Artificial Intelligence in Automated Testing Environments

Mouna Mothey

doi:10.55544/sjmars.2.4.5

Authors

Mouna Mothey Independent Researcher, USA.

DOI:

https://doi.org/10.55544/sjmars.2.4.5

Keywords:

Artificial Intelligence, Component Behaviour, Software Applications, Test Automation, Smart Manufacturing, Machine Learning, Software Testing, AI Industry

Abstract

Artificial intelligence is developing at a breakneck pace, and its combination with automation has begun to transform the corporate environment. Businesses are concentrating on employing current AI in conjunction with automated procedures to achieve unprecedented levels of productivity and quality. The revolutionary impact of AI-driven reporting for test automation is explored in this research study. By using artificial intelligence, we enable test automation to provide useful insights in addition to problem detection. Every day, enormous volumes of data are produced from several sources, which must be properly tracked, analysed, reported on, and used to guide action. With the development of more sophisticated software programs, time is becoming a crucial consideration in the deployment of applications that need to be thoroughly tested and adhere to business requirements. AI is essential to software testing because it can provide faster and more reliable findings. These malfunctions may be hazardous and often happen during testing. Understanding component behaviour is essential for putting into practice effective defences against failure. While it is currently difficult to predict random component failures, artificial intelligence (AI) enables predictive failure simulation by intelligently simulating real-world conditions. Failure prediction is then possible by comparing simulated component behaviour with actual data, which is useful for maintenance and spare provisioning plans. As AI technology in automotive systems continues to advance, it is becoming increasingly important to address current issues and prevent future failures. Virtual reality and preventive maintenance are essential for understanding system behaviour and preventing failures.

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Mahadik, S., Fnu Antara, Chopra, P., Renuka, A., & Goel, O. (2023). User-centric design in product development. Shodh Sagar® Universal Research Reports, 10(4), 473.

Mahadik, S., Murthy, P., Kumar, R., Goel, O., & Jain, A. (2023). The influence of market strategy on product success. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET), 11(7), 1-31. Available at http://www.ijrmeet.org

Balasubramaniam, V. S., Mahadik, S., Khair, M. A., & Goel, O., & Jain, A. (2023). Effective risk mitigation strategies in digital project management. Innovative Research Thoughts, 9(1), 538–567.

Mahadik, S., Antara, F., Chopra, P., Renuka, A., & Goel, O. (2023). Universal research reports. SSRN. https://ssrn.com/abstract=4985267

Mahadik, S., Mangal, A., Singiri, S., Chhapola, A., & Jain, S. (2022). Risk mitigation strategies in product management. International Journal of Creative Research Thoughts (IJCRT), 10(12), 665.

Mahadik, S., Murthy, K. K. K., Cheruku, S. R., Jain, A., & Goel, O. (2022). Agile product management in software development. International Journal for Research Publication & Seminar, 13(5), 453.

Tirupati, K. K., Mahadik, S., Khair, M. A., & Goel, O., & Jain, A. (2022). Optimizing machine learning models for predictive analytics in cloud environments. International Journal for Research Publication & Seminar, 13(5), 611-637. https://doi.org/10.36676/jrps.v13.i5.1530

Mahadik, S., Khatri, D., Bhimanapati, V., Goel, L., & Jain, A. (2022). The role of data analysis in enhancing product features. SSRN. https://ssrn.com/abstract=4985275

Tirupati, K. K., Mahadik, S., Khair, M. A., & Goel, O., & Jain, A. (2022). Optimizing machine learning models for predictive analytics in cloud environments. International Journal for Research Publication & Seminar, 13(5), 611-642.

Mahadik, S., Kolli, R. K., Eeti, S., Goel, P., & Jain, A. (2021). Scaling startups through effective product management. International Journal of Progressive Research in Engineering Management and Science, 1(2), 68-81.

