Ponomarenko, V. V. Rubanov, and E. S. Chernov. "Automation of broad sanity test generation." Programming and Computer Software 34, no. 6 (2008): 351–63. http://dx.doi.org/10.1134/s0361768808060066.

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47

Banerjee, Debdeep, and Kevin Yu. "3D Face Authentication Software Test Automation." IEEE Access 8 (2020): 46546–58. http://dx.doi.org/10.1109/access.2020.2978899.

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48

Шалыгин, Михаил, Mikhail Shalygin, Александр Сафонов, and Aleksandr Safonov. "TRIBOTECHNICAL TEST AUTOMATION USING DAQ-TECHNIQUES." Bulletin of Bryansk state technical university 2016, no. 2 (2016): 215–21. http://dx.doi.org/10.12737/20292.

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In the paper there is considered the automation of machines for tribotechnical tests. A method for the automation of testing machines of friction based on the use of DAQ-techniques is offered. A kinematics and a functional scheme of a testing machine of friction are shown. The means for the automation of friction and wear tests at a reciprocal motion including precision sensors are shown. A method for the definition of combined wear in a sample and counter-body is presented. The scheme of the automation of a loading device with automatic additional loading of a sample up to the value specified
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49

Perla, Srikanth. "Software Quality Engineering: Salesforce, AI, and Test Automation." International Journal on Recent and Innovation Trends in Computing and Communication 8, no. 12 (2020): 94–98. https://doi.org/10.17762/ijritcc.v8i12.11572.

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Software quality engineering plays a critical role in ensuring that customer relationship management (CRM) applications like Salesforce are reliable, efficient, and scalable. Test automation, powered by artificial intelligence (AI), has revolutionized the way software quality is maintained, especially in complex systems such as Salesforce. Salesforce, as one of the leading CRM platforms globally, requires rigorous testing to maintain its functionality, scalability, and security across multiple modules. AI and test automation technologies such as machine learning (ML), natural language processi
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50

Khankhoje, Rohit. "Mastering Test Automation: Bridging Gaps for Seamless QA." Journal of Marketing & Supply Chain Management 1, no. 3 (2022): 1–6. http://dx.doi.org/10.47363/jmscm/2022(1)138.

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The rapid evolution of software development practices has given rise to an increasing demand for efficient and effective test automation. The paper titled “Mastering Test Automation: Bridging Gaps for Seamless QA” delves into the crucial aspects of test automation, addressing the obstacles faced by organizations in achieving flawless quality assurance. The paper highlights the importance of bridging knowledge gaps within organizations, emphasizing the necessity for management to acquire a deeper comprehension of test automation scenarios, coverage, report trends and importance of communication
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