Follow these ten best practices to develop an effective testing strategy and integrate automated tests into a CI/CD pipeline for shorter release cycles and improved code quality.
Software testing is the process of assessing whether a piece of software is bug-free and meets the functional and business requirements determined by designers, developers, and stakeholders.
Due to the scope and complexity of modern software, testing has evolved from an incremental process conducted separately from development into a continuous process integrated within a CI/CD pipeline. Investing resources in effective testing throughout the software development life cycle shortens release cycles and improves code quality, performance, security, and maintainability.
This article will introduce ten best practices to help you gain the maximum benefit from software testing and ensure that your project implements testing effectively, efficiently, and strategically.
In the following sections, we will expand on each best practice summarized above. We will also present actionable steps to help you implement these practices within both current and future software projects.
Creating a formal plan for testing ensures that all members of the software team are on the same page regarding project requirements and specifications. The plan should outline an organization’s general testing philosophy and communicate specific details about testing conditions, scope, tools, and schedule. However, it is worth noting that writing test documentation is a time-consuming process, so it is advisable to create only those documents necessary to achieve project goals.
The following are some of the documents your team might create:
Ultimately, the documents your organization creates should depend on the number and size of the teams involved, the scope of your project, and the resources available. Less can be more, so consider starting with minimal documentation and expanding it if necessary. For more information about different types of testing documentation, see the International Software Testing Qualifications Board (ISTQB) glossary page.
Thoughtfully designed unit tests, integration tests, end-to-end tests, interface-to-database tests, and front-end automation tests will improve test coverage and enhance the overall reliability of your software. Ensure that tests cover all areas of your application, including UI/UX, performance, and security. In addition, a robust testing approach should include both positive testing to verify correct functionality and negative testing to test for weaknesses.
While 100% test coverage may not be feasible given budget or other constraints, an upfront commitment to comprehensive testing within a secure, standardized testing environment will yield long-term dividends for your project.
The widespread adoption of agile methodologies and modern DevOps practices has made test automation within a CI/CD pipeline an essential part of the software development lifecycle. Although writing automated tests can take considerable developer time and entail setting up test environments or learning new tools, the benefits in terms of project workflow and QA confidence often outweigh the costs.
Some common types of automated tests include the following:
In general, it is advisable to automate any tests that are repetitive, are frequently run, involve large data sets, are prone to human error, or are time-consuming or costly to run manually. There are dozens of open-source and commercial test automation tools available; some popular options are Selenium, Katalon Studio, Test Complete, Watir, and Cypress.
Gearing development practices toward testing will help your team recognize the importance of testing and normalize the process of writing tests within the developer workflow. Test-oriented development practices also help developers find and fix bugs earlier in the SDLC, which lowers the direct costs of fixing bugs and the indirect costs of lost development time and damaged business relationships. Shift-left testing, test-driven development, and pair programming are effective test-oriented practices to improve software quality. We will take a closer look at each of these practices below.
This term refers to beginning test efforts early and continuing to test throughout the development process. While it is most often associated with an agile workflow, it can also be used within other software development methodologies. By testing early and often, your team will patch bugs quickly and avoid finding critical “showstopper” bugs during deployment.
Shift-left testing can mean writing unit and integration tests early in development. However, getting started can also be as simple as ensuring that your team has well-defined code standards and employs linters for static analysis, security, and code formatting.
Test-driven development (TDD) shifts testing even further left by requiring tests to be written before any code is implemented. Each code change—however trivial—begins with writing at least one automated test, which will fail until a developer writes production code to satisfy testing requirements. Once all tests pass, the developer refactors the code to improve clarity and design.
The primary benefit of TDD is fewer bugs and defects. According to case studies from IBM and Microsoft, TDD projects featured defect rates (per thousand lines of code) 40-90% lower than projects that did not employ TDD.
Pair programming is a form of extreme programming in which two developers collaborate on a single computer. One developer writes code, while the other reviews each line and thinks about which code the pair should implement next to solve the problem at hand. This can be done in person or remotely using a collaborative IDE like LiveShare for VS Code.
