TY - GEN
T1 - Is this cost estimate reliable? - the relationship between homogeneity of analogues and estimation reliability
AU - Ohsugi, Naoki
AU - Monden, Akito
AU - Kikuchi, Nahomi
AU - Barker, Michael D.
AU - Tsunoda, Masateru
AU - Kakimoto, Takeshi
AU - Matsumoto, Ken Ichi
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Analogy-based cost estimation provides a useful and intuitive means to support decision making in software project management. It derives a cost estimate required for completing a project from information about similar past projects, namely the analogues. While on average this method provides a relatively accurate cost estimate there remains a possibility of large estimation errors. In this paper, we empirically tested the hypothesis that "using more homogeneous analogues produces a more reliable cost estimate" using a software engineering data repository established by the Software Engineering Center (SEC), Information-technology Promotion Agency, Japan. This testing showed that low and high homogeneity projects had a large variation in estimation reliability. For instance, the difference was 22.9% (p = 0.021) in terms of percentage to get accurate estimates (better than Median of Magnitude of Relative Error).
AB - Analogy-based cost estimation provides a useful and intuitive means to support decision making in software project management. It derives a cost estimate required for completing a project from information about similar past projects, namely the analogues. While on average this method provides a relatively accurate cost estimate there remains a possibility of large estimation errors. In this paper, we empirically tested the hypothesis that "using more homogeneous analogues produces a more reliable cost estimate" using a software engineering data repository established by the Software Engineering Center (SEC), Information-technology Promotion Agency, Japan. This testing showed that low and high homogeneity projects had a large variation in estimation reliability. For instance, the difference was 22.9% (p = 0.021) in terms of percentage to get accurate estimates (better than Median of Magnitude of Relative Error).
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U2 - 10.1109/ESEM.2007.61
DO - 10.1109/ESEM.2007.61
M3 - Conference contribution
AN - SCOPUS:44649126202
SN - 0769528864
SN - 9780769528861
T3 - Proceedings - 1st International Symposium on Empirical Software Engineering and Measurement, ESEM 2007
SP - 384
EP - 392
BT - Proceedings - 1st International Symposium on Empirical Software Engineering and Measurement, ESEM 2007
T2 - 1st International Symposium on Empirical Software Engineering and Measurement, ESEM 2007
Y2 - 20 September 2007 through 21 September 2007
ER -