In the rapidly changing software development industry, enterprises must keep up with the latest trends or risk falling behind. The State of Software Quality Report 2023, with insights from over 3000 QA teams, provides a comprehensive view of the software quality landscape.<\/p>\n
Experts from Katalon, Deloitte, and Cigniti recently participated in a webinar. They shared their real-world experiences and discussed best practices and strategies to enhance software quality and achieve business success. The webinar covered topics such as the current state of software quality, the ROI of test automation, and emerging trends like artificial intelligence (AI) and autonomous testing. Case studies from Deloitte and Cigniti were also shared in the webinar.<\/p>\n
Here is a summary of what was discussed in the webinar.<\/p>\n
The QA goals and practices<\/strong> include clients focusing on automation and reskilling, experimenting with AI and continuous testing, expanding QA capabilities to SaaS and cloud projects, targeting long-term UX automation, and introducing a systematic QA approach to digital initiatives. Agile mainstream is the primary client segment for testing services. Vendors are aggregating their IPs and automation around continuous testing platforms, and application migration to the cloud will require bundling of application services, QA, and infrastructure capabilities. However, model-based testing will need help to expand from its niche.<\/p>\n The need for increased test automation<\/strong> is emphasized as it provides benefits such as shorter cycle times, improved regression coverage, reduced long-term testing costs, and more. AI-augmented development and testing strategies will be implemented by 50% of enterprises by 2027. The four essential steps to implement test automation are developing clear goals, dedicating time and resources, focusing on areas of most significant benefit, and choosing the right tools.<\/p>\n The objectives of software test automation include reducing risk, strengthening confidence, releasing faster, freeing up the tester’s time, and delivering working software frequently. Emerging trends in test automation include AI-driven software testing, the digital twin model, the left shift approach, web 3.0 testing, intelligent automation, digital experience testing, and real-time analytics.<\/p>\n Artificial Intelligence for Software Testing<\/strong> In the short term, AI will augment quality engineers before becoming more autonomous and self-managing. It’s not a matter of if, but a matter of how and how much:<\/p>\n In the 2020 Gartner Achieve Business Agility with Automation, Continuous Quality, and DevOps Survey, 84% of respondents said that AI and machine learning (ML) features were more important than other features in software testing tools. To maximize the benefits of AI-augmented testing, software engineering leaders must evaluate five areas of software testing for applying AI.<\/p>\n AI can benefit in five software testing areas:<\/p>\n AI can impact software-testing practices like Requirement-derived testing, Intelligent test selection, Test set optimization, Customer-journey-driven testing, and Scenario-driven API testing.<\/p>\n AI can also be used for AI-augmented design, Unit test creation, Manual test conversion, Self-healing tests, Performance engineering, Synthetic data generation, Automatic defect classification, and Defect prediction. Visual testing using AI can evaluate the visible output of an application and compare it against the expected results without writing specific assertions.<\/p>\n The emerging trends in software testing include AI-powered test automation, intelligent test case generation, predictive analytics for defect detection, AI-powered exploratory testing, and AI-powered test environment management. These trends leverage the power of AI algorithms to automate repetitive tasks, generate test cases, predict defects, assist testers in identifying new scenarios, optimize test environments, and reduce infrastructure costs. These trends could improve the efficiency and effectiveness of software testing processes.<\/p>\n Challenges and Opportunities in Quality Assurance<\/strong> On the other hand, the rise of digital transformation has created opportunities for QA professionals to leverage technologies such as AI, ML, and automation to streamline testing processes and improve software quality. These technologies can help testers identify software defects and vulnerabilities more efficiently, reducing the time and resources required for testing.<\/p>\n Moreover, the shift towards DevOps and Agile methodologies has enabled teams to work more collaboratively, providing QA professionals with opportunities to work closely with developers to integrate testing throughout the development lifecycle. This approach helps detect defects earlier in the process and improves the quality of software products.<\/p>\n While the challenges facing QA professionals are significant, there are ample opportunities to embrace new technologies, work collaboratively with developers, and continuously improve software testing processes to ensure that software products meet the highest quality standards.<\/p>\n Conclusion <\/strong> Need help? Consult our Quality Assurance<\/a> experts to learn more about the latest trends in software testing and how they can benefit by using AI\/ML<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":" In the rapidly changing software development industry, enterprises must keep up with the latest trends or risk falling behind. The State of Software Quality Report 2023, with insights from over 3000 QA teams, provides a comprehensive view of the software quality landscape. Experts from Katalon, Deloitte, and Cigniti recently participated in a webinar. They shared […]<\/p>\n","protected":false},"author":20,"featured_media":19283,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rank_math_lock_modified_date":false,"footnotes":""},"categories":[86],"tags":[2174,2230,4391,88,218,41,409],"ppma_author":[3727],"class_list":["post-19282","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-software-quality-assurance","tag-ai","tag-artificial-intelligence","tag-ml","tag-quality-assurance-2","tag-software-testing","tag-test-automation","tag-webinar"],"authors":[{"term_id":3727,"user_id":20,"is_guest":0,"slug":"cigniti","display_name":"About Cigniti (A Coforge Company)","avatar_url":{"url":"https:\/\/www.cigniti.com\/blog\/wp-content\/uploads\/2024\/10\/Coforge-blog-Logo.png","url2x":"https:\/\/www.cigniti.com\/blog\/wp-content\/uploads\/2024\/10\/Coforge-blog-Logo.png"},"user_url":"https:\/\/www.cigniti.com\/","last_name":"(A Coforge Company)","first_name":"About Cigniti","job_title":"","description":"Cigniti Technologies Limited, a Coforge company, is the world\u2019s leading AI & IP-led Digital Assurance and Digital Engineering services provider. Headquartered in Hyderabad, India, Cigniti\u2019s 4200+ employees help Fortune 500 & Global 2000 enterprises across 25 countries accelerate their digital transformation journey across various stages of digital adoption and help them achieve market leadership by providing transformation services leveraging IP & platform-led innovation with expertise across multiple verticals and domains.\r\n
\nWhile we see mountains of promise and potential, AI for software testing still needs to be completed. As enterprise applications become more diverse across channels, platforms, and devices, volume and data variety have grown exponentially.<\/p>\n\n
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\nQuality Assurance (QA) is a critical aspect of software development that ensures that software products meet the desired quality standards. However, the field of QA faces several challenges, including constantly changing technology, a need for more skilled professionals, and the pressure to deliver software products faster. Additionally, ensuring that software meets regulatory and compliance standards poses a significant challenge.<\/p>\n
\nIn summary, the “Insights from the State of Software Quality Report 2023<\/a>” webinar provided valuable insights into the software testing industry and its current state. The speakers discussed the challenges and opportunities in quality assurance and presented case studies from Deloitte and Cigniti, which provided real-life examples of overcoming these challenges. The webinar also discussed the emerging trends and benefits of using artificial intelligence for software testing, which could be a game-changer for the industry. Overall, the webinar provided valuable insights into the current state of software quality and the software testing industry.<\/p>\n
\r\nLearn more about Cigniti at www.cigniti.com<\/a> and about Coforge at www.coforge.com<\/a>."}],"_links":{"self":[{"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/posts\/19282"}],"collection":[{"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/comments?post=19282"}],"version-history":[{"count":0,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/posts\/19282\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/media\/19283"}],"wp:attachment":[{"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/media?parent=19282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/categories?post=19282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/tags?post=19282"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.cigniti.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=19282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}