What is Launchable?
Launchable offers an AI Co-Pilot aimed at enhancing test suite intelligence and optimization for software development teams. It focuses on reducing test runtimes, enabling smarter test triaging, providing valuable test health insights, and analyzing test failures effectively. By removing friction from the development-test loop, Launchable helps teams iterate and deploy software more rapidly and with greater confidence. The platform is designed to address common challenges such as lengthy test execution times, noisy results from flaky tests, manual root-cause analysis of failures, slow propagation of failure awareness, and cumbersome tracking of issues and fixes.
Leveraging machine learning and generative AI, Launchable correlates code changes with tests to intelligently select a subset of tests most likely to identify failures (Predictive Test Selection). It also groups test failures based on underlying issues, uses GenAI to summarize error logs for quicker comprehension (Intelligent Test Failure Diagnostics), and provides personalized notifications about test failures. Furthermore, it offers insights into test suite health, including identifying flaky, long-running, or consistently failing/passing tests, allowing teams to prioritize improvements and maintain trust in their testing processes. Launchable integrates with various CI servers, test runners, and frameworks and is SOC 2 certified.
Features
- Predictive Test Selection (PTS): Intelligently selects a subset of tests based on code changes to reduce runtimes up to 98%.
- Intelligent Test Failure Diagnostics: Groups test failures by underlying issues and uses GenAI to summarize error logs for faster root-cause analysis.
- Test Suite Insights: Provides metrics on test health, including automatic detection and impact scoring of flaky, longest, always failing, and never failing tests.
- Test Failure Notifications: Delivers personalized notifications (e.g., via Slack, GitHub) to developers and QA when tests fail, indicating potential breaks caused by their changes.
- Flakiness Dashboard: Prioritizes flaky tests based on their negative impact, aiding in sprint planning and test maintenance.
- Integration Support: Works with popular CI servers (Jenkins, CircleCI, GitHub Actions), test runners (Cypress, Maven, pytest), and frameworks (JUnit, Selenium).
Use Cases
- Accelerating feedback loops by running only relevant tests for specific code changes.
- Reducing test execution time and associated costs, especially for large test suites.
- Improving the efficiency of test failure triaging and root-cause analysis.
- Identifying and prioritizing the fixing of flaky or unhealthy tests.
- Optimizing UI, integration, and nightly test runs.
- Enabling shift-left testing by providing faster feedback earlier in the development cycle.
- Managing and tracking test issues across different branches and test sessions.
FAQs
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What problems does Launchable solve?
Launchable addresses long test runtimes, noise from flaky/unhealthy tests, manual root-cause analysis of failures, slow test failure awareness, and cumbersome issue tracking in the dev-test loop. -
How does Launchable speed up testing?
It uses Predictive Test Selection (PTS), correlating code changes to tests to run an ML-based subset, significantly reducing execution time while still finding failing builds. -
How does Launchable help with test failures?
It offers Intelligent Test Failure Diagnostics, grouping failures by underlying issues, summarizing logs with GenAI, and providing personalized notifications to relevant team members. -
What kind of insights does Launchable provide?
It provides insights into test suite health, identifying flaky tests, longest tests, always failing tests, and never failing tests, along with trends on session duration and failure ratios. -
What tools does Launchable integrate with?
Launchable integrates with various CI servers (like Jenkins, CircleCI, GitHub Actions), test runners (like Cypress, Maven, pytest), and test frameworks (like JUnit, Selenium).
Related Queries
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Launchable Uptime Monitor
Average Uptime
100%
Average Response Time
164.8 ms
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