Software Testing

Thanks to Gatling for providing us with this blog post.

You might have already started load testing, which is awesome! But if you haven’t, and you’re wondering when, where and how to start the answers are all here for you. To help you get set up we’re going to give you a few tips and tricks to build your load testing strategy and make sure that you’re set for success. Ready to dive in? Read on!

Know Your User

The most important part of load testing is knowing your user but more specifically what you need to know are the answers to a few key questions.

How are your users using your site/application? 

Most enterprises have an idea of how they’d like their users to use their site or products but for many how they’re actually using it and the journeys they take when they’re using it are a bit of a mystery. By using different tracking software such as Mixpanel or Amplitude though you can get a very detailed idea of what journeys your users are taking on your site and craft simulations to match and replicate this.

Understanding Your Traffic

Crafting great user journeys is the first step in building a scenario. Understanding your traffic though will help you decide what kind of tests you need to create. By using tools like Google analytics, Google Search Console, SEM rush or just monitoring your server usage you should be able to get an idea of what kind of traffic you’re receiving and how you’re receiving it. Are you getting sudden surges of traffic? Run a stress test! Are you getting long durations of constant traffic? Run a soak test. For every traffic scenario you can run a battery of different tests to ensure that your website is resilient enough to withstand the traffic it’s receiving. To learn more about the different kinds of load tests you can run and get an idea about what might work best for you check out our post here.

Continuous Integration

You’ve built your tests and run them, you’re doing great! However, most websites and applications are constantly changing and upgrading. How can you be sure that the changes you’re making aren’t going to change the performance of your project? By introducing load testing into your CI/CD project. We wrote a detailed post on the benefit of using Gatling Enterprise Cloud to integrate load testing into your CI/CD process. Gatling’s Enterprise version allows you to integrate with almost any CI/CD software, whether you’re using one of our dedicated integrations or using our CI Script to create your own.

Plan For The Unexpected

One of the great things about load testing is its ability to prepare you for any eventuality. You might not have thousands of users hitting your application today but by creating tests, and running them you can be sure that if it does happen you’re prepared. So when creating your testing strategy and examining your traffic it’s important not to just consider what is happening right now but also what could happen. What’s the worst/best case scenario? Are you prepared? Make sure by testing and you’ll know that whatever happens you’ll be ready.

By following these tips, this will help ensure that your websites and applications are able to handle the traffic and workloads that they will encounter in the real world, and it will help prevent performance issues that could impact the user experience. 

LINKS
or just monitoring your server	https://hubs.ly/Q01DYDSv0
sudden surges of traffic?	https://hubs.ly/Q01DYH_L0
out our post here	https://hubs.ly/Q01DYK9B0
Gatling Enterprise Cloud to integrate load testing into your CI/CD process.	https://hubs.ly/Q01DYL720

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Experiences with Test Gap Analysis in Practice

Thanks to CQSE for providing us with this blog post.

Most errors occur in code that has been changed lately (e.g., since the last release of a software system) [1,2]. This is of little surprise to practitioners, but how do we ensure that our tests cover all such changes, in order to catch as many of these defects as possible?

Do Tests Cover Code Changes in Practice?

In order to better understand to which degree tests actually cover changes made to a software system, we tracked development and testing activity on an enterprise information system, comprising of about 340k lines of C# code, over a period of 14 months, corresponding to two consecutive releases [1].

Through static code analysis, we determined that for each of these releases, about 15% of the source code were either newly developed or changed. Using a profiler, we recorded the code coverage of all testing activities, including both automated and manual tests. This data showed that approximately half of the changes went into production untested – despite a systematically planned and executed testing process.

To quantify the consequences of untested changes for users of the software, we then reviewed all errors reported in the months following the releases and traced them back to their root causes in the code. We found that changed, untested code contains five times more errors than unchanged code (and also more errors than changed and tested code).

