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An extraction method to collect data on defects and effort evolution in a constantly modified system

Published: 23 May 2011 Publication History

Abstract

This paper describes a data extraction method that was carried out on a set of historical development documentation, related to a commercial software system for mobile platform. This method is part of a major project, which aims to identify evidences of technical debt via the analysis of the defect evolution and effort estimation deviation, verifying if there are relations between these concepts and project decisions during the cycles of development. We intend that a future analysis of such data supports the identification of patterns regarding specific decisions and variations of the defect number/frequency and effort deviation. Thus, such patterns could assist project managers during future project decisions, mainly regarding the maintenance and evolution stages.

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Cited By

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  • (2022)Reproducibility in the technical debt domainActa Universitatis Sapientiae, Informatica10.2478/ausi-2021-001613:2(335-360)Online publication date: 2-Feb-2022
  • (2021)Technical Debt Prioritization: Taxonomy, Methods Results, and Practical Characteristics2021 47th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA53835.2021.00034(206-213)Online publication date: Sep-2021
  • (2016)Theoretical conceptualization of TDJournal of Systems and Software10.1016/j.jss.2016.05.043120:C(219-237)Online publication date: 1-Oct-2016
  • Show More Cited By

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cover image ACM Conferences
MTD '11: Proceedings of the 2nd Workshop on Managing Technical Debt
May 2011
54 pages
ISBN:9781450305860
DOI:10.1145/1985362
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2011

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Author Tags

  1. decision making
  2. effort estimation
  3. evolution of defects

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  • Short-paper

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ICSE11
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ICSE11: International Conference on Software Engineering
May 23, 2011
HI, Waikiki, Honolulu, USA

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Overall Acceptance Rate 40 of 92 submissions, 43%

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Cited By

View all
  • (2022)Reproducibility in the technical debt domainActa Universitatis Sapientiae, Informatica10.2478/ausi-2021-001613:2(335-360)Online publication date: 2-Feb-2022
  • (2021)Technical Debt Prioritization: Taxonomy, Methods Results, and Practical Characteristics2021 47th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA53835.2021.00034(206-213)Online publication date: Sep-2021
  • (2016)Theoretical conceptualization of TDJournal of Systems and Software10.1016/j.jss.2016.05.043120:C(219-237)Online publication date: 1-Oct-2016
  • (2014)Managing Technical Debt in Enterprise Software PackagesIEEE Transactions on Software Engineering10.1109/TSE.2014.232702740:8(758-772)Online publication date: 1-Aug-2014
  • (2014)Applying Metrics to Identify and Monitor Technical Debt Items during Software EvolutionProceedings of the 2014 IEEE International Symposium on Software Reliability Engineering Workshops10.1109/ISSREW.2014.59(92-95)Online publication date: 3-Nov-2014
  • (2013)Towards a model for optimizing technical debt in software productsProceedings of the 4th International Workshop on Managing Technical Debt10.5555/2663297.2663306(51-54)Online publication date: 20-May-2013
  • (2013)Towards a model for optimizing technical debt in software products2013 4th International Workshop on Managing Technical Debt (MTD)10.1109/MTD.2013.6608679(51-54)Online publication date: May-2013

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