remove(key: string) {
   if (!StringWrapper.contains(key, '.')) {
     return this._data.delete(key);
   }
   var pieces = key.split('.');
   var last = ListWrapper.last(pieces);
   pieces.length = pieces.length - 1;
   var target = this._resolve(pieces, this);
   return target.remove(last);
 }

 set(key: string, value) {
   if (key.indexOf('.') == -1) {
     this._data[key] = value;
     return;
   }
   var pieces = key.split('.');
   var last = ListWrapper.last(pieces);
   pieces.length = pieces.length - 1;
   var target = this._resolve(pieces, this);
   target[last] = value;
 }

 get(key: string) {
   if (key.indexOf('.') == -1) {
     return this._data[key];
   }
   var pieces = key.split('.');
   var last = ListWrapper.last(pieces);
   pieces.length = pieces.length - 1;
   var target = this._resolve(pieces, this);
   if (target == null) {
     return null;
   }
   return target[last];
 }

 _computeStageButtons() {
   var disabled = true;
   this.stages = ListWrapper.clone(STATUS_LIST.map((status) => {
     var isCurrent = this._offering.status == status;
     var stage = new Stage();
     stage.name = status;
     stage.isDisabled = disabled;
     stage.backgroundColor = disabled ? '#DDD' : isCurrent ? '#DDF' : '#FDD';
     if (isCurrent) {
       disabled = false;
     }
     return stage;
   }));
 }

 validate(completeSample: MeasureValues[]): MeasureValues[] {
   if (completeSample.length >= this._sampleSize) {
     var latestSample = ListWrapper.slice(completeSample, completeSample.length - this._sampleSize,
                                          completeSample.length);
     var xValues = [];
     var yValues = [];
     for (var i = 0; i < latestSample.length; i++) {
       // For now, we only use the array index as x value.
       // TODO(tbosch): think about whether we should use time here instead
       xValues.push(i);
       yValues.push(latestSample[i].values[this._metric]);
     }
     var regressionSlope = Statistic.calculateRegressionSlope(
         xValues, Statistic.calculateMean(xValues), yValues, Statistic.calculateMean(yValues));
     return regressionSlope >= 0 ? latestSample : null;
   } else {
     return null;
   }
 }

 (value, cat) => { return value && ListWrapper.contains(eventCategories, cat); }, true);