This illustrates that, in practice, untested changes very frequently reach production and that they cause the majority of field errors. We may, thus, systematically improve test quality, if we manage to test changes more reliably.

Why Do Changes Escape Testing?

The amount of untested production code we found in our study actually surprised us, when we originally conducted this study. Therefore, we wanted to understand why this many changes escape testing.

We found that the cause of these untested changes is – to the contrary of what you may assume – not a lack of discipline or commitment on the testers’ part, but rather the fact that it is extremely hard to reliably identify changed code manually, when testing large systems.

Testers often rely on the description of individual issues from their issue tracker (e.g., from Jira or Azure DevOps Boards), in order to decide whether some change has been sufficiently tested. This works well for changes made for functional reasons, because the issues describe how the functionality is supposed to change and it is relatively easy to see which functionality a test covers.

However, there are two reasons why issue trackers are not suitable sources of information in consistently finding changes:

• First, many changes are technically motivated, for example, clean-up operations or adaptations to new versions of libraries or interfaces to external systems. Respective issue descriptions do not clarify which functional test cases make use of the resulting changes.
• Second, and more importantly, the issue tracker often simply does not document all important changes, be it because someone forgot or did not find the time to update the issue description or because someone made changes they were not supposed to make, e.g., due to a policy that is currently in place.

Thus, we need a more reliable source to determine what has been changed. Only then, we can reason about whether these changes have been sufficiently tested.

Test Gap Analysis to the Rescue!

Test Gap Analysis is an approach that combines static analysis and dynamic analysis to identify changed-but-untested code.

First, static code analysis compares the current state of the source code of the System under Test to that of the previous release in order to determine new and changed code areas. In doing so, the analysis filters out refactorings, which do not modify the behavior of the source code (e.g., changes to documentation, renaming of methods or moving of code) and, thus, cannot cause new errors. The remaining code changes lead to a change in the behavior of the system.

For the enterprise information system from before, all changes for one of the releases we analyzed are depicted on the following tree map. Each rectangle represents a method in the source code and the size of the rectangle corresponds to the method’s length in lines of source code. We distinguish unchanged methods (gray), from new methods (red) and modified methods (orange).

Second, dynamic analysis captures code coverage (usually through a coverage profiler). The crucial factor here is that all tests are recorded, across all test stages and regardless of whether they are automated or manually executed.

We use the same tree map as above, to visualize the aggregated code coverage at the end of the test phase. This time, we distinguish between methods that were executed by at least one test (green) and methods that were not (gray).

Third, Test Gap Analysis detects untested changes by combining the results of the static and dynamic analyses. Again, we use our tree map to visualize the results, distinguishing methods that remain unchanged (gray) from changed-and-tested methods (green), untested new methods (red) and untested changed methods (orange).

It is plain to see that whole components containing new or changed code were not executed by even a single test in the testing process. No errors contained in this area can have been found in the tests!

Using Test Gap Analysis

Test Gap Analysis is useful when executed regularly, for example, every night, to gain insights each morning into the executed tests and changes made up until the previous evening. Each day, an updated Test Gap treemap, e.g., on a dashboard, then helps test managers decide whether further test cases are necessary to run through the remaining untested changes. This creates an ongoing feedback loop to steer the testing efforts and make informed decisions.

Which Projects Benefit from Test Gap Analysis?

We have used Test Gap Analysis on a wide range of different projects: from enterprise information systems to embedded software, from C/C++ to Java, C#, Python and even SAP ABAP. Factors that affect the complexity of the introduction are, among others:

• Execution environment. Virtual machines (e.g., Java, C#, ABAP) simplify the collection of test coverage data.
• Architecture. The test-coverage data for a server-based application has to be collected from fewer machines than that for a fat-client application, for example.
• Testing process. Clearly defined test phases and environments facilitate planning and monitoring.

