Research on Cross-Company Defect Prediction Method to Improve Software Security

Table 9

Performance verification results of mainstream methods.

Source	Target	KNN model				NB model				LR model
		FMT	HDP	RM	MMWS	FMT	HDP	RM	MMWS	FMT	HDP	RM	MMWS
CM1	Ant-1.7	0.713	0.654	0.664	0.555	0.756	0.646	0.688	0.663	0.703	0.826	0.660	0.690
MW1	Ant-1.7	0.728	0.722	0.756	0.701	0.812	0.816	0.685	0.630	0.710	0.768	0.641	0.740
PC1	Ant-1.7	0.743	0.675	0.717	0.618	0.778	0.582	0.598	0.612	0.772	0.651	0.494	0.708
PC3	Ant-1.7	0.745	0.708	0.704	0.676	0.751	0.732	0.604	0.702	0.715	0.743	0.392	0.743
PC4	Ant-1.7	0.616	0.560	0.670	0.659	0.701	0.576	0.553	0.584	0.634	0.579	0.506	0.715
CM1	Camel-1.6	0.606	0.588	0.547	0.589	0.611	0.585	0.588	0.538	0.636	0.568	0.573	0.558
MW1	Camel-1.6	0.584	0.546	0.594	0.582	0.592	0.597	0.596	0.600	0.624	0.610	0.555	0.629
PC1	Camel-1.6	0.529	0.542	0.576	0.567	0.596	0.489	0.542	0.583	0.572	0.535	0.498	0.617
PC3	Camel-1.6	0.580	0.571	0.584	0.586	0.606	0.587	0.547	0.573	0.615	0.594	0.455	0.622
PC4	Camel-1.6	0.552	0.467	0.569	0.567	0.519	0.422	0.534	0.571	0.498	0.414	0.517	0.544
CM1	Ivy-2.0	0.691	0.649	0.665	0.641	0.792	0.706	0.694	0.643	0.578	0.738	0.661	0.708
MW1	Ivy-2.0	0.749	0.607	0.764	0.706	0.807	0.700	0.695	0.688	0.496	0.717	0.619	0.772
PC1	Ivy-2.0	0.690	0.556	0.719	0.641	0.682	0.518	0.602	0.723	0.506	0.514	0.517	0.769
PC3	Ivy-2.0	0.684	0.658	0.715	0.682	0.603	0.669	0.649	0.740	0.765	0.732	0.405	0.723
PC4	Ivy-2.0	0.625	0.605	0.655	0.612	0.636	0.540	0.595	0.669	0.637	0.534	0.516	0.687
CM1	Jedit-4.3	0.594	0.538	0.628	0.717	0.667	0.639	0.561	0.545	0.569	0.578	0.552	0.711
MW1	Jedit-4.3	0.612	0.719	0.626	0.613	0.611	0.626	0.543	0.606	0.614	0.616	0.537	0.707
PC1	Jedit-4.3	0.594	0.547	0.601	0.602	0.563	0.537	0.567	0.661	0.592	0.460	0.524	0.743
PC3	Jedit-4.3	0.598	0.591	0.580	0.647	0.585	0.603	0.514	0.636	0.593	0.637	0.477	0.670
PC4	Jedit-4.3	0.520	0.545	0.540	0.579	0.514	0.551	0.521	0.555	0.522	0.555	0.511	0.703
CM1	Synapse-1.2	0.646	0.646	0.605	0.586	0.666	0.653	0.638	0.619	0.740	0.719	0.655	0.648
MW1	Synapse-1.2	0.655	0.655	0.693	0.603	0.715	0.729	0.651	0.633	0.634	0.728	0.583	0.667
PC1	Synapse-1.2	0.656	0.660	0.661	0.628	0.582	0.646	0.571	0.639	0.446	0.703	0.494	0.685
PC3	Synapse-1.2	0.666	0.680	0.649	0.658	0.580	0.691	0.600	0.575	0.573	0.700	0.410	0.632
PC4	Synapse-1.2	0.633	—	0.630	0.617	0.674	—	0.563	0.618	0.591	—	0.542	0.711
CM1	Velocity-1.6	0.647	0.605	0.600	0.657	0.714	0.621	0.624	0.569	0.703	0.627	0.611	0.663
MW1	Velocity-1.6	0.643	0.623	0.669	0.629	0.736	0.734	0.669	0.626	0.722	0.729	0.566	0.680
PC1	Velocity-1.6	0.577	0.650	0.642	0.614	0.748	0.576	0.579	0.570	0.767	0.643	0.495	0.679
PC3	Velocity-1.6	0.663	0.721	0.634	0.657	0.699	0.719	0.599	0.656	0.729	0.736	0.431	0.686
PC4	Velocity-1.6	0.562	0.546	0.584	0.628	0.615	0.615	0.551	0.545	0.585	0.604	0.515	0.670
CM1	Xalan-2.4	0.662	0.621	0.657	0.687	0.666	0.520	0.671	0.648	0.608	0.665	0.635	0.684
MW1	Xalan-2.4	0.683	0.639	0.726	0.644	0.741	0.723	0.677	0.634	0.623	0.721	0.607	0.726
PC1	Xalan-2.4	0.675	0.627	0.687	0.651	0.717	0.601	0.600	0.682	0.713	0.625	0.513	0.717
PC3	Xalan-2.4	0.670	0.671	0.679	0.590	0.667	0.667	0.605	0.591	0.637	0.679	0.392	0.716
PC4	Xalan-2.4	0.593	0.563	0.648	0.507	0.651	0.584	0.560	0.566	0.562	0.589	0.525	0.703
Std		0.084	0.093	0.076	0.051	0.060	0.063	0.057	0.046	0.080	0.081	0.053	0.052
Average		0.640	0.616	0.647	0.626	0.667	0.624	0.601	0.620	0.628	0.642	0.531	0.686