# An Improved CNN Model for Within-Project Software Defect Prediction
## 5 Results and Discussion
### Performance of the Improved CNN Model
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Project.** & **Version** & **DT** & **RF** & **LR** & **NB** & **NET** & **FIX** & **RANDOM** & **Improved CNN** \\ \hline \multirow{4}{*}{Ant} & 1.3 & 0.36 & 0.31 & 0.36 & 0.43 & 0.14 & 0.28 & 0.24 & **0.67** \\ \cline{2-10}  & 1.4 & 0.40 & 0.24 & 0.22 & **0.44** & 0.04 & 0.37 & 0.32 & 0.38 \\ \cline{2-10}  & 1.5 & **0.42** & 0.37 & 0.41 & 0.35 & 0.15 & 0.20 & 0.18 & 0.25 \\ \cline{2-10}  & 1.6 & 0.55 & **0.59** & 0.57 & 0.58 & **0.59** & 0.42 & 0.33 & 0.41 \\ \cline{2-10}  & 1.7 & 0.53 & 0.52 & 0.50 & **0.56** & 0.45 & 0.36 & 0.31 & 0.39 \\ \hline \multirow{4}{*}{Camel} & 1.0 & 0.00 & 0.00 & 0.00 & 0.30 & 0.00 & 0.07 & 0.08 & **0.40** \\ \cline{2-10}  & 1.2 & 0.46 & 0.40 & 0.35 & 0.32 & 0.26 & 0.52 & 0.41 & **0.69** \\ \cline{2-10}  & 1.4 & 0.30 & 0.27 & 0.18 & 0.26 & 0.05 & 0.29 & 0.25 & **0.46** \\ \cline{2-10}  & 1.6 & 0.27 & 0.25 & 0.18 & 0.30 & 0.16 & 0.33 & 0.28 & **0.52** \\ \hline \multirow{4}{*}{Ivy} & 1.1 & 0.73 & 0.71 & 0.71 & 0.54 & 0.73 & 0.72 & 0.55 & **0.80** \\ \cline{2-10}  & 1.4 & 0.00 & 0.00 & 0.15 & 0.17 & 0.11 & 0.12 & 0.11 & **0.22** \\ \cline{2-10}  & 2.0 & 0.17 & 0.31 & 0.31 & **0.40** & 0.16 & 0.20 & 0.18 & 0.31 \\ \hline \multirow{4}{*}{JEdit} & 3.2 & **0.56** & 0.63 & 0.68 & 0.55 & 0.59 & 0.50 & 0.40 & **0.69** \\ \cline{2-10}  & 4.0 & 0.49 & **0.56** & 0.49 & 0.41 & 0.43 & 0.39 & 0.31 & 0.48 \\ \cline{2-10}  & 4.1 & 0.45 & 0.54 & **0.61** & 0.52 & 0.54 & 0.40 & 0.33 & 0.41 \\ \cline{2-10}  & 4.2 & 0.46 & 0.29 & 0.37 & 0.44 & 0.38 & 0.23 & 0.20 & **0.58** \\ \cline{2-10}  & 4.3 & 0.00 & 0.00 & 0.00 & **0.21** & 0.00 & 0.04 & 0.04 & 0.00 \\ \hline \multirow{4}{*}{Log4j} & 1.0 & 0.55 & 0.53 & 0.55 & 0.61 & 0.59 & 0.40 & 0.36 & **0.77** \\ \cline{2-10}  & 1.1 & 0.66 & 0.73 & 0.63 & 0.72 & **0.76** & 0.51 & 0.43 & 0.40 \\ \cline{2-10}  & 1.2 & 0.95 & 0.96 & 0.94 & 0.67 & 0.96 & 0.96 & 0.63 & **0.97** \\ \hline \multirow{4}{*}{Lucene} & 2.0 & 0.58 & 0.59 & 0.65 & 0.54 & 0.66 & 0.64 & 0.48 & **0.74** \\ \cline{2-10}  & 2.2 & 0.62 & 0.67 & 0.70 & 0.48 & 0.66 & **0.74** & 0.53 & 0.63 \\ \cline{2-10}  & 2.4 & 0.72 & 0.73 & 0.74 & 0.54 & 0.71 & 0.75 & 0.54 & **0.77** \\ \hline \multirow{4}{*}{Pbeans} & 1.0 & 0.87 & **0.90** & 0.79 & 0.81 & 0.81 & 0.87 & 0.66 & 0.89 \\ \cline{2-10}  & 2.0 & 0.22 & 0.35 & 0.48 & 0.25 & 0.14 & 0.33 & 0.30 & **0.67** \\ \hline \multirow{4}{*}{Poi} & 1.5 & **0.79** & 0.75 & 0.73 & 0.46 & 0.77 & 0.75 & 0.55 & 0.61 \\ \cline{2-10}  & 2.0 & 0.26 & 0.25 & 0.23 & **0.27** & 0.14 & 0.21 & 0.20 & 0.13 \\ \cline{2-10}  & 2.5 & 0.82 & 0.85 & 0.82 & 0.56 & 0.82 & 0.78 & 0.58 & **0.90** \\ \cline{2-10}  & 3.0 & 0.83 & **0.84** & 0.81 & 0.49 & 0.82 & 0.78 & 0.56 & 0.76 \\ \hline \multirow{4}{*}{Synapse} & 1.0 & 0.08 & 0.09 & 0.32 & **0.41** & 0.19 & 0.18 & 0.16 & 0.29 \\ \cline{2-10}  & 1.1 & 0.53 & 0.51 & 0.58 & 0.56 & 0.52 & 0.43 & 0.35 & **0.67** \\ \cline{2-10}  & 1.2 & 0.60 & 0.59 & 0.55 & 0.59 & 0.56 & 0.50 & 0.39 & **0.69** \\ \hline \multirow{4}{*}{Velocity} & 1.4 & 0.90 & 0.89 & 0.89 & 0.89 & **0.91** & 0.86 & 0.60 & 0.90 \\ \cline{2-10}  & 1.5 & 0.80 & **0.83** & 0.80 & 0.45 & 0.78 & 0.80 & 0.57 & 0.78 \\ \cline{2-10}  & 1.6 & 0.54 & 0.50 & 0.51 & 0.38 & 0.47 & 0.51 & 0.41 & **0.83** \\ \hline \multirow{4}{*}{Xalan} & 2.4 & 0.26 & 0.28 & 0.28 & **0.37** & 0.16 & 0.26 & 0.23 & 0.25 \\ \cline{2-10}  & 2.5 & 0.67 & 0.65 & 0.58 & 0.38 & 0.48 & 0.65 & 0.49 & **0.70** \\ \cline{2-10}  & 2.6 & 0.72 & 0.73 & 0.69 & 0.61 & 0.62 & 0.63 & 0.47 & **0.76** \\ \hline \multirow{4}{*}{Xerces} & Initial & 0.71 & 0.68 & **0.73** & 0.34 & 0.63 & 0.64 & 0.48 & 0.65 \\ \cline{2-10}  & 1.2 & 0.38 & 0.33 & 0.07 & 0.23 & 0.03 & 0.28 & 0.24 & **0.41** \\ \cline{2-10}  & 1.3 & 0.50 & 0.44 & 0.42 & 0.38 & 0.35 & 0.26 & 0.22 & **0.56** \\ \hline \multicolumn{2}{c}{average} & 0.51 & 0.50 & 0.50 & 0.46 & 0.45 & 0.47 & 0.36 & **0.57** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Performance comparison of different models on the PSC dataset. The decimal values represent the average F-measure values.