4.3.2. Effective EvaluationTo furth

4.3.2. Effective EvaluationTo further verify the accuracy of the causal search algorithm, we referred to our previous researchwork. We injected more types of faults into the Sock Shop platform, which included CPU burnout,MEM overload, disk I/O block, and network jam. Meanwhile, those faults were injected into thevarious microservices in Sock Shop, and the number of the injected faults for each type and each serviceis 20. Finally, we evaluated the performance of our causality search algorithm with two evaluationmetrics in Microscope [18]:• Precision at the top K indicates the probability that the root cause in the top K of the ranking list ifthe cause inference is triggered.• Recall at the top K is the portion of the total amount of real causes that were actually retrieved atthe top K of the ranking list.In our experiment, we set K = 2. Finally, we could obtain the experimental results shownin Table 2.