/**
* <copyright>
* Copyright 1997-2002 BBNT Solutions, LLC
* under sponsorship of the Defense Advanced Research Projects Agency (DARPA).
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the Cougaar Open Source License as published by
* DARPA on the Cougaar Open Source Website (www.cougaar.org).
*
* THE COUGAAR SOFTWARE AND ANY DERIVATIVE SUPPLIED BY LICENSOR IS
* PROVIDED 'AS IS' WITHOUT WARRANTIES OF ANY KIND, WHETHER EXPRESS OR
* IMPLIED, INCLUDING (BUT NOT LIMITED TO) ALL IMPLIED WARRANTIES OF
* MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, AND WITHOUT
* ANY WARRANTIES AS TO NON-INFRINGEMENT. IN NO EVENT SHALL COPYRIGHT
* HOLDER BE LIABLE FOR ANY DIRECT, SPECIAL, INDIRECT OR CONSEQUENTIAL
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE OF DATA OR PROFITS,
* TORTIOUS CONDUCT, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
* PERFORMANCE OF THE COUGAAR SOFTWARE.
* </copyright>
*
* Created on Aug 26, 2002
*/
package test.net.sourceforge.pmd.stat;
import junit.framework.AssertionFailedError;
import junit.framework.TestCase;
import net.sourceforge.pmd.Report;
import net.sourceforge.pmd.Rule;
import net.sourceforge.pmd.RuleContext;
import net.sourceforge.pmd.stat.DataPoint;
import net.sourceforge.pmd.stat.Metric;
import net.sourceforge.pmd.stat.StatisticalRule;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Iterator;
import java.util.List;
import java.util.Random;
/**
* This class tests the Statistical Rules in PMD.
*
* The idea is, that we fill up 999 datapoints into
* the Stat Rule, and then throw random parameters
* at it.
*
* The three parameters which are checked are:
* sigma - # Sigmas over the mean.
* topscore - Only the top 5 or so items.
* minimum - Only things of score 10 or better
*
* When more than one parameter is lumped together, then
* we expect the one which would return the fewest to
* determine what gets sent back.
*
* So, we throw each collection of parameters, where each
* one is a different order into the system. We check the
* results off of what the smallest value should be.
*
* If you are going to work with StatisticalRule any, please
* bump the "NUM_TESTS" number up to something like 128. That
* way you are more likely to identify problems. It is set low
* now to make building and running tests easier (when we aren't
* touching the file.)
*
* Note also, that when verifying the Sigma, I wasn't quite able
* to determine how many results it would return (it would vary
* from -2 to 2 of what I expected.) That is what the delta
* parameter on the verify method takes. If you can figure it
* out exactly, (without stealing code from the StatRule) then
* feel free to change it and tighten the deltas.
*/
public class StatisticalRuleTest extends TestCase {
private static final int POINTS = 100;
private DataPoint points[] = new DataPoint[POINTS];
private MockStatisticalRule IUT = null;
private String testName = null;
private Random random = new Random();
public static final double MAX_MINIMUM = POINTS;
public static final double NO_MINIMUM = -1.0;
public static final double MAX_SIGMA = 5.0;
public static final double NO_SIGMA = -1.0;
public static final int MIN_TOPSCORE = 0;
public static final int NO_TOPSCORE = -1;
public static final double MEAN = 49.5;
public static final double SIGMA = 29.0115;
public static final int NUM_TESTS = 1;
public static final double DELTA = 0.005;
public StatisticalRuleTest(String name) {
super(name);
this.testName = name;
}
public void setUp() {
IUT = new MockStatisticalRule();
if (testName.endsWith("0")) {
for (int i = 0; i < POINTS; i++) {
points[i] = new DataPoint();
points[i].setScore(1.0 * i);
points[i].setLineNumber(i);
points[i].setMessage("DataPoint[" + Integer.toString(i) + "]");
IUT.addDataPoint(points[i]);
}
} else if (testName.endsWith("1")) {
for (int i = POINTS-1; i >= 0; i--) {
points[i] = new DataPoint();
points[i].setScore(1.0 * i);
points[i].setLineNumber(i);
points[i].setMessage("DataPoint[" + Integer.toString(i) + "]");
IUT.addDataPoint(points[i]);
}
} else {
List lPoints = new ArrayList();
for (int i = 0; i < POINTS; i++) {
DataPoint point = new DataPoint();
point.setScore(1.0 * i);
point.setLineNumber(i);
point.setMessage("DataPoint[" + Integer.toString(i) + "]");
lPoints.add(point);
}
Collections.shuffle(lPoints);
for (int i = 0; i < POINTS; i++) {
IUT.addDataPoint((DataPoint) lPoints.get(i));
}
}
}
/**
* 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(POINTS -1.0, 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.
