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Why code coverage tools can make or break your application

Code Coverage

Sep 25, 2023

In the dynamic nature of software development, success is bounded by a combination of a well designed codebase and a profound understanding of application performance. As your source code becomes more complex and distributed across different programming languages and frameworks, measuring code coverage becomes necessary for building robust quality gates.

Automated testing (unit tests, integration, end to end, and other types of testing) can help reduce the chances that your users encounter a bug, however, it's important to understand what you are testing in the first place. Taking control over your code coverage metrics will allow you to see how you can retool your automated tests to ensure software quality for your end user. This is where a code coverage platform becomes important in understanding software testing priorities and fortifying test cases. Ahead, we'll present some compelling reasons why integrating code coverage tools into your software development process or workflow is no longer a choice, but a strategic necessity.

1. Illuminating Code Quality with Precision Metrics

Code coverage observability platforms enable code quality assessments by highlighting which parts of your application are engaged while running your test suite - down to the number of lines. This test coverage from unit testing or otherwise empowers developers to zoom in on uncharted areas and lurking bottlenecks, ensuring tests encapsulate critical functionalities with unwavering precision.

2. Bug Vigilance and Vulnerability Mitigation

The bane of every developer, bugs have the potential to disrupt user experiences, compromise data integrity, and stain the software's reputation. A code coverage tools transforms into an early warning system, raising red flags about lurking bugs before they infiltrate production. By identifying untested code segments or dead code, developers adopt a proactive stance towards vulnerability mitigation, culminating in software that is robust and dependable. Through instrumentation, these metrics can be baked into code reviews left-shift issues at the time they're written.

3. Harmonizing Collaborative Endeavors

Collaboration among team members is the bedrock, and a code coverage platform emerges as the bridge. By merging together coverage reports from different test suites, services, or products, a code coverage platform enables teams to quickly understand the health of their platform. Armed with these insights into coverage metrics, teams can then gain a collective perspective on code segments deserving attention. This transparency catalyzes effective communication, empowering everyone to march in tandem towards a shared ambition: an application marked by resilience and perfection.

4. Mastering Performance Optimization

Code coverage goes beyond just comprehensive testing; it extends into the realm of performance optimization. A code coverage platform assumes the role of a compass, guiding developers towards the terrain of performance bottlenecks that would otherwise remain concealed. By directing attention towards frequently executed code segments, developers fine-tune these zones for peak performance, resulting in a swifter and more efficient application.

5. The Art of Confident Code Refactoring

Refactoring is the hallmark of progressive software development. Yet, tampering with the codebase can unleash latent issues. Coverage results and high code coverage give developers unwavering confidence in refactoring endeavors. By orchestrating tests in tandem with code modifications and closely monitoring coverage metrics, developers safeguard existing functionality from inadvertent disruptions. This newfound assurance paves the path for agile and iterative development.

6. Data-Driven Excellence

In the world of software, data reigns supreme. Coverage analysis equips developers with invaluable data-driven insights into application behavior. This knowledge fuels informed decisions about codebase enhancements, resource allocation, and overall development strategies. Armed with a profound understanding of the code's inner workings, developers are poised to steer projects towards triumphant conclusions.

Code Coverage Platforms

BuildPulse Code Coverage enables you to quickly deploy and enforce code coverage across your product in a new way. We believe that code coverage should serve as an asset and accelerate your development workflow - so we’ve taken a granular approach. Different areas of your application have different coverage needs and should be enforced as such, so BuildPulse allows you to configure different coverage standards at the directory or file level.

BuildPulse also goes beyond coverage to highlight parts of the code not covered. By illuminating untested blindspots, your team can left-shift it’s quality strategy and identify issues before they’re shipped - saving time, cost, and reputation. A unified view of your branch coverage, condition coverage, statement coverage, function coverage, and line coverage, coverage percentage, and lines of code can all be aggregated in one simple dashboard.

Modern software development demands adaptive tools that cater to its nuances. The code coverage platform has transcended luxury to become a cornerstone of modern workflows. Its ability to fortifying code quality, safeguard against bugs, nurture collaboration, optimize performance, instill confidence in refactoring, and unearth data-driven insights underscores its indispensability. As you embark on coding odysseys, consider weaving the coverage into your narrative. Your code and its users deserve nothing short of excellence.

