A Comparative Guide to Automation and Manual Testing

Consumers want their applications to work perfectly each time. If your app is rife with performance issues, bugs, and glitches, it can lose its user base in no time due to its flawed quality. As a result, testing your software product is imperative to ensure project teams check, verify, and validate the functionality of the developed software and deliver optimal user experiences.

Recent times have witnessed both manual and automated testing leveraged in tandem to offer quality products to customers. 

This blog covers the basics of manual and automated testing, their key differences, and the best scenarios to use each of the testing processes.

What is manual testing?

Manual testing is a software testing process where test cases are executed manually with almost no intervention of automated tools. The test cases are executed as per the end user's perspective and ensure whether the software is working as mentioned in the requirement document or not.

Manual testing is one of the most conventional testing processes that help identify both visible and hidden software defects. The bugs and feature issues identified are reported through manually created documents and depend significantly on the knowledge, skill sets, and experience of the manual tester.

Primary types of manual testing

Some of the major manual testing methods and techniques used by manual testers include:

1. Black box testing: This method largely focuses on the software functionality and how well it responds to a particular input given. Black box technique can include:

• Equivalence Partitioning
• Boundary Value Analysis
• Decision Table
• State Transition Testing

2. White box testing: This testing process helps the tester understand the structure and code of the application. Developers often leverage white box testing and check each line of code prior to passing it on to a test engineer. Developers utilize techniques like branch testing, control flow testing, decision coverage, data flow testing, path testing, and statement coverage.

3. Gray box testing: White box and black box testing applied together help identify bugs and defects and the effects arising from structural issues or improper application usage.

4. Acceptance testing: This testing process determines if the software system meets the desired specifications. The test evaluates compliance with business requirements and ensures meeting the end-user criteria.

5. Integration testing: The integration testing process involves the stage where developers test how efficiently different application modules work together.

Let's dive into the working of manual testing

Performing manual testing involves analysts and QA engineers handling the tasks precisely, from the creation of test cases to their execution.

At first, the tester observes every document related to the software thoroughly to select the testing areas. Following this, testers analyze the documents to cover all requirements stated by the customer. The tester develops test cases according to the requirement document. Every test case is executed manually with the black box and white box testing. The status of every test is marked and well-documented. In certain cases, testers might go beyond the tests to determine the cause of any failure for a test case. Following this, the testers create reports with information on all bugs and defects found. The reports also provide the status of reruns relying on the number of skipped and failed tests. The development team fixes the bugs identified and hands over the software to the testing team for the retest.

Benefits of manual testing

• Lower initial investment and start time
• Suitable for applications with frequently changing GUI
• Minimal or no coding for rapidly testing small changes
• Opportunity to interact with applications as real users that enables testers to evaluate usability and user interface issues
• Extensive human judgment and intuitive abilities that help analyze elements better
• Fast and accurate visual feedback

Downsides of manual testing

• Requires a large number of human resources
• Prone to errors
• Limits test code reusability for different apps
• Doesn't cover all aspects of testing
• Requires time-consuming processes

What is automation testing?

Automation testing refers to the software testing technique that uses specialized automated testing tools to execute a test case suite. Automation testing software can help enter test data into the system Under test, compare expected results and actual results and render detailed test reports. Using a test automation tool helps in repeated execution of the same test suite that allows recording test suites and re-play them as required. 

Types of automation testing

Varied automation testing types can be utilized together by QA departments to derive the best outcomes. Following are some of the key automation testing types:

1. Functional testing:

This involves testing the functionalities of elements as per the requirements with minimal awareness of the design or structure of the app.

‍2. Non-functional testing:

This form of testing follows functional testing and checks how well the products work concerning their reliability, performance, usability, etc.

‍3. Keyword-driven testing:

This works by associating keywords in data files with a specified set of actions that are automatically performed for the app under test. This is easy to maintain, functions with any automation tool, and requires minimal or no programming knowledge.

‍4. Data-driven testing:

A data-driven testing process involves feeding different sets of external data compiled in spreadsheets or tabular format into one set to check the consistency of outcomes, enable the reusability of code, and save time.

‍5. Regression testing:

This form of maintenance testing involves testers rerunning the functional and non-functional tests to ensure that modifications and changes made to the app codes negatively impact the app's response, functionality, and performance.

There has been a major shift from manual to automated regression testing to drive agile software development lifecycles. Regression testing in manual test efforts requires more time and resources, limits continuous testing, heightens chances of redundancies and human errors, and limits test coverage. As a result, most companies depend on automated regression testing to improve the overall testing lifecycle.

Manual vs. Automation Testing

Let's quickly glance through the differences between automation testing vs. manual testing.

Manual testing or automated testing? Which one to leverage?

Automation vs. manual testing has been an area of discussion for a long while in the software testing realm that requires a precise understanding of the scope of the software, its audiences, and requirements to determine which type of testing is best suitable. Let us find out in more depth about the core differences between these two testing types.

Should you choose automated testing over manual testing?