Upadhyay, A., Oommen, N. M., & Mahadik, S. (2021). Identification and assessment of Black Sigatoka disease in banana leaf. In V. Goar, M. Kuri, R. Kumar, & T. Senjyu (Eds.), Advances in Information Communication Technology and Computing (Vol. 135). Springer, Singapore. https://doi.org/10.1007/978-981-15-5421-6_24

Musunuri, A., Goel, P., & Renuka, A. (2023). Innovations in multicore network processor design for enhanced performance. Innovative Research Thoughts, 9(3), Article 1460.

Musunuri, A., Jain, S., & Aggarwal, A. (2023). Characterization and validation of PAM4 signaling in modern hardware designs. Darpan International Research Analysis, 11(1), 60.

Arulkumaran, R., Ayyagiri, A., & Musunuri, A., Prof. (Dr.) Punit Goel, & Prof. (Dr.) Arpit Jain. (2022). Decentralized AI for financial predictions. International Journal for Research Publication & Seminar, 13(5), 434.

Musunuri, A., Goel, O., & Agarwal, N. (2021). Design strategies for high-speed digital circuits in network switching systems. International Journal of Creative Research Thoughts (IJCRT), 9(9), d842–d860. https://www.ijcrt.org/

Salunkhe, V., Ayyagiri, A., Musunuri, A., Jain, Prof. Dr. A., & Goel, Dr. P. (2021). Machine learning in clinical decision support: Applications, challenges, and future directions. Available at SSRN: https://ssrn.com/abstract=4985006 or http://dx.doi.org/10.2139/ssrn.4985006

Tangudu, A., & Agarwal, D. Y. K. PROF.(DR.) PUNIT GOEL, "Optimizing Salesforce Implementation for Enhanced Decision-Making and Business Performance." International Journal of Creative Research Thoughts (IJCRT), ISSN: 2320, 2882, d814-d832.

Tangudu, A., Jain, S., & Pandian, P. K. G. (2023). "Developing scalable APIs for data synchronization in Salesforce environments." Darpan International Research Analysis, 11(1), 75.

Tangudu, A., Chhapola, A., & Jain, S. (2023). "Integrating Salesforce with third-party platforms: Challenges and best practices." International Journal for Research Publication & Seminar, 14(4), 229. https://doi.org/10.36676/jrps.v14.i4.

Abhishek Tangudu, Akshun Chhapola, & Shalu Jain. (2023). "Leveraging Lightning Web Components for Modern Salesforce UI Development." Innovative Research Thoughts, 9(2), 220–234. https://doi.org/10.36676/irt.v9.i2.1459.

Alahari, J., Tangudu, A., Mokkapati, C., Khan, S., & Singh, S. P. (2021). "Enhancing Mobile App Performance with Dependency Management and Swift Package Manager (SPM)." International Journal of Progressive Research in Engineering Management and Science, 1(2), 130-138.

Vijayabaskar, S., Tangudu, A., Mokkapati, C., Khan, S., & Singh, S. P. (2021). "Best Practices for Managing Large-Scale Automation Projects in Financial Services." International Journal of Progressive Research in Engineering Management and Science, 1(2), 107-117. https://doi.org/10.58257/IJPREMS12.

Abhishek Tangudu, Akshun Chhapola, & Shalu Jain. (2023). "Leveraging Lightning Web Components for Modern Salesforce UI Development." Innovative Research Thoughts, 9(2), 220–234. https://doi.org/10.36676/irt.v9.i2.1459

Agarwal, N., Gunj, R., Chintha, V. R., Pamadi, V. N., Aggarwal, A., & Gupta, V. (2023). GANs for enhancing wearable biosensor data accuracy. SHODH SAGAR® Universal Research Reports, 10(4), 533. https://doi.org/10.36676/urr.v10.i4.13,62

Agarwal, N., Murthy, P., Kumar, R., Goel, O., & Agarwal, R. (2023). Predictive analytics for real-time stress monitoring from BCI. International Journal of Research in Modern Engineering and Emerging Technology, 11(7), 61-97.

