The objective of this paper is to examine the efficacy of test impact analysis in a setting of continuous testing, where automated test cases are routinely run to guarantee the integration of high-quality codes. While continuous testing can enhance code quality and minimize maintenance workload, it may also lead to a notable rise in overhead for test execution. Building on previous research, we introduce a new static class-level technique by constructing test cases to class dependency graphs from abstract syntax trees using JavaParser and applying it to seven Java systems. Like prior findings, we observe that, despite a small number of changed files in code changes, roughly 40 percent of test cases are impacted and require execution on average. Nonetheless, we conclude that test impact analysis can serve as a powerful tool for reducing test overhead. Moreover, we compare our proposed technique with a state-of-the-art static class-level method and find that our approach outperforms by achieving roughly a 13 percent reduction in selecting impacted tests on the commonly evaluated systems.