Changeset 132 for trunk/CrossPare/src/de/ugoe/cs/cpdp/eval/AbstractWekaEvaluation.java

Timestamp:

06/28/16 12:01:39 (8 years ago)

Author:

sherbold

Message:

• rather intrusive and large change to correctly evaluate AUCEC in case metrics are modified. The effort is now stored directly with a software version and it is the duty of the loader to specify the review effort for each instance. This required changes to the execution strategiey, data loading, and evaluation process.

File:

• trunk/CrossPare/src/de/ugoe/cs/cpdp/eval/AbstractWekaEvaluation.java (modified) (3 diffs)

trunk/CrossPare/src/de/ugoe/cs/cpdp/eval/AbstractWekaEvaluation.java

@@ -92 +92 @@
                       Instances traindata,
                       List<ITrainer> trainers,
+                      List<Double> efforts, 
                       boolean writeHeader,
                       List<IResultStorage> storages)
@@ -150 +151 @@
                 eval.numFalsePositives(1) / (eval.numFalsePositives(1) + eval.numTrueNegatives(1));
             double gmeasure = 2 * eval.recall(1) * (1.0 - pf) / (eval.recall(1) + (1.0 - pf));
-            double aucec = calculateReviewEffort(testdata, classifier);
+            double aucec = calculateReviewEffort(testdata, classifier, efforts);
             double succHe = eval.recall(1) >= 0.7 && eval.precision(1) >= 0.5 ? 1.0 : 0.0;
             double succZi = eval.recall(1) >= 0.7 && eval.precision(1) >= 0.7 ? 1.0 : 0.0;
@@ -208 +209 @@
         output.flush();
     }
-
+    
+    private double calculateReviewEffort(Instances testdata, Classifier classifier, List<Double> efforts) {
+        if( efforts==null ) {
+            return 0;
+        }
+        
+        final List<Integer> bugPredicted = new ArrayList<>();
+        final List<Integer> nobugPredicted = new ArrayList<>();
+        double totalLoc = 0.0d;
+        int totalBugs = 0;
+        for (int i = 0; i < testdata.numInstances(); i++) {
+            try {
+                if (Double.compare(classifier.classifyInstance(testdata.instance(i)), 0.0d) == 0) {
+                    nobugPredicted.add(i);
+                }
+                else {
+                    bugPredicted.add(i);
+                }
+            }
+            catch (Exception e) {
+                throw new RuntimeException(
+                                           "unexpected error during the evaluation of the review effort",
+                                           e);
+            }
+            if (Double.compare(testdata.instance(i).classValue(), 1.0d) == 0) {
+                totalBugs++;
+            }
+            totalLoc += efforts.get(i);
+        }
+
+        final List<Double> reviewLoc = new ArrayList<>(testdata.numInstances());
+        final List<Double> bugsFound = new ArrayList<>(testdata.numInstances());
+
+        double currentBugsFound = 0;
+
+        while (!bugPredicted.isEmpty()) {
+            double minLoc = Double.MAX_VALUE;
+            int minIndex = -1;
+            for (int i = 0; i < bugPredicted.size(); i++) {
+                double currentLoc = efforts.get(bugPredicted.get(i));
+                if (currentLoc < minLoc) {
+                    minIndex = i;
+                    minLoc = currentLoc;
+                }
+            }
+            if (minIndex != -1) {
+                reviewLoc.add(minLoc / totalLoc);
+
+                currentBugsFound += testdata.instance(bugPredicted.get(minIndex)).classValue();
+                bugsFound.add(currentBugsFound);
+
+                bugPredicted.remove(minIndex);
+            }
+            else {
+                throw new RuntimeException("Shouldn't happen!");
+            }
+        }
+
+        while (!nobugPredicted.isEmpty()) {
+            double minLoc = Double.MAX_VALUE;
+            int minIndex = -1;
+            for (int i = 0; i < nobugPredicted.size(); i++) {
+                double currentLoc = efforts.get(nobugPredicted.get(i));
+                if (currentLoc < minLoc) {
+                    minIndex = i;
+                    minLoc = currentLoc;
+                }
+            }
+            if (minIndex != -1) {
+                reviewLoc.add(minLoc / totalLoc);
+
+                currentBugsFound += testdata.instance(nobugPredicted.get(minIndex)).classValue();
+                bugsFound.add(currentBugsFound);
+                nobugPredicted.remove(minIndex);
+            }
+            else {
+                throw new RuntimeException("Shouldn't happen!");
+            }
+        }
+
+        double auc = 0.0;
+        for (int i = 0; i < bugsFound.size(); i++) {
+            auc += reviewLoc.get(i) * bugsFound.get(i) / totalBugs;
+        }
+
+        return auc;
+    }
+
+    @SuppressWarnings("unused")
+    @Deprecated
     private double calculateReviewEffort(Instances testdata, Classifier classifier) {