FAQ

What is the difference between a flaky test and a false positive?

A false positive is a test failure in your test suite due to an actual error in the code being executed, or a mismatch in what the test expects from the code.

A flaky test is when you have conflicting test results for the same code. For example, while running tests if you see that a test fails and passes, but the code hasn’t changed, then it’s a flaky test. There’s many causes of flakiness.

What is an example of a flaky test?

An example can be seen in growing test suites - when pull request builds fail for changes you haven’t made. Put differently, when you see a test pass and fail without any code change. These failed tests are flaky tests.

What are common causes of flakiness?

Broken assumptions in test automation and development process can introduce flaky tests - for example, if test data is shared between different tests whether asynchronous, high concurrency, or sequential, the results of one test can affect another. 

Poorly written test code can also be a factor. Improper polling, race conditions, improper event dependency handling, shared test data, or timeout handling for network requests or page loads. Any of these can lead to flaky test failures and test flakiness.

End-to-end tests that rely on internal API uptime can cause test flakiness and test failures.

What's the impact of flaky tests?

Flaky tests can wreck havoc on the development process - from wasted developer time from test retries, to creating bugs and product instability and missed releases, time-consuming flaky tests can grind your development process to a halt.

What is the best way to resolve or fix flaky tests?

Devops, software engineering, and software development teams will often need to compare code changes, logs, and other context across test environments from before the test instability started, and after - adding retries or reruns can also help with debugging. Test detection and test execution tooling can help automate this process as well. 

BuildPulse enables you to find, assess impact metrics, quarantine, and fix flaky tests.

What are some strategies for preventing flaky tests?

Paying attention and prioritizing flaky tests as they come up can be a good way to prevent them from becoming an issue. This is where a testing culture is important - if a flaky test case is spotted by an engineer, it should be logged right away. This, however, takes a certain level of hygiene - BuildPulse can provide monitoring so flaky tests are caught right away.

What type of tests have flaky tests?

Flaky tests can be seen across the testing process - unit tests, integration tests, end-to-end tests, UI tests, acceptance tests.

What if I don't have that many flaky tests?

Flaky tests can be stealthy - often ignored by engineers and test runs are retried, they build up until they can’t be ignored anymore. These automated tests slow down developer productivity, impact functionality, and reduce confidence in test results and test suites. Better to get ahead while it’s easy and invest in test management.

It’s also important to prevent regressions to catch flakiness early while it’s manageable.

What languages and continuous integration providers does BuildPulse work with?

BuildPulse integrates with all continuous integration providers (including GitHub Actions, BitBucket Pipelines, and more), test frameworks, and workflows.

Combat non-determinism, drive test confidence, and provide the best experience you can to your developers!

How long does implementation/integration with BuildPulse take?

Implementation/integration takes 5 minutes!

What is the difference between a flaky test and a false positive?

A false positive is a test failure in your test suite due to an actual error in the code being executed, or a mismatch in what the test expects from the code.

A flaky test is when you have conflicting test results for the same code. For example, while running tests if you see that a test fails and passes, but the code hasn’t changed, then it’s a flaky test. There’s many causes of flakiness.

What is an example of a flaky test?

An example can be seen in growing test suites - when pull request builds fail for changes you haven’t made. Put differently, when you see a test pass and fail without any code change. These failed tests are flaky tests.

What are common causes of flakiness?

Broken assumptions in test automation and development process can introduce flaky tests - for example, if test data is shared between different tests whether asynchronous, high concurrency, or sequential, the results of one test can affect another. 

Poorly written test code can also be a factor. Improper polling, race conditions, improper event dependency handling, shared test data, or timeout handling for network requests or page loads. Any of these can lead to flaky test failures and test flakiness.

End-to-end tests that rely on internal API uptime can cause test flakiness and test failures.

What's the impact of flaky tests?

Flaky tests can wreck havoc on the development process - from wasted developer time from test retries, to creating bugs and product instability and missed releases, time-consuming flaky tests can grind your development process to a halt.

What is the best way to resolve or fix flaky tests?

