软件质量工程project2.pptVIP

软件质量工程project2 陈晓玲 2010280167 陈明 2010220778 赵珅 2010220786 1 How many MRs the developers are working on in each week? 2-4 How much is each release cost (measured in developer time)? AVG(submtDate - crDate) 结论（排除没有完成的数据）： r0：共580个数据，平均值为1549914。即17天22小时。 r1：共3个数据，平均值为370033。即4天6小时。 r2：共44个数据，平均值为210432。即2天10小时。 r3：共534个数据，平均值为2126756。即24天14小时。 r4：共63个数据，平均值为1050009。即12天3小时。 r5：共1151个数据，平均值为2474887。即28天15小时。 r6：共3个数据，平均值为428918。即4天23小时。 r7：共33个数据，平均值为2073110。即23天23小时。 3 Predicting Defect MRs For each release, can you predict the number of Defect MRs at each week based on the following data? the number of New Feature MRs the Defect MRs in previous version the Defect MRs in previous weeks for the same release 3 Predicting Defect MRs For each release, can you predict the number of Defect MRs at each week based on the following data? the number of New Feature MRs the Defect MRs in previous version the Defect MRs in previous weeks for the same release 3 Predicting Defect MRs For each release, can you predict the number of Defect MRs at each week based on the following data? the number of New Feature MRs the Defect MRs in previous version the Defect MRs in previous weeks for the same release 3-1 the number of New Feature MRs General model Gauss4: f(x) = a1*exp(-((x-b1)/c1)^2) + a2*exp(-((x-b2)/c2)^2) + a3*exp(-((x-b3)/c3)^2) + a4*exp(-((x-b4)/c4)^2) Coefficients (with 95% confidence bounds): a1 = 0 b1 = 39.62 c1 = 0.7552 a2 = 399.3 (-4880, 5678) b2 = 55.97 (-253.2, 365.1) c2 = 29.51 (-90.48, 149.5) a3 = 362.7 (-1.28e+004, 1.353e+004) b3 = 32.03 (17.95, 46.11) c3 = 1.353 (-12.66, 15.37) a4 = 628.1 (-1.074e+004, 1.199e+004) b4 = 35.32 (-57.53, 128.2) c4 = 2.421 (-141.5, 146.4) Goodness of fit: SSE: 3.572e+005 R-square: 0.974