Using Test Gap Analysis During Hotfix Testing

The objectives of hotfix tests are to ensure that the fixed error does not re-occur and that no new errors have been introduced. To achieve the latter, we should at least ensure we tested all changes made in the course of the hotfix. Usually, there is very little time to achieve this.

With Test Gap Analysis, we may define the release state (before the hotfix) as the reference version and detect all changes made due to the hotfix (for example, on a dedicated branch). We then determine whether all changes were actually tested during confirmation testing. A Test Gap tree map immediately shows whether there are any untested changes left.

In our experience, Test Gap Analysis specifically helps avoid new errors that are introduced through hotfix changes.

Using Test Gap Analysis During a Release Test

For this scenario, we define a release test as the test phase prior to a major release, which usually involves both testing newly implemented functionality and executing regression tests. Often, this involves different kinds of tests on multiple test stages.

In the introduction to Test Gap Analysis above, we’ve looked at the results of running Test Gap Analysis at the end of a release test of an enterprise information system. These results revealed glaring gaps in the coverage of changes, after a test phase without using Test Gap Analysis to guide the testing efforts.

From that point onwards, Test Gap Analysis became an integral part of the testing process and was executed regularly during subsequent release tests. The following is a snapshot of the Test Gap Analysis during a later release test. It is plain to see that it contains much fewer Test Gaps.

If testing happens in multiple environments simultaneously, we may run Test Gap Analysis for each individual environment separately. And at the same time, we may run Test Gap Analysis globally, to assess our combined testing efforts. The following example illustrates this for a scenario with three test environments:

• Test is the environment in which testers carry out manual test cases.
• Dev is the environment where automated test cases are executed.
• UAT is the User Acceptance Test environment, where end users carry out exploratory tests.
• All combines the data of all three test environments.

We observed that, in many cases, some Test Gaps are accepted, for example, when the corresponding source code is not yet reachable via the user interface. The goal of using Test Gap Analysis is not to test every single change at all cost. The key is that we can make conscious and well-founded decisions with predictable consequences about what to test.

In our experience, Test Gap Analysis significantly reduces the amount of untested changes that reach production. In a study with one of our customers, we found that this reduces the number of errors in the field by as much as 50%.

Using Test Gap Analysis Alongside Iterative Development

Today, fewer and fewer teams work with dedicated release tests, like in the previous scenario. Instead, issues from their issue trackers move into the focus of test planning, to steer testing efforts alongside iterative development.

In this scenario, testers are responsible to test individual issues in a timely manner after development finishes. As a result, development and testing interleave and dedicated test phases become obsolete or much shorter.

At the same time, it becomes even harder to keep an eye on all changes, because much of the work typically happens in isolation, e.g., on dedicated feature branches, and gets integrated into the release branch only on very short notice. All the more, we need a systematic approach to keep track of which changes have been tested and in which test environments.

Fortunately, we may run Test Gap Analysis also on the changes made in the context of individual issues. All we need to do is single out the changes that happened in the context of any particular issue, which is straightforward, e.g., if all changes happen on a dedicated feature branch or if developers annotate changes with the corresponding issue numbers when committing them to the version control system. Once we grouped the changes by issue, we simply run Test Gap Analysis for each of them.

Limitations of Test Gap Analysis

Like any analysis method, Test Gap Analysis has its limitations and your knowledge of them is crucial for making the best use of the analysis.

One of the limitations of Test Gap Analysis are changes that are made on the configuration level without changing the code itself. These changes remain hidden from the analysis.

Another limitation of Test Gap Analysis is the significance of processed code. Test Gap Analysis evaluates which code was executed during the test. It cannot figure out how thoroughly the code was tested. This potentially leads to undetected errors despite the analysis depicting the executed code as “green”. This effect increases with the coarseness of the measurement of code coverage. However, the reverse is as simple as it is true: red and orange code was not executed in tests, thus, no contained errors can have been found.

