Software Testing

Top 12 Software Testing Trends Shaping the Future in 2024

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The software development landscape is constantly evolving, driven by ever-increasing user demands, the proliferation of complex technologies, and the relentless march towards faster delivery cycles. In this dynamic environment, software testing remains a cornerstone of quality assurance, ensuring applications function flawlessly and meet user expectations. However, traditional testing methodologies are no longer sufficient. To stay ahead of the curve, testers and QA leaders must embrace the latest trends that are transforming the software testing landscape in 2024.

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This article delves into the top 12 software QA trends that will shape the future of software testing, providing valuable insights for software testers, senior testing experts, and VP of Quality Assurance looking to optimize their testing strategies.

Top 12 Software Testing & QA Trends

1. AI-Powered Testing Boom Continues: Multimodal AI Takes Automation to the Next Level

Artificial Intelligence (AI) and Machine Learning (ML) are no longer novelties in software testing. In 2024, we will witness a continued upsurge in AI-powered testing, with a particular focus on multimodal AI.

This advanced approach combines techniques like natural language processing (NLP) and computer vision to automate complex testing tasks. NLP can analyze user stories and requirements to generate test cases, while computer vision can automate visual regression testing, ensuring UI consistency across platforms.

 Multimodal AI empowers testers to automate a broader range of scenarios, freeing them to focus on higher-level testing strategies.

A recent Lambada Test survey found AI Adoption among Software Testers at 78%.

In a TestGuild Webinar on Generative AI, 76% of testers say they already use (or plan on using) Chat-GPT AI to help them with their day-to-day testing activities.

Multimodal AI Takes Automation to the Next Level

Plus, with the recent release of multimodal AI Google’s Gemini, AI in Testing will get even more interesting.

Imagine testing that gets smarter by the data it sees! Multimodal AI combines text, images, voice commands, and even sensor readings to create a more robust and adaptable testing process.

This is cool because this should allow multimodal AI to enhance test automation with things like:

  • Visual Application Validation: Imagine software testers with superpowers! These next-generation bots combine eagle-eyed vision with the power of language to navigate apps and websites just like real users. This lets them uncover a wider range of issues, ensuring a smoother experience for everyone.
  • Expanded Types of Testable Applications Test automation is breaking free from the web! Now, it can understand images, videos, and even speech, allowing it to tackle a whole new world of applications.
  • Training with Diverse Sensory Inputs: “Training automated testing models with a combination of images, voice, and other sensory data unlocks a deeper understanding of system behavior, leading to the detection of subtler defects.”
  • Mainstream Accessibility Integration Cutting-edge frameworks like GPT-4 Turbo are being integrated into commercial testing tools, making them more user-friendly and accessible to non-technical testers.

By combining multiple data types processed via specialized algorithms tailored to each input, multimodal AI will deliver more comprehensive test automation capabilities, helping to mirror real-world complexity.

2. Testing for the Low-Code/No-Code Revolution

The low-code/no-code (LCNC) application development movement is gaining significant traction. These platforms allow citizen developers to build business applications without extensive coding knowledge. However, ensuring the quality of LCNC applications presents unique challenges. In 2024, we will see a rise in testing tools and frameworks specifically designed for LCNC environments.

These tools will leverage AI and automation to test the functionality, security, and performance of LCNC applications, ensuring their robustness and reliability.

Key aspects to testing low-code apps:

E2E Testing: Low-code apps often support web, mobile, and other channels that require automated testing across surfaces.

Integration Testing Challenges: Connecting low-code apps to existing systems requires API and integration testing for end-to-end flows.

Enabling Non-Technical Users: Empowering business teams to test their low-code apps independently is key to widespread adoption.

Optimized CI/CD Pipeline Integration: “To ensure the rapid delivery of high-quality applications built with low-code platforms, testing needs to seamlessly integrate into existing continuous delivery pipelines.”

Scalability Across App Portfolios: Testing capabilities must economically scale across large portfolios of low-code apps as adoption spreads enterprise-wide.

3. End-to-End API Testing Takes Center Stage

APIs are the backbone of modern software architectures, enabling seamless communication between different applications and services. As microservices-based architectures become increasingly prevalent, robust API testing becomes paramount.

In 2024, organizations will prioritize end-to-end API testing, ensuring that APIs function as intended throughout the entire user journey. This will involve not only testing individual APIs but also verifying their interactions within the broader application ecosystem.

Key aspects of robust API testing automation needed in 2024 include:

  • Functional Validation Verify APIs correctly implement required operations and business logic through extensive parameterized test cases.
  • Push Your APIs to the Limit: Uncover Bottlenecks Before They Become Breakdowns: Imagine putting your application through a stress test with a surge of users. Load and performance testing does exactly that, simulating high volumes of traffic to expose weaknesses before they impact real users..
  • Security Testing Validate APIs resist OWASP top threats like injection attacks, broken authentication, rate limiting, and input filtering using negative test cases.
  • Contract Validation
    Compare API responses against OpenAPI or Swagger schemas to ensure compliance with defined contracts.
  • Service Virtualization Simulate APIs not yet developed or mock external facing APIs to enable earlier testing before availability.

