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Investigating the Identification of Technical Debt Through Code Comment Analysis.

, , , , and . ICEIS (Revised Selected Papers), volume 291 of Lecture Notes in Business Information Processing, page 284-309. Springer, (2016)

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A systematic mapping study on mining software repositories., , , , , and . SAC, page 1472-1479. ACM, (2016)Industrial and OSS developers' profiles: a family of experiments to evaluate a pioneering neuro-linguistic method for preferred representational systems automatic detection., , , , and . J. Braz. Comput. Soc., 27 (1): 4 (2021)Identifying Technical Debt through a Code Comment Mining Tool., , , , , , and . SBSI, page 18:1-18:8. ACM, (2019)Procedural x OO - A Corporative Experiment on Source Code Clone Mining., , and . ICEIS (2), page 395-402. SciTePress, (2017)Recovering Valuable Information Behaviour from OSS Contributors: An Exploratory Study., , , , and . SEKE, page 474-477. Knowledge Systems Institute Graduate School, (2014)A Study on Identification of Documentation and Requirement Technical Debt through Code Comment Analysis., , , and . SBQS, page 21-30. ACM, (2018)A Contextualized Vocabulary Model for identifying technical debt on code comments., , , and . MTD@ICSME, page 25-32. IEEE Computer Society, (2015)Identifying self-admitted technical debt through code comment analysis with a contextualized vocabulary., , , and . Inf. Softw. Technol., (2020)Decision Criteria for the Payment of Technical Debt in Software Projects: A Systematic Mapping Study., , , and . ICEIS (1), page 572-579. SciTePress, (2016)Impacts of agile requirements documentation debt on software projects: a retrospective study., , , , , and . SAC, page 1290-1295. ACM, (2016)