  This paper provides a systematic study of several proposed measures for
online algorithms in the context of a specific problem, namely, the two server
problem on three colinear points. Even though the problem is simple, it
encapsulates a core challenge in online algorithms which is to balance
greediness and adaptability. We examine Competitive Analysis, the Max/Max
Ratio, the Random Order Ratio, Bijective Analysis and Relative Worst Order
Analysis, and determine how these measures compare the Greedy Algorithm, Double
Coverage, and Lazy Double Coverage, commonly studied algorithms in the context
of server problems. We find that by the Max/Max Ratio and Bijective Analysis,
Greedy is the best of the three algorithms. Under the other measures, Double
Coverage and Lazy Double Coverage are better, though Relative Worst Order
Analysis indicates that Greedy is sometimes better. Only Bijective Analysis and
Relative Worst Order Analysis indicate that Lazy Double Coverage is better than
Double Coverage. Our results also provide the first proof of optimality of an
algorithm under Relative Worst Order Analysis.