The rise of API testing automation is fueled by platforms like Karate and Postman offering features like automatic test case generation. This trend extends to general testing tools like Cypress and Playwright, suggesting their wider use for API testing in the future.

Some sessions at AG24 to help you learn more about API Testing for 2024:

  • API Automation Mastery: From Novice To Ninja
  • Accelerating API Testing: A Practical Guide to Automation with Cypress
  • Mocking The Unmockable: Elevating Test Automation Stability Through Advanced API Simulation
  • Safeguarding Digital Assets: Revealing Security Risks In APIs

4. Shift-Left Testing Goes Mainstream

            The concept of “shift-left testing” – integrating testing earlier in the Software Development Lifecycle (SDLC) – has been around for some time. However, in 2024, it will become a mainstream practice.

By integrating unit testing, code reviews, and other testing activities earlier in the development process, organizations can identify and fix bugs much sooner.

 This proactive approach leads to faster development cycles, reduced rework costs, and ultimately, higher-quality software.

Types of testing shifting left include:

  • Many developers skip writing unit tests for their code. Shift left practices integrate unit testing into the development workflow, ensuring tests are written alongside code during commits and pull requests.
  • Automatically run integration tests as part of the pipeline to verify new code interacts correctly with real dependencies after merging, instead of relying on mock objects.
  • “Enforce API consumer compatibility through automated contract testing integrated within the pull request workflow. This enables immediate assessment of potential disruptions for existing integrations upon code changes.”
  • Security Scanning Static and dynamic application security testing scans assess code early for vulnerabilities like SQL injection upon each commit.
  • Integrate load testing into your development pipeline to catch performance issues early, ideally after every major code change, preventing regressions from reaching production.

Shift left testing empowers developers, catches bugs earlier, and speeds up delivery. By identifying problems during code submissions instead of later stages, it allows for quicker and less expensive fixes.  This approach transforms testing from a final hurdle into a continuous guide, enabling the creation of high-quality software faster

5. Containers Make Test Environment Consistency a Reality

Containerization technology has revolutionized application deployment by providing a lightweight and portable way to package and run software. In 2024, containerization will play a more significant role in software testing. By leveraging containerized testing environments, organizations can ensure consistency across different testing stages, from development to production. This eliminates the variability often associated with traditional testing environments, leading to more reliable and repeatable test results.

Benefits containers bring test environments:

  • Isolated Dependency Replication Containers bundle all essential components for running code, including libraries, data, and configurations. This simplifies the process of setting up test environments.
  • Forget manual setup headaches! Container registries make it easy to launch identical test environments whenever you need them, across all development stages.
  • Leveraging containers, developers and QA teams can achieve significant cost savings on infrastructure. This is because containers enable them to replicate a wider variety of test environments efficiently, eliminating the need to provision and maintain numerous virtual machines (VMs).
  • Automated Scaling & Teardown Programmatically spins up containerized test environments in pipeline stages and automatically scales them up or destroys them on demand.

 Modern software development thrives on containerized testing with tools like Docker and Kubernetes. These technologies streamline the creation of reusable, microservice-based test environments. Additionally, cloud providers offer container services that effortlessly scale test orchestration. As codebases become increasingly intricate in today’s architectures, containers ensure consistent testing across environments.

6. Automating Compliance Testing for Increased Efficiency

Compliance with industry regulations and security standards is a critical aspect of software development. However, manual compliance testing can be time-consuming and error-prone. In 2024, we will see a surge in automation tools specifically designed to streamline compliance testing.

These tools will automate repetitive tasks such as data validation and security checks, allowing testers to focus on strategic compliance analysis.

Automating compliance testing delivers:

Shift security, privacy, and compliance checks left! Automate validation within CI/CD pipelines to provide immediate feedback on code commits and test suites, catching violations early in the development process.

Policy Enforcement: As Code Define compliance policies and controls as executable code for easy testing without manual script creation overhead.

Automated control testing reports provide objective evidence of application policy conformance. These reports detail the specific controls tested, allowing auditors to efficiently assess compliance.

Run automated tests frequently after code changes to ensure new features don’t affect existing functionalities. This proactive approach helps catch issues early in the development process

Risk Analysis Integration Incorporate risk analysis from tools like RSA Archer into test case generation to target high-risk use cases.

Example: Traceable AI bolsters API security by integrating advanced fraud prevention capabilities, effectively thwarting malicious actors who exploit APIs for digital scams.

