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Cross-Layer Measurement for the Analysis of DVB-T System Performance.

, , , and . IEEE Trans. Instrumentation and Measurement, 57 (7): 1304-1312 (2008)

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OSS developers context-specific Preferred Representational systems: A initial Neurolinguistic text analysis of the Apache mailing list., , , and . MSR, page 126-129. IEEE Computer Society, (2010)Uma análise da relação entre code smells e dívida técnica auto-admitida., , , , and . VEM, page 37-44. Sociedade Brasileira de Computação, (2019)Cross-Layer Measurement for the Analysis of DVB-T System Performance., , , and . IEEE Trans. Instrumentation and Measurement, 57 (7): 1304-1312 (2008)On Comment Patterns that are Good Indicators of the Presence of Self-Admitted Technical Debt and those that Lead to False Positive Items., , , and . AMCIS, Association for Information Systems, (2021)A Systematic Mapping Study on Software Comments Analysis., , , , and . SEKE, page 681-680. KSI Research Inc. and Knowledge Systems Institute Graduate School, (2018)A Contextualized Vocabulary Model for identifying technical debt on code comments., , , and . MTD@ICSME, page 25-32. IEEE Computer Society, (2015)Impacts of agile requirements documentation debt on software projects: a retrospective study., , , , , and . SAC, page 1290-1295. ACM, (2016)Decision Criteria for the Payment of Technical Debt in Software Projects: A Systematic Mapping Study., , , and . ICEIS (1), page 572-579. SciTePress, (2016)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)A Study on Identification of Documentation and Requirement Technical Debt through Code Comment Analysis., , , and . SBQS, page 21-30. ACM, (2018)