Our experience in practice shows that the gaps brought to light when using Test Gap Analysis are usually so large that we gain substantial insights into weaknesses in the testing process. With respect to these large gaps, the limitations mentioned above are insignificant.

Further Information

Test Gap Analysis may greatly enhance the effectiveness of testing processes. If you would like to learn more about how Test Gap Analysis works in our analysis platform Team scale, the first tool that offered Test Gap Analysis and, to date, the only tool providing Test Gap tree maps, as you have seen them above, check out our website on Test Gap Analysis or join our next workshop on the topic (online & free)!

References

[1] Sebastian Eder, Benedikt Hauptmann, Maximilian Junker, Elmar Juergens, Rudolf Vaas, and Karl-Heinz Prommer. Did we test our changes? assessing alignment between tests and development in practice.
In Proceedings of the Eighth International Workshop on Automation of Software Test (AST’13), 2013.

https://www.cqse.eu/publications/2013-did-we-test-our-changes-assessing-alignment-between-tests-and-development-in-practice.pdf

[2] N. Nagappan, Th. Ball, Use of relative code churn measures to predict system defect density, in: Proc. of the 27. Int. Conf. on Software Engineering (ICSE) 2005

Authors

Thanks to b.ignited for providing us with this blog post.

In the world of software development, testing is an essential part of the process. It is through testing that we can ensure that the software being developed is fit for use, meets requirements, and is ready for release. However, there are some situations where test reporting does not reach management, which is a problem. Do you wonder why this might happen? What are the consequences? Because believe me, there are consequences! And most importantly, what can be done to avoid all of this?
To understand the importance of test reporting, it is important to understand what a good test report consists of. The report summarizes the results and findings of a testing process. It provides a comprehensive view of the testing activities, including the objectives, scope, and methodology of the testing, as well as the test cases, test scripts, and test data used. It serves as a formal record of the testing activities and provides stakeholders with a clear understanding of the quality of the product or system being tested. It is an important tool for decision-making, as it can help stakeholders determine whether the product or system is ready for release or further testing is required.

Why does test reporting not reach management?

There are a few reasons why test reporting might not be available to management.
One reason is that the testing team does not have the necessary resources to produce reports. This could be due to a lack of personnel, time or funding. Another reason could be that they do not recognize the value of producing reports. They may believe that their work speaks for itself, and that there is no need to provide additional documentation.

Another reason could be that the development team is focused on meeting deadlines and releasing software quickly. In this case, the testing team may not have enough time to produce reports and meet their other responsibilities.
Or it could be that the team is not aware of the importance of test reporting to management. They may not realize that management needs this information to make informed decisions about the software development process.

What are the consequences of not reporting?

There are several consequences of not reporting test results to management. One of the most significant consequences is that management will not have a clear view of the quality of the software being developed. Without this information, they may make decisions that are not in the best interest of the company. For example: releasing software that has not been adequately tested leads to customer complaints, negative reviews and even legal action.

Another consequence of not reporting is that the testing team may not receive the recognition they deserve for their hard work. When management is not aware of the effort of the testers, they may not appreciate the value of their work, leading to lower morale and decreased job satisfaction.

Not reporting test results can lead to a breakdown in communication between the testers and the other members of the development team. This can make it more difficult to identify and fix bugs, leading to longer development times and higher costs.

How can you avoid not reporting test results?

There are 4 simple steps:

• The first step is to ensure that the testing team has the necessary resources to produce reports. This might involve hiring additional personnel, providing more time for reporting, or increasing funding for testing activities.
• The second step is to educate the testers about the importance of test reporting to management. By explaining how this information is used, the testing team will be more motivated to produce reports.
• The third step is to make sure that reporting is integrated into the software development process. This might involve using automated tools to generate reports or creating templates that make it easy for the testing team to produce reports quickly.
• And the fourth and final step is to ensure that there is open communication between the testers and the other members of the development team. By sharing test results and collaborating on solutions, the development process can be more efficient and effective.