One potential drawback of pair programming is that it can be difficult to adopt, depending on team culture and developer work preferences. For some developers, coding with another person can feel uncomfortable or even stifling. However, when embraced by team members and used effectively, pair programming offers substantial benefits.
Pair programming encourages developers to collaborate, share knowledge, and plan together before deciding on a solution. Because any newly written code must be understood and reviewed by two developers, code produced in pair programming sessions tends to have fewer bugs and be better designed. In addition, pair programming can promote a positive team culture and help onboard new hires quickly, since new members of the team can learn from those with more experience with the code base.
Containerization is widely used for software development and deployment because it allows an application to run consistently in any computing environment. Containers provide the resources and configurations an application needs to run on a standard container runtime and offer additional benefits in terms of scalability, security, and fault tolerance.
Containers are ideal for testing because they can easily be started, stopped, and rebuilt. Once a container image is defined, containers can quickly be spun up on demand, enabling tests to be run independently and predictably in consistent, repeatable, and isolated environments. Another benefit of containerized testing is freedom in hosting, meaning that developers can run tests locally or within cloud-based infrastructures with the same results.
Docker Compose allows you to define and run multiple Docker containers within the same host with a single command. Compose uses a YAML file to configure application services and can run in production, staging, development, and testing environments. Compose is ideally suited for CI/CD workflows and setting up and tearing down ephemeral test environments because it allows you to create reproducible and isolated environments on any platform.
Running tests with large data sets and a variety of inputs facilitates negative testing and helps identify edge cases by simulating real-world scenarios. For full-stack applications, this means seeding test databases so that developers can access the data necessary to run comprehensive local and cloud-based tests. As teams and data sets grow, however, it can be difficult to know where to store seed data.
Many modern object-relational mappers (ORMs) include built-in tools for database seeding and schema migrations. If your application language or framework does not incorporate an ORM or declarative migration tool, consider storing a SQL dump file within a service like GitHub’s Large File Storage. The dump file will point to seed data stored in an object storage service, such as Amazon S3 or Google Cloud Storage.
If neither of these solutions is suitable for your application, it is possible to use a third-party library like Faker to generate dummy seed data.
Ephemeral test environments (or preview environments) are independently deployed versions of your application created on-demand for a specific purpose. As the term “ephemeral” implies, these environments are intended to be short-lived. In practice, they are typically spun up to test a particular Git branch and taken down once a pull request is merged or closed.
Ephemeral environments are ideal for testing because they avoid many of the drawbacks of persistent test environments, including testing bottlenecks, inconsistencies between development and QA environments, and dependency issues. They allow developers to test their code independently in standardized environments that can be hosted locally or in the cloud. This leads to earlier bug identification and shorter release cycles. In addition, cloud-based ephemeral environments provide a static hosted URL for each pull request to facilitate collaboration across development and QA teams, product managers, and even end-users.
While creating and maintaining test environments was once costly and required a dedicated team, ephemeral environments can now be easily integrated into a CI/CD pipeline using an EaaS solution. Uffizzi offers both an open-source solution and hosted service that allow you to leverage the benefits of ephemeral test environments in new and existing projects.
While the approaches above will improve your team’s testing approach and workflow, it is still essential to include user acceptance testing toward the end of your QA process. Testing on end-users will ensure that your application behaves as intended on a variety of devices, including ones that encounter common issues like low battery levels or slow/spotty network connectivity.
Some common types of user acceptance testing include:
In planning user acceptance testing, ensure that testers represent a variety of user personas. Allow testers to see your product with fresh eyes, and solicit feedback on any user documentation or onboarding in your application. Finally, be sure to provide your testers with a convenient avenue for reporting their experiences.
It is important to remember that your testing strategy must grow and evolve as your product does. New application features will inevitably lead to new vulnerabilities and gaps in test coverage, which means that your team must work continuously to examine what is already in place, discover areas of weakness, and find effective ways to address those weaknesses. There is no one-size-fits-all approach to testing, so do not be afraid to revisit old strategies and find ways to improve testing in your organization.
Rigorous and well-planned quality assurance is essential in developing the high-quality, reliable software expected by users today. While no single testing procedure will work for every project, following some or all the practices described above will enhance your QA process and improve your product’s overall chances of success.