Missing data imputation techniques for software effort estimation: a study of recent issues and challenges
Software effort estimation is one the critical aspects of software engineering. It revolves around predicting the required efforts needed to complete a software task. However, any estimation technique or model relies on an input data in which it defines and predicts future values. Missing data and v...
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my.utm.926032021-10-28T10:18:24Z http://eprints.utm.my/id/eprint/92603/ Missing data imputation techniques for software effort estimation: a study of recent issues and challenges Almutlaq, Ayman Jalal Hassan Jawawi, Dayang N. A. QA75 Electronic computers. Computer science Software effort estimation is one the critical aspects of software engineering. It revolves around predicting the required efforts needed to complete a software task. However, any estimation technique or model relies on an input data in which it defines and predicts future values. Missing data and values within such data is a common occurrence in the software development industry and thus it leads to inaccurate predictions or misleading results. Thus, Missing Data is an important aspect of effort estimation models that is required to be addressed. However, Missing Data is not without its gaps and issues. This review aims at elaborating the recent issues and gaps that exist within the missing data and software effort estimation field. This may allow future researchers to get a better grasp and understanding of the inner workings of Missing Data and the methods through which these challenges can be addressed. 2020-01 Conference or Workshop Item PeerReviewed Almutlaq, Ayman Jalal Hassan and Jawawi, Dayang N. A. (2020) Missing data imputation techniques for software effort estimation: a study of recent issues and challenges. In: 4th International Conference of Reliable Information and Communication Technology, IRICT 2019, 22 September 2019 - 23 September 2019, Johor Bahru, Johor, Malaysia. http://dx.doi.org/10.1007/978-3-030-33582-3_107 |
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QA75 Electronic computers. Computer science Almutlaq, Ayman Jalal Hassan Jawawi, Dayang N. A. Missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
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Software effort estimation is one the critical aspects of software engineering. It revolves around predicting the required efforts needed to complete a software task. However, any estimation technique or model relies on an input data in which it defines and predicts future values. Missing data and values within such data is a common occurrence in the software development industry and thus it leads to inaccurate predictions or misleading results. Thus, Missing Data is an important aspect of effort estimation models that is required to be addressed. However, Missing Data is not without its gaps and issues. This review aims at elaborating the recent issues and gaps that exist within the missing data and software effort estimation field. This may allow future researchers to get a better grasp and understanding of the inner workings of Missing Data and the methods through which these challenges can be addressed. |
format |
Conference or Workshop Item |
author |
Almutlaq, Ayman Jalal Hassan Jawawi, Dayang N. A. |
author_facet |
Almutlaq, Ayman Jalal Hassan Jawawi, Dayang N. A. |
author_sort |
Almutlaq, Ayman Jalal Hassan |
title |
Missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
title_short |
Missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
title_full |
Missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
title_fullStr |
Missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
title_full_unstemmed |
Missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
title_sort |
missing data imputation techniques for software effort estimation: a study of recent issues and challenges |
publishDate |
2020 |
url |
http://eprints.utm.my/id/eprint/92603/ http://dx.doi.org/10.1007/978-3-030-33582-3_107 |
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1715189662463557632 |
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13.160551 |