Test-Automation-as-a-Service: your test reporting solution

At b.ignited, we are convinced that there is yet another solution to ensure that test reporting is always up-to-date, namely using ‘b.ignition’. b.ignition is an in-house developed tool, with an underlying cloud architecture to provide test reporting. Users can log in via a portal and thus view and compare all information of current and historical test results. There is always an overview available of the test results status across projects. If necessary, a new test run can be started from the same portal, and the results are immediately included in the overview. b.ignition is set up in such a way that the customer can choose between a private or a public cloud, depending on the desired data security.

Understanding the value of test reporting

In conclusion, not reporting test results to management can have significant consequences for the software development process. By understanding why this might happen and taking steps to avoid it, you can ensure that the software being developed is of the highest quality and meets the needs of the customer. It is essential to recognize the value of test reporting to management and to make it a priority in the software development process.

Author

Thanks to Lambdatest for providing us with this blog post.

Since the global pandemic, companies worldwide have rapidly accelerated their digital transformation initiatives. As more and more consumers are interacting with brands digitally, it has now become a strategic priority for every business to ensure that their digital products and services meet the expectations of their customers. This made testing of these digital products very essential as a negative digital experience will have a direct impact on the revenue stream. According to Forrester, prioritizing CX helps 66% of businesses enhance retention, and 60% of businesses increase customer lifetime value.

Software quality assurance (QA) ensures that your digital products are error-free, which helps in ensuring a positive customer experience, builds trust, and helps maintain brand reputation in the competitive online landscape. Yet, testing may be an expensive and time-consuming operation that drains a company’s resources significantly. Businesses must analyze ROI to effectively manage testing resources, prioritize activities that give the highest return, and identify areas for improvement. Businesses can make informed decisions using data-driven insights. Constant ROI tracking allows them to optimize their results and increase the quality of their digital products, ultimately leading to favorable outcomes.

In this blog post, we will look at why calculating ROI is important, and how a stronger software toolset can assist in unlocking the ROI of testing.

Why is ROI Important for Digital Testing?

ROI is an essential indicator for digital testing since it allows firms to calculate their testing process’s financial advantages and costs. Assessing ROI will enable organizations to make educated decisions about their testing efforts.

Organizations may assess the total return on investment of testing by comparing costs and benefits and making data-driven decisions about where to devote resources, what improvements to make to the testing process, and which initiatives to prioritize by comparing prices and benefits. Measuring ROI identifies which tests and modifications have the most significant impact on the customer experience and business outcomes, allowing companies to improve and enhance the testing process to boost the impact and ROI of future testing efforts.

Monitoring the ROI of digital testing allows firms to justify their time and money while proving to stakeholders the value of their testing program. If ROI analysis demonstrates that testing efforts boosted customer happiness, conversion rates, and revenue, this provides a compelling justification for future testing expenditure. Assessing ROI on digital testing can also aid in performance improvement by demonstrating which testing activities have the greatest influence on customer experience and business outcomes.

As a result, quantifying ROI is critical for businesses trying to enhance their online presence, improve user experience, and boost conversions and revenue through digital testing.

Increase ROI with a better Toolset

1. Test Automation

One of the most important advantages of a software toolset is the ability to automate testing. Test automation can reduce the time and effort required for manual testing, allowing resources to be focused on more important tasks. Automation can also improve testing accuracy by removing human errors and guaranteeing consistent test execution. Companies can achieve faster time-to-market and lower overall testing expenses by lowering the time and effort necessary for testing.

2. Test Infrastructure

Faster time-to-market, improved quality, lower costs, and higher customer satisfaction can all be achieved with better test infrastructure, which can raise ROI. It’s critical to invest in a strong and scalable infrastructure, make use of automated testing technologies, develop a thorough test plan, and have a dedicated testing staff in order to reap these benefits.

