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Added test to check for Metrics on the Report.

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git-svn-id: https://pmd.svn.sourceforge.net/svnroot/pmd/trunk@816 51baf565-9d33-0410-a72c-fc3788e3496d
This commit is contained in:
David Dixon-Peugh
2002-08-28 21:20:41 +00:00
parent f67d557d13
commit 0edbe9594c
2 changed files with 34 additions and 11 deletions
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27
pmd/regress/test/net/sourceforge/pmd/stat/StatisticalRuleTest.java
View File

@ -1,5 +1,6 @@
package test.net.sourceforge.pmd.stat;
import java.util.Iterator;
import java.util.List;
import java.util.ArrayList;
import java.util.Random;
@ -60,7 +61,7 @@ public class StatisticalRuleTest
public static final double MEAN = 499.5;
public static final double SIGMA = 288.8194;
public static final double SIGMA = 288.6750;
public static final int NUM_TESTS = 32;
public StatisticalRuleTest(String name)
@ -81,6 +82,30 @@ public class StatisticalRuleTest
}
}
/**
* This test verifies that the Stat rule creates a Metric,
* with the proper values.
*/
public void testMetrics() throws Throwable
{
Report report = makeReport( IUT );
Iterator metrics = report.metrics();
assertTrue( metrics.hasNext());
Object o = metrics.next();
assertTrue( o instanceof Metric);
Metric m = (Metric) o;
assertEquals("test.net.sourceforge.pmd.stat.MockStatisticalRule",
m.getMetricName());
assertEquals( 0.0, m.getLowValue(), 0.05 );
assertEquals( 999.0, m.getHighValue(), 0.05 );
assertEquals( MEAN, m.getAverage(), 0.05 );
assertEquals( SIGMA, m.getStandardDeviation(), 0.05 );
}
/**
* This returns a Random value for Sigma which will
* return some values.

18
pmd/src/net/sourceforge/pmd/stat/StatisticalRule.java
View File

@ -24,11 +24,14 @@ public abstract class StatisticalRule extends AbstractRule {
private int count = 0;
private double total = 0.0;
private double totalSquared = 0.0;
public void addDataPoint( DataPoint point )
{
count++;
total += point.getScore();
totalSquared += point.getScore() * point.getScore();
dataPoints.add( point );
}
@ -61,8 +64,8 @@ public abstract class StatisticalRule extends AbstractRule {
makeViolations(ctx, newPoints);
double low = ((DataPoint) newPoints.first()).getScore();
double high = ((DataPoint) newPoints.last()).getScore();
double low = ((DataPoint) dataPoints.first()).getScore();
double high = ((DataPoint) dataPoints.last()).getScore();
ctx.getReport().addMetric( new Metric( this.getName(), low, high,
getMean(), getStdDev()));
@ -77,13 +80,8 @@ public abstract class StatisticalRule extends AbstractRule {
Iterator points = dataPoints.iterator();
while (points.hasNext()) {
DataPoint point = (DataPoint) points.next();
varTotal += ((point.getScore() - getMean()) *
(point.getScore() - getMean()));
}
double variance = varTotal / count;
double variance = ((totalSquared / count) -
(getMean() * getMean() ));
return Math.sqrt( variance );
}