5 minute read

A much-anticipated mobile banking app was launched with great fanfare. However, within just hours, the app store was flooded with user complaints. Features that worked perfectly during testing have miserably failed on specific devices. Additionally, the app crashes when users attempt transactions, costing the company both revenue and trust. Despite a rigorous mobile app testing process, device-specific issues were overlooked, leading to critical user experience breakdowns—ones that could only be caught on real devices. 

This scenario is all too common in the mobile app development industry, and yet, somehow, it is often least prepared for. With 6.92 billion smartphone users worldwide, the diversity of hardware, operating systems, and usage conditions presents a monumental challenge for testers. Whether or not one should use simulators or real devices for testing plays a significant role in crafting a robust mobile app testing strategy. Therefore, it is crucial to evaluate and adequately understand the advantages and limitations of both approaches, offering teams actionable insights on creating a balanced strategy to elevate the mobile app testing game.

The Importance of Mobile App Testing

The year 2023 witnessed over 257 billion app downloads globally, solidifying the necessity of delivering high-quality applications. Rigorous mobile app testing is non-negotiable for reasons such as:

  • Identifying Hidden Bugs: Detect and resolve device- and platform-specific issues.
  • Ensuring Positive User Experiences: Eliminate crashes, slowdowns, and errors that could frustrate users.
  • Avoiding Negative Feedback: Reduce the likelihood of app store rejections and negative reviews.
  • Safeguarding Brand Reputation: Position your business as reliable and trustworthy.
  • Reducing Post-Release Costs: Identify issues early, minimizing costly fixes after deployment.

A well-tested app enhances user satisfaction, builds loyalty, and strengthens a brand’s position in a competitive market. A robust checklist helps teams to test mobile apps without leaving any stone unturned.

A Comparative Analysis: Simulators vs. Real Devices

  Simulators Real Devices
Advantages Cost-effective: Eliminates the need for physical devices, thereby reducing expenses.

 

Rapid iterations: Easily integrates into development environments for quick prototyping and bug fixes.

Early testing: Suitable for initial checks on functionality and UI design.

Real-world testing: Provides authentic insights into app behaviour under diverse real-world conditions.

 

Hardware integration: Validates features like GPS, camera functions, and touch gestures.

Network variability: Ensures performance across different connectivity levels (3G, 4G, Wi-Fi).

Limitations Limited realism: Cannot replicate real-world conditions like varying network speeds or hardware-specific issues.

 

No hardware testing: Ineffective for GPS, camera, or biometric sensors.

High cost: Requires purchasing and maintaining a range of devices, increasing expenses.

 

Operational challenges: Managing and scaling a physical device lab requires significant resources.

When to Use Early-stage development for basic functionality testing.

 

Prototyping UI/UX designs across different screen sizes.

Low-budget projects requiring rapid iterations.

Performance testing under real-world conditions.

 

Compatibility testing across various hardware configurations and operating systems.

Validating hardware-dependent features like location tracking or biometric authentication.

Although simulators and real devices have their unique set of advantages, disadvantages, and usability, combining both enables teams to optimize resources and achieve comprehensive testing. Such a hybrid strategy ensures cost efficiency through simulators for early development and accurate bug detection with real devices for pre-launch validation. An efficient way to implement the hybrid strategy is to start testing on simulators for basic functionality and then switch to real devices for advanced scenarios like stress testing and feature validation.

Case Studies

Case Study 1: Implementing a Robust Test Framework for Keysight Technologies

Client: Keysight Technologies, a leading provider of electronic measurement solutions.

Challenge Presented: Keysight aimed to scale production while ensuring consistent quality in their software releases. Prior to collaborating with Moolya, their testing process was predominantly manual, focusing solely on functional testing without any automation. Undoubtedly, this approach was time-consuming and delayed releases.

Solution Offered: Moolya partnered with Keysight to establish a comprehensive testing strategy:

  • Test Planning and Strategy: Collaboratively developed a detailed test plan and strategy, identifying key modules for automation.
  • Automation Implementation: Utilized Java and Selenium to automate approximately 150 test cases within six months, prioritizing the Chrome browser initially.
  • Infrastructure Setup: Established a virtual machine to execute tests remotely, facilitating cross-browser and parallel testing to reduce test execution time.

