Effort Prediction in Iterative Software Development Processes -- Incremental Versus Global Prediction Models

Abrahamsson, Pekka; Moser, Raimund; Pedrycz, Witold; Sillitti, Alberto; Succi, Giancarlo

doi:10.1109/esem.2007.16

Cited by 39 publications

(27 citation statements)

References 19 publications

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“…Table 4 describes the number of studies passing through different stages of the SLR. Details of the excluded papers during the full text screening and the QA phases are: eight papers [29,40,44,[48][49][50][51][52] were excluded due to not passing the inclusion criteria, two due to a low quality score [25,53] and one [54] due to reporting a study already included in another paper [14]. Breakup of the eight papers excluded on inclusion & exclusion criteria is as under:…”

Section: Resultsmentioning

confidence: 99%

“…Table 1 lists the keywords used by some primary studies on effort estimation in ASD. 12 Agile Methods [26,32,42] 13 Agile Processes [43] 14 Agile Development [33,36,39,43] 15 Agile Estimation, Agile Estimating [26,27,30,44] 16 Extreme Programming [10,14,35,37,40] 17 Scrum [13,25,28,30,36] 18 Agile Project Management [29,31] 19 Agile Projects [29,32] 20 Agile Teams [34] 21 Agile Methodology [35,39] 22 Agile Planning [39] The term "agile software development" has a large number of synonyms and alternate terms that are used in literature; some are listed in table 1 above. Given that as we added more studies to our set of known primary studies more alternate terms for agile software development were found, we decided to simply use one word (i.e.…”

Section: Query Stringmentioning

confidence: 99%

“…A detailed incremental prediction model is proposed in [14] for effort prediction in agile and iterative development environments. This model was compared with a traditional global prediction model in an Extreme Programming (XP) environment, and results showed that the new incremental model outperformed the traditional estimation model in the early phases of development.…”

Section: Introductionmentioning

confidence: 99%

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Effort estimation in agile software development

Usman

Mendes

Weidt

et al. 2014

Proceedings of the 10th International Conference on Predictive Models in Software Engineering

169

135

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Context: Ever since the emergence of agile methodologies in 2001, many software companies have shifted to Agile Software Development (ASD), and since then many studies have been conducted to investigate effort estimation within such context; however to date there is no single study that presents a detailed overview of the state of the art in effort estimation for ASD. Objectives: The aim of this study is to provide a detailed overview of the state of the art in the area of effort estimation in ASD. Method: To report the state of the art, we conducted a systematic literature review in accordance with the guidelines proposed in the evidence-based software engineering literature. Results: A total of 25 primary studies were selected; the main findings are: i) Subjective estimation techniques (e.g. expert judgment, planning poker, use case points estimation method) are the most frequently applied in an agile context; ii) Use case points and story points are the most frequently used size metrics respectively; iii) MMRE (Mean Magnitude of Relative Error) and MRE (Magnitude of Relative Error) are the most frequently used accuracy metrics; iv) team skills, prior experience and task size are cited as the three important cost drivers for effort estimation in ASD; and v) Extreme Programming (XP) and SCRUM are the only two agile methods that are identified in the primary studies. Conclusion: Subjective estimation techniques, e.g. expert judgment-based techniques, planning poker or the use case points method, are the one used the most in agile effort estimation studies. As for the size metrics, the ones that were used the most in the primary studies were story points and use case points. Several research gaps were identified, relating to the agile methods, size metrics and cost drivers, thus suggesting numerous possible avenues for future work.

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Section: Resultsmentioning

confidence: 99%

Section: Query Stringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effort estimation in agile software development

Usman

Mendes

Weidt

et al. 2014

Proceedings of the 10th International Conference on Predictive Models in Software Engineering

169

135

View full text Add to dashboard Cite

show abstract

“…This enabled them to illustrate the need for the organization to continually re-plan to cope not so much with external events but with the fact that the initial schedule was so unrealistic. Abrahamsson et al [1] report an empirical investigation of an agile development project in which effort prediction and management occurred with increments in delivery of the software system. They did so utilizing measures of OO design appropriate to the project at hand and coding effort per class.…”

Section: Within-project Effort Predictionmentioning

confidence: 99%

“…In the first we look at whether the sequence of project completion affects the accuracy of predictive models built from a single-organization industrial data set related to sixteen projects 1 The data used in the analysis that follows were provided to us by a large multi-national manufacturing company that had a strong and enduring interest in software process improvement. Their data collection activities were quite extensive, at least in relation to development effort .…”

Section: Empirical Analysismentioning

confidence: 99%