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      Investigating the Use of Chronological Splitting to Compare Software Cross-company and Single-company Effort Predictions

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      12th International Conference on Evaluation and Assessment in Software Engineering (EASE) (EASE)

      Evaluation and Assessment in Software Engineering (EASE)

      26 - 27 June 2008

      chronological split, effort estimation, software projects, cross-company estimation models, single-company estimation models, regression-based estimation models

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          Abstract

          CONTEXT: Numerous studies have investigated the use of cross-company datasets to estimate effort for single-company projects; however to date only one has compared the effect of using a chronological split instead of a random split to assign projects to a training set and a validation set, finding no significant differences.

          OBJECTIVE: The aim of this study is to extend [15] using a project-by-project chronological split, and also to investigate how this type of split affects the results when comparing within- to cross-company effort estimation.

          METHOD: Chronological splitting was compared with two forms of cross-validation. Here a more realistic form of chronological splitting than the one used in [15] is investigated, in which a validation set contains a single project, and a regression model is built from scratch using as training set the set of projects completed before the validation project’s start date. We used 228 single-company projects and 678 cross-company projects from the ISBSG Release 10 repository.

          RESULTS: We obtained contradictory results when comparing cross- to single-company predictions for single-company projects. First, when results were compared using absolute residuals there were no differences between cross- and single-company predictions, or between techniques. However, when using z values, chronological splitting favoured cross-company models, and cross-validation (both types) favoured single-company models.

          CONCLUSIONS: Results were promising when using project-by-project splitting because: i) they favoured cross-company models; and ii) this type of splitting mimics an effort estimation scenario in a real environment. However, these results were obtained using z values only. Therefore we urge future studies comparing prediction models to document results obtained using both z values and absolute residuals, such that a full picture can be provided.

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          Most cited references 12

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          Cross versus Within-Company Cost Estimation Studies: A Systematic Review

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            Real-time contributions of auditory feedback to avian vocal motor control.

            Songbirds and humans both rely critically on hearing for learning and maintaining accurate vocalizations. Evidence strongly indicates that auditory feedback contributes in real time to human speech, but similar contributions of feedback to birdsong remain unclear. Here, we assessed real-time influences of auditory feedback on Bengalese finch song using a computerized system to detect targeted syllables as they were being sung and to disrupt feedback transiently at short and precisely controlled latencies. Altered feedback elicited changes within tens of milliseconds to both syllable sequencing and timing in ongoing song. These vocal disruptions were larger when feedback was altered at segments of song with variable sequence transitions than at stereotyped sequences. As in humans, these effects depended on the feedback delay relative to ongoing song, with the most disruptive delays approximating the average syllable duration. These results extend the parallels between speech and birdsong with respect to a moment-by-moment reliance on auditory feedback. Moreover, they demonstrate that song premotor circuitry is sensitive to auditory feedback during singing and suggest that feedback may contribute in real time to the control and calibration of song.
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              What accuracy statistics really measure

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                Author and article information

                Contributors
                Conference
                June 2008
                June 2008
                : 1-10
                Affiliations
                School of IT&EE, UNSW@ADFA, Canberra ACT 2600, Australia
                Computer Science Department, The University of Auckland, Private Bag 92019, Auckland, New Zealand
                Article
                10.14236/ewic/EASE2008.15
                © Chris Lokan et al. Published by BCS Learning and Development Ltd. 12th International Conference on Evaluation and Assessment in Software Engineering (EASE)

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                12th International Conference on Evaluation and Assessment in Software Engineering (EASE)
                EASE
                12
                University of Bari, Italy
                26 - 27 June 2008
                Electronic Workshops in Computing (eWiC)
                Evaluation and Assessment in Software Engineering (EASE)
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Electronic Workshops in Computing

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