Outcome:

  • Enhanced Release Cycles: The automation framework enabled smoother and more timely releases.
  • Improved Collaboration: Introduced a peer development team comprising developers and testers working towards unified goals.
  • Scalability Achieved: With the new test framework, Keysight successfully scaled their production, leading to extended collaborations with Moolya on multiple projects.

Case Study 2: User Field Testing for a Customer Loyalty Mobile Application

Client: A prominent fashion brand launching a customer loyalty app.

Challenge Presented: The app was designed to reward customers with points for purchases, which could be redeemed for items from a catalog. Ensuring accurate point calculations, seamless purchase and redemption processes, and proper membership upgrades were critical.

Solution Offered: Moolya conducted real-time user field testing by:

  • Simulating Purchases: Testers posed as customers, executing test cases in actual store environments to validate point crediting mechanisms.
  • Redeeming Points: Assessed the redemption process to ensure customers could accurately use points for catalog purchases.
  • Membership Upgrades: Verified that customers were appropriately upgraded to new membership levels based on their purchase history.

Challenges Faced:

  • Simulating Transactions: Generating real-time bills without actual monetary transactions required coordination with the billing department.
  • Complex Calculations: Ensuring accurate point calculations and membership upgrades involved testing multiple scenarios with varying purchase amounts.

Outcome:

  • Critical Issue Identification: Discovered issues that were only apparent in a real-world environment, leading to significant improvements before the official launch.
  • Enhanced User Experience: Ensured that end-users would have a seamless experience with accurate point tracking and redemption functionalities.

The Role of Bugasura in Mobile App Testing

Bugasura excels in streamlining mobile app testing with its robust capabilities:

  • AI-Powered Bug Identification: Automates bug classification and prioritization.
  • Cross-Browser and Cross-Device Insights: Tracks app performance across a variety of conditions.
  • Collaborative Dashboards: Ensures alignment between QA, developers, and product managers.

Choosing the right testing approach—simulators, real devices, or a hybrid strategy—is pivotal to the success of your mobile app testing strategy. Combining these approaches ensures cost-efficient development, thorough validation, and superior app quality. Tools like Bugasura help teams streamline bug tracking, optimize workflows, and enhance user satisfaction.

Ready to streamline your mobile app testing process?

Explore Bugasura today and unlock the full potential of your testing framework

Frequently Asked Questions:

Why is mobile app testing important in 2025?

Mobile app testing ensures apps function seamlessly across diverse devices, avoiding bugs, crashes, and user dissatisfaction while safeguarding brand reputation.

What are the key differences between simulators and real devices for mobile app testing?

Simulators are cost-effective and ideal for early-stage testing, while real devices provide accurate insights into hardware and real-world conditions.

When should you use simulators for mobile app testing?

Simulators are best for early development stages, prototyping UI/UX designs, and projects with tight budgets requiring rapid iterations.

What are the limitations of using simulators in mobile app testing?

Simulators lack the ability to test real-world conditions, hardware-dependent features like GPS or camera functionality, and network variability.

Why are real devices essential for mobile app testing?

Real devices offer accurate performance analysis under real-world conditions, ensuring compatibility across hardware and validating features like biometrics or GPS.

What are the challenges of testing mobile apps on real devices?

Real devices require significant investment in purchasing and maintaining a device lab, along with operational challenges in scaling and management.

How does a hybrid testing strategy combine simulators and real devices?

A hybrid approach starts with simulators for basic functionality and progresses to real devices for advanced testing, achieving cost efficiency and thorough validation.

What role does Bugasura play in enhancing mobile app testing?

Bugasura streamlines testing with AI-powered bug identification, cross-device insights, and collaborative dashboards for improved team alignment and workflow efficiency.

How can testing on real devices prevent app crashes and user complaints?

Real device testing captures device-specific issues, network variability, and hardware performance, ensuring a stable and reliable user experience.

What are the top factors to consider when choosing between simulators and real devices?

Consider project budget, testing requirements, hardware-dependent features, real-world scenarios, and the need for scalability to make an informed decision.