• More efficiency

Automation tools make it easier and simpler to run tests more frequently with no significant hassles each time, unlike manual testing, which requires the same amount of time over and over again for repetitive processes. Thus, automated testing can help execute more tests in less time. This helps drive the productivity and efficiency of the entire software delivery process. Especially with a massive escalation in the usage of smart devices and applications, the focus on automation has increased with the expectation of improving the app's qualities. Web and manual mobile app testing have somewhat importance with indications of poorer efficiency across industries.

• Cost-effective

Though manual testing has a lower initial investment, it requires large volumes of human resources and effort for every process. Automated costing only requires a one-time cost. Once the tests are written, testers can easily leverage them every time. While in manual testing, testers must perform the routine repetitively, costing them every time.

• Improved accuracy in test cases

In the case of manual testing, even the most experienced test engineers can make errors, especially for complex use cases. However, automated testing can easily eliminate this worry and help perform tests with better accuracy as they follow similar algorithms, function similarly each time, and render the same outcomes. 

• Test suite reusability

The repetitive nature of test cases in automation testing enables software developers to easily determine application reactions. Further, the configurations are easy to set up and allow automated test cases to be reused in different scenarios.

• Scalability

As manual testing requires significant human resources and involves a large number of hours for each project, scaling up manual test projects will require more people with more test cases. However, automation testing owes a high degree of scalability as it needs adding just more test executors to the testing framework or method.

• Reduced manual tasks

Automated testing allows testers to reduce repetitive manual tasks across the testing journey and leverage multiple automation tools to help execute the testing efficiently. However, a certain amount of manual intervention is required during the implementation stage where testers manually create the baseline testing scripts.

Writing test scripts can be made simpler in automated testing, where specialized tools allow testers to develop code and test scripts. 

• Opportunity to accommodate advanced features

Automation makes it easier for software companies to automate highly advanced tests leveraging real user simulation technologies. This includes face ID, Fingerprint testing, location mocking, network virtualization, and image and voice-related testing.

• Increased test coverage

The number of tests you can execute in manual testing is constricted as it requires more time and resources to write and execute new tests. In contrast, automation enables testers to invest more time in crafting new tests to make them optimal and add them to the automated test suite. This helps expand the product's testing coverage and ensure that more features are tested rigorously, thereby improving the quality of the software product.

• Scenarios where you should consider manual testing

Though automation is ruling the software testing landscape, some situations might require manual testing as it allows testers to manually create and execute tests with more ability to handle complex and nuanced test scenarios.

• Initial development stage

During the initial development stage, utilizing manual testing is one of the most suitable processes as it helps testers detect bottlenecks or visual errors proactively and results in lesser time and resource consumption for fixing bugs. Additionally, the initial development is often an unstable phase of product development; therefore, it isn't rational to invest money and human resources into automation.

• During ad-hoc testing

QA specialists sporadically test functionalities of the system during ad-hoc testing. Ad-hoc testing is done best manually without preparation or a written test case.

• Testing the visual aspects of the UI

Testing the visual aspects of the user interfaces can be seamlessly done with manual testing. Manual testing offers extensive capabilities to capture visual aspects of the tests, notice defects, and much more. Leveraging manual testing for UI ensures that design elements in the interface match elements in the final layout.

Additionally, there is a lower risk for false negatives; false negatives can create additional work for DevOps teams to validate whether a reported error is true or false. Repeated high-frequency tests can be easily automated. Considering manual testing can prove to be suitable for 

• UX and exploratory testing
• Complex test scenarios
• Test scenarios that are being validated once in a while

Deploy HeadSpin to improve your testing cycles

HeadSpin offers a holistic AI testing platform to ensure efficient testing of your apps and digital products and deliver flawless end-user experiences throughout the product life cycle. 

How can HeadSpin help you test your software efficiently?

• Identify issues — HeadSpin leverages advanced AI technologies that help to identify performance and functional issues proactively. Perform automatic issue detection and RCA using industry-specific user experience metrics driven by the HeadSpin AI engine and improve your test results.
• End-to-end integrated, automated testing — Run integrated, continuous, and automated tests with HeadSpin Platform for functional, performance, and load testing across multiple applications, devices, and networks with no requirement for manual scripts. HeadSpin also allows efficient regression testing to help compare build over build, location over location, network over a network, and device over device performance to better understand cross-device/OS compatibility and performance.
• Global testing — HeadSpin's testing solution helps you perform end-to-end testing and monitoring with real devices on carrier and WiFi networks worldwide. Its secure global device infrastructure provides access to multiple real devices helping you to run geolocation tests on your mobile apps and websites. With multiple deployment options, companies can evaluate actual user experiences across the globe while ensuring complete security and optimal performance.
• Capturing key metrics — HeadSpin allows metric-based performance testing and session capture across the entire user journey and monitor network latencies that impact user experience. The AI modules help obtain actionable insights into app performances, helping companies improve overall performance and app experiences.

Conclusion

Regardless of whichever testing type your testing team focuses on, neither of the testing techniques can be entirely eliminated. It becomes inevitable for testers to rely on manual testing in the initial development phases, while automation is leveraged in areas of continuous tests, repeated processes, and tasks that need to be performed with time and resource limitations. 

Originally Published: https://www.headspin.io/blog/automation-and-manual-testing