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Using developers' feedback to improve code smell detection., , , , and . SAC, page 1661-1663. ACM, (2015)Developers' perception matters: machine learning to detect developer-sensitive smells., , , , and . Empir. Softw. Eng., 27 (7): 195 (2022)Developers' viewpoints to avoid bug-introducing changes., , , , , , , and . Inf. Softw. Technol., (2022)Assessing fine-grained feature dependencies., , , , , and . Inf. Softw. Technol., (2016)Identifying method-level mutation subsumption relations using Z3., , , , , , , , and . Inf. Softw. Technol., (2021)Manual Tests Do Smell! Cataloging and Identifying Natural Language Test Smells., , , , , , , , , and . ESEM, page 1-11. IEEE, (2023)Beyond the Code: Investigating the Effects of Pull Request Conversations on Design Decay., , , , , , , , , and 1 other author(s). ESEM, page 1-12. IEEE, (2023)A Qualitative Analysis of Variability Weaknesses in Configurable Systems with #ifdefs., , , , , and . VaMoS, page 51-58. ACM, (2018)Search-based many-criteria identification of microservices from legacy systems., , , , , , , and . GECCO Companion, page 305-306. ACM, (2020)Investigating the social representations of code smell identification: a preliminary study., , , , , , and . CHASE@ICSE, page 53-60. IEEE / ACM, (2019)