Software Quality Assurance Using Artificial Intelligence Techniques: A Survey of the Software Industry of Pakistan

Sheereen Qazi, Irfana Memon, Shahzana Memon, Beenish Qureshi Hashmi, M. Suleman Memon, Qazi Ejaz Ali


The software industry is quality-based and paramount for market-oriented software products. In the software industry, quality assurance (SQA) plays the key role, and is also known as software testing. The testing strategy can include a few steps to consider, such as ownership, unscripted tests, documentation and reportage, and test frequency. Testing provides software quality for the proposed software product and fulfills customer satisfaction. Software product testing and delivery is more suitable than unverified software consistency, expectedness, and non-exceptional resources. A few important types of software testing are unit, integration, system, sanity, smoke, interface, regression, and beta testing. Artificial intelligence approaches will enhance the quality of applications through new approaches to testing and regression testing by describing the impact factor of AI SQA tools. It will also aid in developing steep-quality, less insecure, and safer software. AI can help manage complex digital realms, such as dynamically decentralized networks, surveillance, robotics, and digital services of the next era (often grouped under the term “Next Generation Internet”). Outputs can help promote work on specific AI-based domains that may be required to implement modern digital platform smart activities that involve near interrelationships involving innovations, semblance, and implementations in quality assurance.


Keywords: artificial intelligence, software quality assurance, software development cycle.

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