Test Smarter Not Harder: Shift Testing Left and Right with Test Impact Analysis - Part 2
August 19, 2019

Mark Lambert
Applitools

Software testing is still a bottleneck, even after the implementation of modern development processes like Agile, DevOps, and Continuous Integration/Deployment. In some cases, software teams aren't testing nearly enough and have to deal with bugs and security vulnerabilities at the later stages of the development cycle, which creates a false assumption that these new processes can't deliver on their promise. One solution to certain classes of issues is shift right testing, which relies on monitoring the application in a production environment, but it requires a rock solid infrastructure to roll back new changes if a critical defect arises.

Start with Test Smarter Not Harder: Shift Testing Left and Right with Test Impact Analysis - Part 1

Testing Smarter, Not Harder, by Focusing Your Testing

Most software isn't fully tested, and the decision of what to test is essentially based on developers' best guesses about what is critical functionality. During a SCRUM sprint, or an iteration in other processes, it's difficult to determine what to test, because, of course, "test everything" isn't an option. Since timelines are short, only parts of the software that were updated by the latest functionality can be tested, but exactly what code is impacted is usually unknown. Test automation helps, but without understanding exactly where and what to test, test coverage is inadequate.

These shortcomings can be overcome by using test impact analysis, which is a multivariate analysis of test coverage, code changes, and dependencies that pinpoints exactly what code needs to be tested. In addition, these exact tests can be scheduled and executed automatically.

Test impact analysis works at the developer level within the IDE, collecting information about which code is exercised by which tests, and applies that information within the developer's IDE as the developer is changing code, enabling the developer to easily identify and execute the specific tests that need to be run to verify that the changed code doesn't break any tests. Also, keeping track of which affected tests have been run, which have passed, and which have failed, makes it easy for the developer to determine which tests still need to be run, or which tests have failed and need to be addressed. Once all tests have been run and are passing, the developer knows that it's safe to commit their code and move on.

Test impact analysis works within a CI/CD process by integrating seamlessly into a project's build system, to get immediate feedback on changes. Test impact analysis identifies which code has changed since the baseline build (i.e. the last nightly build), determines which tests need to be run to exercise that code, and then runs just that subset of tests. This workflow enables teams to set up CI jobs that only run tests based on the most recent code changes, shrinking the amount of time it takes to run a CI job from hours to minutes.

Test impact analysis provides the following key benefits:

Understand what each test covers: Automatically correlating test execution data with test coverage data identifies which tests need to be run, based on the code currently being developed. Users save time without having to run unnecessary tests, and teams benefit from immediate feedback during development and after code check-in.

Understand what has changed: Developers often don't know which tests to run to validate code changes, so they either check their code in without running any tests (a very bad practice), or they run only one or two tests that they know about (which easily misses some), or they run all of their tests (which wastes time). Test impact analysis immediately identifies which tests are related to which code changes and are automatically executed. Checked-in code becomes more stable since it has been thoroughly tested prior to check-in.

Focus on tests that validate changes and impacted dependencies: Identifying and running just the set of tests needed to verify all of the code changes, and affected dependencies, that have been committed since the last baseline build (usually the nightly build), significantly decreasing the amount of time it takes to run CI. This allows teams to benefit from a true CI process.

Immediate and Ongoing Feedback: Identifying not just direct dependencies between tests and code, but indirect dependencies as well, test impact analysis helps teams understand as soon as possible after code is checked in whether the code broke any tests.

Summary

To greatly decrease the testing bottleneck in development to improve the efficiency of the "saw tooth" effort that testers put into every iteration, development teams can benefit from test impact analysis technology. Test automation with test impact analysis means focusing testing specifically on changes made during each iteration, and testing exactly what needs to be tested, automatically. These teams optimize their in-development testing effort with instant feedback on what needs to be done, what code fails testing, and what other code is impacted by new changes.

Mark Lambert is VP and Evangelist at Applitools
Share this

Industry News

April 23, 2025

Kubernetes 1.33 was released today.

Kubernetes 1.33 Release Information

April 23, 2025

Docker announced a major expansion of its AI initiative with the upcoming Docker MCP Catalog and Docker MCP Toolkit.

April 23, 2025

Perforce Software announced the release of its latest platform update for Puppet Enterprise Advanced, designed to streamline DevSecOps practices and fortify enterprise security postures.

April 23, 2025

Azul announced JVM Inventory, a new feature of Azul Intelligence Cloud designed to address the complexity and risk of migrating off Oracle Java.

April 23, 2025

LaunchDarkly announced the acquisition of Highlight, a powerful, open source, full-stack application monitoring platform known for its error monitoring, logging, distributed tracing and session replay capabilities.

April 22, 2025

O’Reilly announced AI Codecon—a groundbreaking virtual conference series dedicated to exploring the rapidly evolving world of AI-assisted software development.

April 22, 2025

Veracode unveiled new capabilities offering proactive risk mitigation and automated security at enterprise scale.

April 22, 2025

Snyk launched Snyk API & Web, delivering a dynamic application security testing (DAST) solution designed to meet the growing demands of modern and increasingly AI-powered software development.

April 21, 2025

Postman announced new releases designed to help organizations build APIs faster, more securely, and with less friction.

April 21, 2025

SnapLogic announced AgentCreator 3.0, an evolution in agentic AI technology that eliminates the complexity of enterprise AI adoption.

April 17, 2025

GitLab announced the general availability of GitLab Duo with Amazon Q.

April 17, 2025

Perforce Software and Liquibase announced a strategic partnership to enhance secure and compliant database change management for DevOps teams.

April 17, 2025

Spacelift announced the launch of Saturnhead AI — an enterprise-grade AI assistant that slashes DevOps troubleshooting time by transforming complex infrastructure logs into clear, actionable explanations.

April 16, 2025

CodeSecure and FOSSA announced a strategic partnership and native product integration that enables organizations to eliminate security blindspots associated with both third party and open source code.