*/
public double randomSigma() {
return random.nextDouble() * 1.0;
}
/**
* This returns a Random value for Sigma which value
* is greater than the parameter.
*/
public double randomSigma(int minimum) {
double minSigma = ((POINTS -1 - minimum) - MEAN) / SIGMA;
if ((minSigma <= 0) || (minSigma > 2))
return randomSigma();
return minSigma + (random.nextDouble() * (2 - minSigma));
}
/**
* This returns the expected number of results when
* the Sigma rating is the smallest.
*/
public int expectedSigma(double sigma) {
long expectedMin = Math.round(MEAN + (sigma * SIGMA));
if (((POINTS -1) - expectedMin) < 0)
return 0;
return (POINTS -1) - (int) expectedMin;
}
/**
* This generates a random minimum value for testing.
*/
public double randomMinimum() {
return random.nextDouble() * (POINTS -1);
}
/**
* This generates a random minimum value for which fewer
* results would be returned.
*/
public double randomMinimum(int minimum) {
double diffTarget = 1.0 * (POINTS -1 - minimum);
return (random.nextDouble() * minimum) + diffTarget;
}
/**
* This returns the expected number of reports.
*
* If the Minimum comes in at 521.569 then we expect
* 522, 523, ... 999 will pass.
*/
public int expectedMinimum(double minimum) {
Double d = new Double(minimum);
return POINTS -1 - d.intValue();
}
public void testExpectedMinimum() {
for (int i = 0; i < POINTS -1; i++) {
assertEquals("Integer Min", POINTS -1 - i, expectedMinimum(i * 1.0));
assertEquals("Double Min", POINTS -1 - i, expectedMinimum((i * 1.0) + 0.5));
}
}
/**
* This returns a random value for Top Score.
*/
public int randomTopScore() {
return random.nextInt(POINTS -1);
}
/**
* This will return a random value for the Top Score
* which will return more than the minimum provided.
*/
public int randomTopScore(double target) {
if (target < 0)
return 0;
return random.nextInt((new Double(target)).intValue());
}
/**
* This will return the expected number of results
* with the given Top Score.
*/
public int expectedTopScore(int target) {
return target;
}
// Test Single Datapoint
public void testSingleDatapoint() {
StatisticalRule IUT = new MockStatisticalRule();
DataPoint point = new DataPoint();
point.setScore(POINTS + 1.0);
point.setLineNumber(POINTS + 1);
point.setMessage("SingleDataPoint");
IUT.addProperty("minimum", Integer.toString(POINTS));
IUT.addDataPoint(point);
Report report = makeReport(IUT);
assertEquals("Expecting only one result.", 1, report.size());
}
// Okay, we have three properties we need to
// test in Combination:
// S = Sigma
// T = Top Score
// M = Minimum
//
// They are listed in decreasing order of what
// to expect.
//
// Thus testSM() should have the Sigma less than
// the minimum, so we expect the Minimum # of results.
