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Improving Defect Localization by Classifying the Affected Asset Using Machine Learning.

, , , and . SWQD, volume 338 of Lecture Notes in Business Information Processing, page 106-122. Springer, (2019)

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Generating Domain Models from Ontologies., and . OOIS, volume 2425 of Lecture Notes in Computer Science, page 160-166. Springer, (2002)Predicting weekly defect inflow in large software projects based on project planning and test status., and . Inf. Softw. Technol., 50 (7-8): 782-796 (2008)Empirical assessment of using stereotypes to improve comprehension of UML models: A set of experiments., , and . J. Syst. Softw., 79 (5): 727-742 (2006)A Pragmatic View on Code Complexity Management., , and . Computer, 52 (2): 14-22 (2019)Assessing the impact of meta-model evolution: a measure and its automotive application., , , and . Softw. Syst. Model., 18 (2): 1419-1445 (2019)Measuring the impact of changes to the complexity and coupling properties of automotive software systems., , , and . J. Syst. Softw., 86 (5): 1275-1293 (2013)Recognizing lines of code violating company-specific coding guidelines using machine learning., , , , and . Empir. Softw. Eng., 25 (1): 220-265 (2020)Mining Task-Specific Lines of Code Counters., , , and . IEEE Access, (2023)Improving Completeness of Measurement Systems for Monitoring Software Development Workflows., , and . SWQD, volume 133 of Lecture Notes in Business Information Processing, page 230-243. Springer, (2013)Automotive Software Architectures: An Introduction. Springer, Cham, (2017)