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A systematic review of web resource estimation

Published: 21 September 2012 Publication History

Abstract

Background: Web development plays an important role in today's industry, so an in depth view into Web resource estimation would be valuable. However a systematic review (SR) on Web resource estimation in its entirety has not been done.
Aim: The aim of this paper is to present a SR of Web resource estimation in order to define the current state of the art, and to identify any research gaps that may be present.
Method: Research questions that would address the current state of the art in Web resource estimation were first identified. A comprehensive literature search was then executed resulting in the retrieval of 84 empirical studies that investigated any aspect of Web resource estimation. Data extraction and synthesis was performed on these studies with these research questions in mind.
Results: We have found that there are no guidelines with regards to what resource estimation technique should be used in a particular estimation scenario, how it should be implemented, and how its effectiveness should be evaluated. Accuracy results vary widely and are dependent on numerous factors. Research has focused on development effort/cost estimation, neglecting other facets of resource estimation like quality and maintenance. Size measures have been used in all but one study as a resource predictor.
Conclusions: Our results suggest that there is plenty of work to be done in the field of Web resource estimation whether it be investigating a more comprehensive approach that considers more than a single resource facet, evaluating other possible resource predictors, or trying to determine guidelines that would help simplify the process of selecting a resource estimation technique.

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cover image ACM Other conferences
PROMISE '12: Proceedings of the 8th International Conference on Predictive Models in Software Engineering
September 2012
126 pages
ISBN:9781450312417
DOI:10.1145/2365324
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

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Publication History

Published: 21 September 2012

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  1. systematic review
  2. web resource estimation

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PROMISE '12 Paper Acceptance Rate 12 of 24 submissions, 50%;
Overall Acceptance Rate 98 of 213 submissions, 46%

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  • (2023)Comparing Measured Agile Software Development Metrics Using an Agile Model-Based Software Engineering Approach versus Scrum OnlySoftware10.3390/software20300152:3(310-331)Online publication date: 26-Jul-2023
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