//
public void testS() throws Throwable {
verifyResults(MAX_SIGMA, NO_MINIMUM, NO_TOPSCORE, 0, 2);
for (int i = 0; i < NUM_TESTS; i++) {
double sigma = randomSigma();
verifyResults(sigma, -1.0, -1, expectedSigma(sigma), 2);
}
}
public void testS1() throws Throwable {
testS();
}
public void testS2() throws Throwable {
testS();
}
public void testS3() throws Throwable {
testS();
}
public void testS4() throws Throwable {
testS();
}
public void testS5() throws Throwable {
testS();
}
public void testT() throws Throwable {
verifyResults(NO_SIGMA, NO_MINIMUM, MIN_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
int topScore = randomTopScore();
verifyResults(-1.0, -1.0, topScore, expectedTopScore(topScore), 0);
}
}
public void testT1() throws Throwable {
testT();
}
public void testT2() throws Throwable {
testT();
}
public void testT3() throws Throwable {
testT();
}
public void testT4() throws Throwable {
testT();
}
public void testT5() throws Throwable {
testT();
}
public void testM() throws Throwable {
verifyResults(NO_SIGMA, MAX_MINIMUM, NO_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
double minimum = randomMinimum();
verifyResults(-1.0, minimum, -1, expectedMinimum(minimum), 0);
}
}
public void testM1() throws Throwable {
testM();
}
public void testM2() throws Throwable {
testM();
}
public void testM3() throws Throwable {
testM();
}
public void testM4() throws Throwable {
testM();
}
public void testM5() throws Throwable {
testM();
}
public void testST() throws Throwable {
verifyResults(randomSigma(), NO_MINIMUM, MIN_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
double sigma = randomSigma();
int topScore = randomTopScore(expectedSigma(sigma));
verifyResults(sigma, NO_MINIMUM, topScore, expectedTopScore(topScore), 0);
}
}
public void testST1() throws Throwable {
testST();
}
public void testST2() throws Throwable {
testST();
}
public void testST3() throws Throwable {
testST();
}
public void testST4() throws Throwable {
testST();
}
public void testST5() throws Throwable {
testST();
}
public void testTS() throws Throwable {
verifyResults(MAX_SIGMA, NO_MINIMUM, randomTopScore(), 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
int topScore = randomTopScore();
double sigma = randomSigma(expectedTopScore(topScore));
verifyResults(sigma, -1.0, topScore, expectedSigma(sigma), 2);
}
}
public void testTS1() throws Throwable {
testTS();
}
public void testTS2() throws Throwable {
testTS();
}
public void testTS3() throws Throwable {
testTS();
}
public void testTS4() throws Throwable {
testTS();
}
public void testTS5() throws Throwable {
testTS();
}
public void testSM() throws Throwable {
verifyResults(randomSigma(), MAX_MINIMUM, NO_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
double sigma = randomSigma();
double minimum = randomMinimum(expectedSigma(sigma));
verifyResults(sigma, minimum, -1, expectedMinimum(minimum), 0);
}
}
public void testSM1() throws Throwable {
testSM();
}
public void testSM2() throws Throwable {
testSM();
}
public void testSM3() throws Throwable {
testSM();
}
public void testSM4() throws Throwable {
testSM();
}
public void testSM5() throws Throwable {
testSM();
}
public void testMS() throws Throwable {
verifyResults(MAX_SIGMA, randomMinimum(), NO_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
double minimum = randomMinimum();
double sigma = randomSigma(expectedMinimum(minimum));
verifyResults(sigma, minimum, -1, expectedSigma(sigma), 2);
}
}
public void testMS1() throws Throwable {
testMS();
}
public void testMS2() throws Throwable {
testMS();
}
public void testMS3() throws Throwable {
testMS();
}
public void testMS4() throws Throwable {
testMS();
}
public void testMS5() throws Throwable {
testMS();
}
public void testTM() throws Throwable {
verifyResults(NO_SIGMA, MAX_MINIMUM, randomTopScore(), 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
int topScore = randomTopScore();
double minimum = randomMinimum(expectedTopScore(topScore));
verifyResults(NO_SIGMA, minimum, topScore, expectedMinimum(minimum), 0);
}
}
public void testTM1() throws Throwable {
testTM();
}
public void testTM2() throws Throwable {
testTM();
}
public void testTM3() throws Throwable {
testTM();
}
public void testTM4() throws Throwable {
testTM();
}
public void testTM5() throws Throwable {
testTM();
}
public void testMT() throws Throwable {
verifyResults(NO_SIGMA, randomMinimum(), MIN_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
double minimum = randomMinimum();
int topScore = randomTopScore(expectedMinimum(minimum));
verifyResults(NO_SIGMA, minimum, topScore, expectedTopScore(topScore), 0);
}
}
public void testMT1() throws Throwable {
testMT();
}
public void testMT2() throws Throwable {
testMT();
}
public void testMT3() throws Throwable {
testMT();
}
public void testMT4() throws Throwable {
