Citation:

Nagaraj Mandaloju,Vinod kumar Karne,Noone Srinivas,Siddhartha Varma Nadimpalli ,2021. "Overcoming Challenges in Salesforce Lightning Testing with AI Solutions", ESP Journal of Engineering & Technology Advancements 1(1): 228-238.

Abstract:

This study investigates the effectiveness of AI-driven solutions in overcoming the challenges of automated testing within Salesforce Lightning environments, characterized by dynamic content and frequent updates. The research aimed to evaluate how AI technologies such as machine learning, natural language processing, and computer vision can enhance testing efficiency and accuracy compared to traditional methods. Using simulated Salesforce Lightning scenarios, the study compared the performance of AI-driven and conventional testing approaches across key metrics including defect detection rates, test execution time, and test coverage. The analysis revealed that AI-driven tools significantly outperform traditional methods, offering improved adaptability to dynamic content and reducing manual script maintenance. AI techniques led to higher testing quality and efficiency, confirming their superiority in handling Salesforce Lightning’s complexities. The study concludes that integrating AI solutions into testing frameworks can substantially enhance testing processes, reduce operational costs, and improve overall quality. These findings underscore the value of adopting AI-driven testing approaches for dynamic application environments.

References:

[1] Haaranen, L., Mariani, G., Sormunen, P., Lehtinen, T., Complex online material development in CS Courses, Proceedings of the 20th Koli Calling International Conference, 2020, pp. 1-5.

[2] Pandey, D., Suman, U., Ramani, A. K., An Effective Requirement Engineering Process Model for Software Development and Requirements Management, 2010 International Conference on Advances in Recent Technologies in Communication and Computing, 2010, pp. 287-291.

[3] Ray, P., An Introduction to Dew Computing: Definition, Concept and Implications, IEEE Access, vol. 6, pp. 723-737, 2018.

[4] Bokhari, M. U., Shallal, Q. M., Tamandani, Y. K., Cloud computing service models: A comparative study, 2016 3rd International Conference on Computing for Sustainable Global Development, pp. 890-895, 2016.

[5] Thakkar, M., Rajaan, R., Salesforce CRM: A new way of managing Customer Relationship in cloud environment, International Journal of Electrical, Electronics and Computers, vol. 5, no. 3, pp. 14-17, 2020.

[6] What is Salesforce?, Salesforce.com, 2022.

[7] Craig, D. W., Bobrowski, S., The design of the Force.com multitenant internet application development platform, Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, 2009.

[8] Poniszewska-Maranda, A., Matusiak, R., Kryvinska, N., Use of Salesforce Platform for Building Real-Time Service Systems in Cloud, 2017 IEEE International Conference on Services Computing (SCC), 2017, pp. 491-494.

[9] Jyoti, D., Hutcherson, J., Salesforce Architects Handbook: A Comprehensive End-to-End Solutions Guide, 1st ed. New York: APress, 2021, pp. 164-169.

[10] Karavirta, V., Ihantola, P., Koskinen, T., Service-Oriented Approach to Improve Interoperability of E-Learning Systems, 2013 IEEE 13th International Conference on Advanced Learning Technologies, 2013, pp. 341-345.

[11] Crnkovic, G. D., Constructive research and info-computational knowledge generation, Model-Based Reasoning in Science and Technology, Heidelberg: Springer, 2010, pp. 359-380.

[12] Lehtiranta, L., Junnonen, J., Kärnä, S., The Constructive Research Approach: Problem Solving for Complex Projects, Design Methods and Practices for Research of Project Management, Aldershot: Taylor & Francis Group, 2015, pp. 95-106.

[13] Kasanen, E., Lukka, K., Siitonen, A., The Constructive Approach in Management Accounting Research, Journal of Management Accounting Research, 1993, pp. 243-264.

[14] Siemens, G., Long, P., Penetrating the Fog: Analytics in Learning and Education, EDUCAUSE Review, 2011, pp. 30-26.

[15] Pokhrel, S., Chhetri, R., A Literature Review on Impact of COVID-19 Pandemic on Teaching and Learning, Higher Education for the Future, 2021, pp. 133-141.

[16] Siemens, G., Learning Analytics: The Emergence of a Discipline, American Behavioral Scientist, 2013, pp. 1380-1400.

[17] Hove, S. E., and Anda, B., Experiences from Conducting Semi-Structured Interviews in Empirical Software Engineering Research, 11th IEEE International Software Metrics Symposium, 2005.

[18] Kallio, H., Pietilä, A. M., Johnson, M., Kangasniemi, M., Systematic Methodological Review: Developing a Framework for a Qualitative Semi-Structured Interview Guide, Journal of Advanced Nursing, 2016, pp. 2954-2965.

[19] Rubin, H. J., and Rubin, I. S., Qualitative Interviewing: The Art of Hearing Data, Sage, 2011.

[20] Persico, D., Pozzi, F., Informing Learning Design with Learning Analytics to Improve Teacher Inquiry, British Journal of Educational Technology, 2015, pp. 230-248.

Keywords:

Salesforce Lightning, Automated Testing, Ai Solutions, Machine Learning, Test Efficiency