Devops, software engineering, and software development teams will often need to compare code changes, logs, and other context across test environments from before the test instability started, and after - adding retries or reruns can also help with debugging. Test detection and test execution tooling can help automate this process as well. 

BuildPulse enables you to find, assess impact metrics, quarantine, and fix flaky tests.

What are some strategies for preventing flaky tests?

Paying attention and prioritizing flaky tests as they come up can be a good way to prevent them from becoming an issue. This is where a testing culture is important - if a flaky test case is spotted by an engineer, it should be logged right away. This, however, takes a certain level of hygiene - BuildPulse can provide monitoring so flaky tests are caught right away.

What type of tests have flaky tests?

Flaky tests can be seen across the testing process - unit tests, integration tests, end-to-end tests, UI tests, acceptance tests.

What if I don't have that many flaky tests?

Flaky tests can be stealthy - often ignored by engineers and test runs are retried, they build up until they can’t be ignored anymore. These automated tests slow down developer productivity, impact functionality, and reduce confidence in test results and test suites. Better to get ahead while it’s easy and invest in test management.

It’s also important to prevent regressions to catch flakiness early while it’s manageable.

What languages and continuous integration providers does BuildPulse work with?

BuildPulse integrates with all continuous integration providers (including GitHub Actions, BitBucket Pipelines, and more), test frameworks, and workflows.

Combat non-determinism, drive test confidence, and provide the best experience you can to your developers!

How long does implementation/integration with BuildPulse take?

Implementation/integration takes 5 minutes!

What is the difference between a flaky test and a false positive?

A false positive is a test failure in your test suite due to an actual error in the code being executed, or a mismatch in what the test expects from the code.

A flaky test is when you have conflicting test results for the same code. For example, while running tests if you see that a test fails and passes, but the code hasn’t changed, then it’s a flaky test. There’s many causes of flakiness.

What is an example of a flaky test?

An example can be seen in growing test suites - when pull request builds fail for changes you haven’t made. Put differently, when you see a test pass and fail without any code change. These failed tests are flaky tests.

What are common causes of flakiness?

Broken assumptions in test automation and development process can introduce flaky tests - for example, if test data is shared between different tests whether asynchronous, high concurrency, or sequential, the results of one test can affect another. 

Poorly written test code can also be a factor. Improper polling, race conditions, improper event dependency handling, shared test data, or timeout handling for network requests or page loads. Any of these can lead to flaky test failures and test flakiness.

End-to-end tests that rely on internal API uptime can cause test flakiness and test failures.

What's the impact of flaky tests?

Flaky tests can wreck havoc on the development process - from wasted developer time from test retries, to creating bugs and product instability and missed releases, time-consuming flaky tests can grind your development process to a halt.

What is the best way to resolve or fix flaky tests?

Devops, software engineering, and software development teams will often need to compare code changes, logs, and other context across test environments from before the test instability started, and after - adding retries or reruns can also help with debugging. Test detection and test execution tooling can help automate this process as well. 

BuildPulse enables you to find, assess impact metrics, quarantine, and fix flaky tests.

What are some strategies for preventing flaky tests?

Paying attention and prioritizing flaky tests as they come up can be a good way to prevent them from becoming an issue. This is where a testing culture is important - if a flaky test case is spotted by an engineer, it should be logged right away. This, however, takes a certain level of hygiene - BuildPulse can provide monitoring so flaky tests are caught right away.

What type of tests have flaky tests?

Flaky tests can be seen across the testing process - unit tests, integration tests, end-to-end tests, UI tests, acceptance tests.

What if I don't have that many flaky tests?

Flaky tests can be stealthy - often ignored by engineers and test runs are retried, they build up until they can’t be ignored anymore. These automated tests slow down developer productivity, impact functionality, and reduce confidence in test results and test suites. Better to get ahead while it’s easy and invest in test management.

It’s also important to prevent regressions to catch flakiness early while it’s manageable.

What languages and continuous integration providers does BuildPulse work with?

BuildPulse integrates with all continuous integration providers (including GitHub Actions, BitBucket Pipelines, and more), test frameworks, and workflows.

Combat non-determinism, drive test confidence, and provide the best experience you can to your developers!

How long does implementation/integration with BuildPulse take?

Implementation/integration takes 5 minutes!

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