testMT();
}
public void testMT5() throws Throwable {
testMT();
}
public void testSTM() throws Throwable {
double sigma = randomSigma();
verifyResults(sigma, MAX_MINIMUM, randomTopScore(expectedSigma(sigma)), 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
sigma = randomSigma();
int topScore = randomTopScore(expectedSigma(sigma));
double minimum = randomMinimum(expectedTopScore(topScore));
verifyResults(sigma, minimum, topScore, expectedMinimum(minimum), 0);
}
}
public void testSTM1() throws Throwable {
testSTM();
}
public void testSTM2() throws Throwable {
testSTM();
}
public void testSTM3() throws Throwable {
testSTM();
}
public void testSTM4() throws Throwable {
testSTM();
}
public void testSTM5() throws Throwable {
testSTM();
}
public void testSMT() throws Throwable {
double sigma = randomSigma();
verifyResults(sigma, randomMinimum(expectedSigma(sigma)), MIN_TOPSCORE, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
sigma = randomSigma();
double minimum = randomMinimum(expectedSigma(sigma));
int topScore = randomTopScore(expectedMinimum(minimum));
verifyResults(sigma, minimum, topScore, expectedTopScore(topScore), 0);
}
}
public void testSMT1() throws Throwable {
testSMT();
}
public void testSMT2() throws Throwable {
testSMT();
}
public void testSMT3() throws Throwable {
testSMT();
}
public void testSMT4() throws Throwable {
testSMT();
}
public void testSMT5() throws Throwable {
testSMT();
}
public void testTSM() throws Throwable {
int topScore = randomTopScore();
verifyResults(randomSigma(expectedTopScore(topScore)), MAX_MINIMUM, topScore, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
topScore = randomTopScore();
double sigma = randomSigma(expectedTopScore(topScore));
double minimum = randomMinimum(expectedSigma(sigma));
verifyResults(sigma, minimum, topScore, expectedMinimum(minimum), 0);
}
}
public void testTSM1() throws Throwable {
testTSM();
}
public void testTSM2() throws Throwable {
testTSM();
}
public void testTSM3() throws Throwable {
testTSM();
}
public void testTSM4() throws Throwable {
testTSM();
}
public void testTSM5() throws Throwable {
testTSM();
}
public void testTMS() throws Throwable {
int topScore = randomTopScore();
verifyResults(MAX_SIGMA, randomMinimum(expectedTopScore(topScore)), topScore, 0, 0);
for (int i = 0; i < NUM_TESTS; i++) {
topScore = randomTopScore();
double minimum = randomMinimum(expectedTopScore(topScore));
double sigma = randomSigma(expectedMinimum(minimum));
verifyResults(sigma, minimum, topScore, expectedSigma(sigma), 2);
}
}
public void testTMS1() throws Throwable {
testTMS();
}
public void testTMS2() throws Throwable {
testTMS();
}
public void testTMS3() throws Throwable {
testTMS();
}
public void testTMS4() throws Throwable {
testTMS();
}
public void testTMS5() throws Throwable {
testTMS();
}
/**
* Verifies what happens when you pass these parameters
* into the thing. DELTA is the amount of error allowed.
* Usually DELTA is only used for Sigma, as we really can't
* calculate it exactly.
*/
public void verifyResults(double sigma, double minimum, int topScore, int expected, int delta) {
try {
setUp();
if (sigma >= 0) {
IUT.addProperty("sigma", Double.toString(sigma));
}
if (minimum >= 0) {
IUT.addProperty("minimum", Double.toString(minimum));
}
if (topScore >= 0) {
IUT.addProperty("topscore", Integer.toString(topScore));
}
Report report = makeReport(IUT);
if (delta == 0) {
assertEquals("Unexpected number of results: sigma= " + Double.toString(sigma) + " min= " + Double.toString(minimum) + " topscore= " + Integer.toString(topScore), expected, report.size());
} else {
String assertStr = "Unexpected number of results: sigma= " + Double.toString(sigma) + " min= " + Double.toString(minimum) + " topscore= " + Integer.toString(topScore) + " expected= " + Integer.toString(expected) + " +/- " + Integer.toString(delta) + " actual-result= " + report.size();
assertTrue(assertStr, report.size() >= (expected - delta));
assertTrue(assertStr, report.size() <= (expected + delta));
}
} catch (AssertionFailedError afe) {
System.err.println("******** " + testName + " ***********");
if (sigma != NO_SIGMA) {
System.err.println("SIGMA: " + Double.toString(sigma) + " EXPECT: " + Integer.toString(expectedSigma(sigma)));
}
if (minimum != NO_MINIMUM) {
System.err.println("MIN: " + Double.toString(minimum) + " EXPECT: " + Integer.toString(expectedMinimum(minimum)));
}
if (topScore != NO_TOPSCORE) {
System.err.println("TOP: " + Integer.toString(topScore) + " EXPECT: " + Integer.toString(expectedTopScore(topScore)));
}
throw afe;
}
}
public Report makeReport(Rule IUT) {
List list = new ArrayList();
Report report = new Report();
RuleContext ctx = new RuleContext();
ctx.setReport(report);
ctx.setSourceCodeFilename(testName);
IUT.apply(list, ctx);
return report;
}
}