},
		{
			scores:         []int64{0, 0, 0, 0},
			expectedScores: []int64{0, 0, 0, 0},
		},
		{
			reverse:        true,
			scores:         []int64{0, 0, 0, 0},
			expectedScores: []int64{100, 100, 100, 100},
		},
	}

	for i, test := range tests {
		t.Run(fmt.Sprintf("case_%d", i), func(t *testing.T) {
			scores := framework.NodeScoreList{}
			for _, score := range test.scores {

				hostResult, status := p.(framework.ScorePlugin).Score(ctx, state, test.pod, test.nodes[i].Name)
				if !status.IsSuccess() {
					t.Errorf("Score is expected to return success, but didn't. Got status: %v", status)
				}
				if !reflect.DeepEqual(test.expectedList[i].Score, hostResult) {
					t.Errorf("got score %v for host %v, expected %v", hostResult, test.nodes[i].Name, test.expectedList[i].Score)
				}
			}
		})
	}

		if scores[i].Score > maxCount {
			maxCount = scores[i].Score
		}
	}

	if maxCount == 0 {
		if reverse {
			for i := range scores {
				scores[i].Score = maxPriority
			}
		}
		return nil
	}

	for i := range scores {
		score := scores[i].Score

		score = maxPriority * score / maxCount
		if reverse {
			score = maxPriority - score
		}

		scores[i].Score = score
	}
	return nil

	var maxCount int64 = math.MinInt64
	for i := range scores {
		score := scores[i].Score
		if score > maxCount {
			maxCount = score
		}
		if score < minCount {
			minCount = score
		}
	}

	maxMinDiff := maxCount - minCount
	for i := range scores {
		fScore := float64(0)
		if maxMinDiff > 0 {
			fScore = float64(framework.MaxNodeScore) * (float64(scores[i].Score-minCount) / float64(maxMinDiff))
		}

			resources:      defaultResources,
		},
		{
			// Node1 scores on 0-MaxNodeScore scale
			// CPU Score: ((4000 - 3000) * MaxNodeScore) / 4000 = 25
			// Memory Score: ((10000 - 5000) * MaxNodeScore) / 10000 = 50
			// Node1 Score: (25 + 50) / 2 = 37
			// Node2 scores on 0-MaxNodeScore scale

	}{
		{
			// Node1 scores (used resources) on 0-MaxNodeScore scale
			// CPU Score: (0 * MaxNodeScore)  / 4000 = 0
			// Memory Score: (0 * MaxNodeScore) / 10000 = 0
			// Node1 Score: (0 + 0) / 2 = 0
			// Node2 scores (used resources) on 0-MaxNodeScore scale
			// CPU Score: (0 * MaxNodeScore) / 4000 = 0
			// Memory Score: (0 * MaxNodeScore) / 10000 = 0
			// Node2 Score: (0 + 0) / 2 = 0

	var minScore int64 = math.MaxInt64
	var maxScore int64
	for i, score := range scores {
		// it's mandatory to check if <score.Name> is present in m.IgnoredNodes
		if s.IgnoredNodes.Has(score.Name) {
			scores[i].Score = invalidScore
			continue
		}
		if score.Score < minScore {
			minScore = score.Score
		}
		if score.Score > maxScore {
			maxScore = score.Score
		}
	}

	for i := range scores {

			// resources["intel.com/bar"] = 5
			// Node1 scores (used resources) on 0-10 scale
			// used + requested / available
			// intel.com/foo Score: { (0 + 4) / 8 } * 10 = 0
			// intel.com/bar Score: { (0 + 2) / 4 } * 10 = 0
			// Node1 Score: (0.25 * 3) + (0.5 * 5) / 8 = 5
			// resources["intel.com/foo"] = 3
			// resources["intel.com/bar"] = 5
			// Node2 scores (used resources) on 0-10 scale
			// used + requested / available

	// Prioritize based on extender-implemented priority functions. The returned scores & weight
	// are used to compute the weighted score for an extender. The weighted scores are added to
	// the scores computed by Kubernetes scheduler. The total scores are used to do the host selection.
	Prioritize(pod *v1.Pod, nodes []*NodeInfo) (hostPriorities *extenderv1.HostPriorityList, weight int64, err error)

		return
	} else if err != nil {
		return
	}
	// Check that OOM scores were applied to the right processes.
	if len(appliedPids) != len(pidOOMs) {
		t.Errorf("Applied OOM scores to incorrect number of processes - %+v vs %v", appliedPids, pidOOMs)
		return
	}
	for _, pid := range appliedPids {
		if !pidOOMs[pid] {
			t.Errorf("Failed to apply OOM scores to process %d", pid)
		}
	}
}