Code resilience through static analysis and code coverage

Code Coverage

Oct 6, 2023

In software development, ensuring code quality and security is paramount. As projects grow in complexity, managing source code and guarding against vulnerabilities become even more crucial. This is where static analysis and code coverage prove to be invaluable tools in the developer's toolkit. In this article, we'll explore how these techniques contribute to software quality, security, and the development process.

Understanding Static Analysis and Source Code Security

Static analysis involves a comprehensive examination of the source code, without its execution. This technique dissects the code to uncover vulnerabilities, adherence to coding standards, and potential security issues. By utilizing static analysis tools, often available as open source or via platforms like GitHub, developers can efficiently scan the codebase and pinpoint areas that need attention.

Benefits of Static Analysis:

  1. Identifying security vulnerabilities early in the development process.

  2. Pinpointing potential code overflows and other security issues.

  3. Ensuring compliance with coding standards for better maintainability.

  4. Minimizing false positives to focus on actionable issues.

Leveraging Static Analysis for Code Quality

One of the key aspects of code quality is adhering to established coding standards and best practices. Static analysis, as a part of the software development life cycle, aids in maintaining and enhancing code quality by enforcing these standards. Whether the project is in Java, Python, PHP, or any other programming language, static analysis tools like FindBugs, Checkstyle, and many others can be seamlessly integrated into the development workflow.

Code Coverage: Validating the Extent of Testing

Code coverage is a metric that measures the proportion of source code that is covered by the test suite. It's an essential gauge to evaluate the thoroughness of testing. The goal is to cover as much of the codebase as possible through tests, ensuring that the software behaves as expected across different scenarios.

Benefits of Code Coverage:

  1. Evaluating the effectiveness of software testing.

  2. Ensuring that every line of code is validated during the testing process.

  3. Identifying untested or poorly tested sections of the code.

Integrating Static Analysis and Code Coverage in Development Workflow

For development teams, seamlessly integrating static analysis and code coverage into the development workflow is pivotal. These processes need to be automated, becoming an integral part of the continuous integration and continuous deployment (CI/CD) pipeline. By automating static analysis and incorporating it into the CI/CD pipeline, developers can promptly address vulnerabilities and maintain code quality throughout the software development life cycle.

However, not all parts of your application need the same levels of coverage - business critical paths should have higher standards. BuildPulse Code Coverage enables granular enforcement, freeing up developer time for hardening sensitive areas of the codebase and working on roadmap.

Security and Beyond: Dynamic Analysis and the Big Picture

While static analysis focuses on potential issues within the source code, dynamic analysis involves running the software to identify problems that may manifest during runtime. This comprehensive approach, encompassing static and dynamic analysis, contributes to a resilient software system.


In the ever-evolving landscape of software engineering, ensuring the resilience and security of code is paramount. By integrating static analysis and code coverage into the development process, development teams can fortify their code against vulnerabilities, adhere to coding standards, and enhance overall software quality. Embracing these techniques not only aids in identifying and addressing security issues but also fosters a culture of continuous improvement and vigilance, crucial in the dynamic world of software development.


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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