The prolonged continuous integration (CI) runs are affecting timely feedback to software developers. Test-case prioritization (TCP) aims to expose faults sooner by reordering tests such that the ones more likely to fail are run earlier. TCP is thus especially important for long-running test suites. While many studies have explored TCP, they are based on outdated CI builds from over 10 years ago with test suites that last several minutes, or builds from inaccessible, proprietary projects. In this paper, we present LRTS, the first dataset of long-running test suites, with 21,255 CI builds and 57,437 test-suite runs from 10 large-scale, open-source projects that use Jenkins CI. LRTS spans from 2020 to 2023, with an average test-suite run duration of 6.5 hours. On LRTS, we study the effectiveness of 59 leading TCP techniques, the impact of confounding test failures on TCP, and TCP for failing tests with no prior failures. We revisit prior key findings (9 confirmed, 2 refuted) and establish 3 new findings. Our results show that prioritizing faster tests that recently failed performs the best, outperforming the sophisticated techniques.

Today's software failures have two dominating root causes: code bugs and misconfigurations. To combat failure-inducing software changes, unified regression testing (URT) is needed to synergistically test the changed code and all changed production configurations for deployment reliability. However, URT could incur high cost, as it needs to run a large number of tests under multiple configurations. Regression test selection (RTS) can reduce regression testing cost. Unfortunately, no existing RTS technique reasons about code and configuration changes collectively. We introduce Unified Regression Test Selection (uRTS) to effectively reduce the cost of URT. uRTS supports project changes on 1) code only, 2) configurations only, and 3) both code and configurations. It selects regular tests and configuration tests with a unified selection algorithm. The uRTS algorithm analyzes code and configuration dependencies of each test across runs and across configurations. uRTS provides the same safety guarantee as the state-of-the-art RTS while selecting fewer tests and, more importantly, reducing the end-to-end testing time. We implemented uRTS on top of Ekstazi (a RTS tool for code changes) and Ctest (a configuration testing framework). We evaluate uRTS on hundreds of code revisions and dozens of configurations of five large projects. The results show that uRTS reduces the end-to-end testing time, on average, by 3.64X compared to executing all tests and 1.87X compared to a competitive reference solution that directly extends RTS for URT.