Joshi, A., Arulkumaran, R., Agarwal, N., Aggarwal, A., Goel, P., & Gupta, A. (2023). Cross market monetization strategies using Google mobile ads. Innovative Research Thoughts, 9(1), 480–507.

Agarwal, N., Gunj, R., Mahimkar, S., Shekhar, S., Jain, A., & Goel, P. (2023). Signal processing for spinal cord injury monitoring with sEMG. Innovative Research Thoughts, 9(5), 334. https://doi.org/10.36676/irt.v9.i5,1491

Pamadi, V. N., Chhapola, A., & Agarwal, N. (2023). Performance analysis techniques for big data systems. International Journal of Computer Science and Publications, 13(2), 217-236. https://rjpn.org/ijcspub/papers/IJCSP23B1501.pdf

Vadlamani, S., Agarwal, N., Chintha, V. R., Shrivastav, A., Jain, S., & Goel, O. (2023). Cross-platform data migration strategies for enterprise data warehouses. International Research Journal of Modernization in Engineering Technology and Science, 5(11), 1-15. https://doi.org/10.56726/IRJMETS46858

Agarwal, N., Gunj, R., Chintha, V. R., Kolli, R. K., Goel, O., & Agarwal, R. (2022). Deep learning for real-time EEG artifact detection in wearables. International Journal for Research Publication & Seminar, 13(5), 402.

Agarwal, N., Gunj, R., Mangal, A., Singiri, S., Chhapola, A., & Jain, S. (2022). Self-supervised learning for EEG artifact detection. International Journal of Creative Research Thoughts (IJCRT, 10(12).

Balasubramaniam, V. S., Thumati, P. R. R., Kanchi, P., Agarwal, R., Goel, O., & Shrivastav, E. A. (2023). Evaluating the impact of agile and waterfall methodologies in large scale IT projects. International Journal of Progressive Research in Engineering Management and Science, 3(12), 397-412.

Joshi, A., Dandu, M. M. K., Sivasankaran, V., Renuka, A., & Goel, O. (2023). Improving delivery app user experience with tailored search features. Universal Research Reports, 10(2), 611-638.

Tirupati, K. K., Dandu, M. M. K., Balasubramaniam, V. S., Renuka, A., & Goel, O. (2023). End to end development and deployment of predictive models using Azure Synapse Analytics. Innovative Research Thoughts, 9(1), 508–537.

Balasubramaniam, V. S., Mahadik, S., Khair, M. A., & Goel, O., Prof. (Dr.) Jain, A. (2023). Effective risk mitigation strategies in digital project management. Innovative Research Thoughts, 9(1), 538–567.

Dandu, M. M. K., Balasubramaniam, V. S., Renuka, A., Goel, O., Goel, Dr. P., & Gupta, Dr. A. (2022). BERT models for biomedical relation extraction. SSRN. https://ssrn.com/abstract=4985957

Balasubramaniam, V. S., Vijayabaskar, S., Voola, P. K., Agarwal, R., & Goel, O. (2022). Improving digital transformation in enterprises through agile methodologies. International Journal for Research Publication and Seminar, 13(5), 507-537.

Chandramouli, A., Shukla, S., Nair, N., Purohit, S., Pandey, S., & Dandu, M. M. K. (2021). Unsupervised paradigm for information extraction from transcripts using BERT. ECML PKDD 2021. https://doi.org/10.48550/arXiv.2110.00949

Dandu, M. M. K., & Kumar, G. (2021). Composable NLP workflows for BERT-based ranking and QA system. UC San Diego. Retrieved from [https://gaurav5590.github.io/data/UCSD_CASL_Research_Gaurav_Murali.pdf].

Voola, P. K., Avancha, S., Gajbhiye, B., Goel, O., & Jain, U. (2023). Automation in mobile testing: Techniques and strategies for faster, more accurate testing in healthcare applications. Shodh Sagar® Universal Research Reports, 10(4), 420–432. https://doi.org/10.36676/urr.v10.i4.1356