A Systematic Review of Software Development Cost Estimation Studies

By Magne Jørgensen, Martin J. Shepperd. IEEE Transactions on Software Engineering, 2007

1,082 citations recorded by the source corpus.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/d1cdcb490d1fca41cd278099f8b6eb0760cb10c3

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Citations in the corpus

A systematic review of software fault prediction studies (2009, methodology): “We did not search for papers based on issue-by-issue, manual reading of titles of all published papers in journals, as Jorgensen and Shepperd (2007) did.”
Software process improvement in small and medium software enterprises: a systematic review (2008, result): “We have, moreover, looked at other similar systematic reviews (Hannay et al. 2007; Jørgensen and Shepperd 2007; Staples and Niazi 2007).”
Automated Parameter Optimization of Classification Techniques for Defect Prediction Models (2016, background): “[23] also point out that the unstable performance estimates that are produced by classification techniques may introduce bias, which can mislead different research groups to draw erroneous conclusions.”
An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation (2018, background): “Localizing and fixing bugs is known to be an effort-prone and time-consuming task for software developers [33, 71, 86].”
GenProg: A Generic Method for Automatic Software Repair (2012, background): “Software maintenance, of which bug repair is a major component [3], [4], is time-consuming and expensive, accounting for as much as 90 percent of the cost of a software project [5] at a total cost of up to $70 billion per year in the US [6], [7].”
Systematic literature review of machine learning based software development effort estimation models (2012, methodology): “Jørgensen and Shepperd [1] conducted a review which identifies up to 11 estimation methods used for SDEE.”
The Impact of Automated Parameter Optimization on Defect Prediction Models (2018, neutral): “[66] point out”
Using mapping studies as the basis for further research - A participant-observer case study (2011, background): “In addition, an SLR must be careful to discount duplicate reports of the same study whereas Jørgensen and Shepperd explicitly state that they included different papers discussing the same study.”
Guidelines for conducting systematic mapping studies in software engineering: An update (2015, methodology): “A set of studies also used existing literature studies [32,51,52] as templates for their systematic reviews.”
Evaluating prediction systems in software project estimation (2012, background): “For an overview see the 2007 mapping study by Jørgensen and Shepperd [16] which identified more than 300 journal papers that examined cost or effort prediction (and this number has continued to grow and, of course, excludes conference publications).”
Communicative Agents for Software Development (2023, background): “2967, significantly lower than traditional custom software development companies’ expenses [17; 20; 30].”
Using Mapping Studies in Software Engineering (2008, background): “This study is reported as ( Jorgensen & Shepperd 2007 ).”
A Systematic Literature Review on Fault Prediction Performance in Software Engineering (2012, positive): “adapted Jørgensen and Shepperd's [4] methodology.”
Systematic Mapping Studies in Software Engineering (2008, background): “Only two reviews (7,8: (Sjøberg et al. 2005, Jørgensen & Shepperd 2007)) focused mainly on classiﬁcations and taxonomies and presented frequencies of papers in identiﬁed categories through thematic analysis.”
Systematic literature reviews in software engineering - A systematic literature review (2009, background): “A database of cost estimation papers from over 70 journals [16] has been the basis of many of the detailed cost estimation studies authored or co-authored by Jørgensen and the database of 103 software experiments [36] has allowed researchers to assess a number of specific research trends in software”
Software development in startup companies: A systematic mapping study (2014, methodology): “extracting the following data, inspired by other similar studies [57, 58]:”