The increasing complexity of modern software systems has exacerbated the challenges of debugging, often leading to significant financial and time costs. This paper explores the effectiveness of Spectrum-Based Fault Localization (SBFL) as an automated debugging technique using the Flacoco tool. The research evaluates the tool's performance on the IntroClassJava benchmark dataset, analyzing the suspiciousness scores of Java programs with known defects. The results indicate that Flacoco significantly reduces the search space for developers by highlighting potentially faulty code elements. However, discrepancies in the accuracy of fault localization reveal limitations related to test case quality, underscoring the importance of high-quality, comprehensive test cases in the debugging process. This study contributes to enhancing the practical application of SBFL in industrial software development and demonstrates the potential of Flacoco for more efficient and accurate fault localization.