Swarnima Singh Gautam - Academia.edu (original) (raw)
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Westerdals Oslo School of Arts, Communication & Technology
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Papers by Swarnima Singh Gautam
Journal of Software: Evolution and Process
Journal of Software: Evolution and Process
The software developers and researchers have been facing difficulties regarding software developm... more The software developers and researchers have been facing difficulties regarding software development effort estimation (SDEE) since 1960s. Both overestimation and underestimation are problematic for future software development. The software engineering field is continuously adapting new technologies and development methodologies, so there is always a requirement to have an accurate SDEE method that can cater the needs of continually growing software industry. The major purpose of this state-of-the-art review is to provide an additional insight of existing SDEE studies while considering five points of reference: techniques used to construct models, strengths and weaknesses of different models, availability of benchmark data sets, data set characteristics, generalization ability of models. We have performed a comprehensive review of SDEE studies published in the period 1981-2016. We have defined a new scheme of categorizing existing SDEE models. We have found that a majority of available data sets do not include complete information of projects, which misleads the direction of research. To compare SDEE models, we recommend to use same data sets while focusing on specific aspects of accuracy as none of SDEE studies has yet been able to compare all the existing models over same data sets while considering same aspects of accuracy.
Journal of Software: Evolution and Process
Journal of Software: Evolution and Process
The software developers and researchers have been facing difficulties regarding software developm... more The software developers and researchers have been facing difficulties regarding software development effort estimation (SDEE) since 1960s. Both overestimation and underestimation are problematic for future software development. The software engineering field is continuously adapting new technologies and development methodologies, so there is always a requirement to have an accurate SDEE method that can cater the needs of continually growing software industry. The major purpose of this state-of-the-art review is to provide an additional insight of existing SDEE studies while considering five points of reference: techniques used to construct models, strengths and weaknesses of different models, availability of benchmark data sets, data set characteristics, generalization ability of models. We have performed a comprehensive review of SDEE studies published in the period 1981-2016. We have defined a new scheme of categorizing existing SDEE models. We have found that a majority of available data sets do not include complete information of projects, which misleads the direction of research. To compare SDEE models, we recommend to use same data sets while focusing on specific aspects of accuracy as none of SDEE studies has yet been able to compare all the existing models over same data sets while considering same aspects of accuracy.