Example: CrowdStrike debuts generative AI cybersecurity chatbot and new AWS integrations

Neglecting compliance testing automation makes achieving continuous delivery with governance impossible at scale. So that’s why I think this area will expand in 2024.

7. Self-Healing Tests Drive Higher System Resilience

The ability of software systems to self-heal in response to unexpected errors is becoming increasingly crucial. In 2024, self-healing tests will emerge as a key trend.

 These tests not only identify issues but also attempt to recover from them automatically. This can involve restarting failed components, rerouting traffic, or triggering automated remediation scripts.

Self-healing tests can significantly enhance system resilience and improve overall application uptime.

8. AIOps Powers Software Delivery Efficiency

AIOps refers to the use of AI and ML to automate IT operations processes. In 2024, AIOps will be increasingly applied in software delivery, including the testing domain. AIOps tools can analyze historical testing data, identify patterns, and predict potential bottlenecks in the testing process. This allows teams to optimize test execution strategies, streamline resource allocation, and ultimately, accelerate software delivery.

Why AIOps is important in 2024:

  • Anomaly Detection: Analyze metrics to recognize abnormalities from normal activity indicative of emerging issues automatically.
  • Leverage log aggregation and analytics to gain comprehensive insights from massive datasets across your systems. This enables rapid identification of root causes through event correlation.
  • Anticipate IT issues before they happen. Incident prediction spots trends like running out of disk space, so you can take action to prevent problems..
  • Automated Remediation: Apply pre-defined playbooks to resolve common infrastructure issues automatically, like freeing up disk space.
  • Optimized Cloud Cost: Continuously tune infrastructure sizing based on utilization to optimize cloud costs.

Leading examples include Dynatrace (Davis AI with Davis CoPilot), Splunk (Splunk AI), and Datadog (Bits AI). With infrastructures growing exponentially in scale and complexity, AIOps becomes essential for IT teams to manage reliability and costs efficiently.

9. Increased Focus on Mobile App Security Testing

Mobile applications are ubiquitous, and with their growing complexity comes an increased risk of security vulnerabilities. In 2024, organizations will prioritize robust mobile app security testing. This will involve not only traditional security assessments but also employing tools that simulate real-world hacking attempts to identify potential weaknesses before they can be exploited by malicious actors.

In 2024, Testing solutions must keep pace with faster mobile release cycles. Neglecting mobile test automation threatens customer experience and security.

10. Rise of Testing in Production (Shift-Right)

While “shift-left testing” emphasizes early integration, there’s also a growing trend towards “shift-right testing” – extending testing activities into production environments. In 2024, we will see organizations leverage tools like chaos engineering and canary deployments to proactively test applications in production. By injecting faults and monitoring system behavior, these techniques can identify potential issues before they impact end-users.

Traditional, meticulously crafted test environments can’t keep up with massive user loads and unpredictable systems.  To meet this challenge, advancements in monitoring real-world performance (production testing observability) and intelligent test automation are redefining how we validate software.

Example: Grafana Labs announced that it has Asserts.ai, a technology that promises to revolutionize how users understand and interact with observability data.

Testing transforms from deterministic laboratories to conducting controlled experiments in live environments will grow in 2024.

11. Developing for Observability: Building Testability into Applications

Modern software architectures are often complex and distributed. This can make it challenging to monitor system health and identify the root cause of issues. In 2024, a key focus will be on developing applications with observability in mind.

This involves instrumenting code with logging and tracing capabilities, allowing testers to gather rich data about application behavior.

By building testability into the application from the ground up, organizations can streamline troubleshooting and expedite issue resolution.

12. Playwright Takes the Crown in Automation Testing

The landscape of automation testing frameworks is constantly evolving. In 2024, Playwright is poised to gain significant traction. Playwright is a powerful framework that allows testers to write cross-browser automation scripts using a single codebase.

 It supports a wide range of browsers, including Chrome, Firefox, and WebKit, and offers seamless integration with popular testing libraries like Jest and Mocha. Playwright’s versatility and ease of use make it a compelling option for testers looking to streamline their automation efforts.

Conclusion: Embracing the Future of Software Testing

The software testing landscape is rapidly evolving, and the future belongs to those who embrace this transformation. By actively incorporating the trends highlighted above, testers, senior experts, and QA VPs can equip themselves for success in this dynamic environment. This future-proof approach involves leveraging AI-powered automation to streamline repetitive tasks and free up human testers for higher-level strategic thinking. Additionally, prioritizing security testing throughout the development lifecycle will become paramount in a world increasingly vulnerable to cyber threats. Building testability into applications from the ground up will further enhance efficiency and ensure comprehensive . By embracing these advancements and actively shaping the testing landscape, organizations can propel their software testing practices to new heights, ensuring the quality, reliability, and security of their offerings for years to come.

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