3. Test Intelligence and Observability

By identifying problems more quickly, prioritizing defects, doing risk assessments, enhancing testing effectiveness, raising quality, and improving customer happiness, test intelligence and observability can increase ROI. Investing in test intelligence and observability technologies to ensure the testing infrastructure provides real-time insights and data, and having a qualified testing team to continuously monitor the infrastructure are necessary to maximize ROI.

4. Better Test Coverage

A software toolset can also aid in increasing test coverage. Test coverage is the percentage of software code that is covered by tests. The greater the test coverage, the greater the trust in the software’s quality. A toolkit can assist in identifying parts of code that are not covered by tests and making recommendations for new tests to increase coverage. This can aid in ensuring that essential portions of the software are adequately tested, lowering the likelihood of defects or errors in production.

5. Integration with other tools

Integrating a software toolset with other tools is another advantage. Integration with project management solutions like JIRA, for example, can help to speed the testing process by automatically issuing tickets for failing tests. Integrating with version control systems such as Git can aid in the management of test code and the tracking of changes over time. Companies can develop a more effective and streamlined testing process by combining it with other solutions.

How to Calculate the ROI of Digital Testing

To calculate the ROI of digital testing, organizations must follow three key steps:

1. Establish Objectives: The first stage is to define the testing program’s objectives. Companies should determine the particular objectives they hope to achieve through digital testing. For example, the goal could be to boost conversions, improve user experience, or lower bounce rates.
2. Determine Costs: The next step is to figure out how much the testing will cost. This includes direct and indirect costs such as software license fees, testing equipment, and employee pay. Organizations should also consider the amount of time and resources needed for each testing activity.
3. Benefits Assessment: The final phase is to assess the benefits of the testing process. Key metrics like conversion rates, bounce rates, time on site, and customer happiness must be tracked. By weighing the costs and advantages, organizations can determine the overall ROI of their digital testing program.

Formula to Calculate ROI: (Benefits – Costs) / Costs

Organizations can calculate the ROI of their digital testing efforts using this approach. A positive ROI implies that the advantages of the testing process outweigh the disadvantages, whereas a negative ROI suggests that the disadvantages outweigh the benefits.

Benefits of Measuring ROI for Digital Testing

Calculating ROI on digital testing has various advantages for businesses:

1. Justification of Time and Money: By quantifying ROI, firms may justify to stakeholders the time and money spent on digital testing. ROI analysis enables firms to make informed decisions about where to deploy resources and prioritize efforts. According to Forrester Analytics survey data, 33% of global developers at the manager level or higher consider speeding up cycle time to be a top-three priority; 30% said the same about increasing the automation of software development lifecycle (SDLC) tasks.
   
2. Assessing ROI on digital testing allows businesses to understand which testing activities have the most significant influence on customer experience and business outcomes, allowing them to improve the testing process continuously. Gartner predicts that by 2023, 40% of product and platform teams will have cut unexpected downtime by 20% by incorporating AIOps into their DevOps pipelines for automated change risk assessments. By intelligently combining the stack’s functionality, the AIOps platform organizes and integrates domain-specific IT monitoring and management tools. Connecting various tools to the AIOps platform acts as a coordinating layer, serving as the brain.
   
3. Future Planning: Measuring ROI helps firms plan for future testing costs and align testing efforts with company goals. By prioritizing high-return activities, companies can allocate resources accordingly. Firms might allocate additional resources to evaluating a feature or capability that has a high ROI. A low ROI may prompt organizations to rethink their approach and either optimize the process or reallocate resources elsewhere. Businesses can guarantee their testing approach is successful and efficient by making data-driven decisions, which improves the quality of their digital products and services and drives positive outcomes.

Conclusion

In conclusion, by automating testing, connecting with other tools, enhancing test coverage, performing performance testing, and conducting security testing, a better software toolset can help unlock the ROI of testing. Companies can increase the quality of their software, lower the chance of defects or errors in production, and achieve a faster time-to-market by investing in a software toolset.

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