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NEW QUESTION: 1
To determine if a software program properly handles a wide range of invalid input, a form of automated testing can be used to randomly generate invalid input in an attempt to crash the program.
What term is commonly used when referring to this type of testing?
A. Randomizing
B. Mutating
C. Fuzzing
D. Bounding
Answer: C
Explanation:
Fuzz testing or fuzzing is a software testing technique, often automated or semi-automated, that involves providing invalid, unexpected, or random data to the inputs of a computer program. The program is then monitored for exceptions such as crashes, or failing built-in code assertions or for finding potential memory leaks. Fuzzing is commonly used to test for security problems in software or computer systems. It is a form of random testing which has been used for testing hardware or software.
References: https://en.wikipedia.org/wiki/Fuzz_testing

NEW QUESTION: 2
Which two statements are true about initialization parameters for Clustered ASM instances?
A. The ASM_DISKGROUP parameter is optional.
B. ASM_POWER_LIMIT controls the number of RDBMS instances that can access a disk group while it is being rebalanced.
C. The maximum value of ASM_POWER_LIMIT is 1024.
D. A change to ASM_DISKSTRING requires a restart of all ASM instances for the change to take effect.
E. The default value of INSTANT_TYPE is ASM.
Answer: A,C
Explanation:
C: The default value of the ASM_DISKGROUPS parameter is a NULL string. If the parameter value is NULL or is not specified, then ASM does not mount any disk groups.
E: The ASM_POWER_LIMIT initialization parameter specifies the default power for disk rebalancing in a disk group. The range of values is 0 to 1024.
References:

NEW QUESTION: 3
Azure Kubernetes Service（AKS）クラスターを使用するいくつかのAIアプリケーションがあります。クラスターは最大32ノードをサポートします。
時折、予想外に、アプリケーションには32を超えるノードが必要であることがわかります。
予測できないアプリケーション負荷を処理するソリューションを推奨する必要があります。
どのスケーリング方法をお勧めしますか？
A. クラスターオートスケーラー
B. 水平ポッドオートスケーラー
C. 手動スケーリング
D. Azure Container Instances
Answer: A
Explanation:
Explanation
To keep up with application demands in Azure Kubernetes Service (AKS), you may need to adjust the number of nodes that run your workloads. The cluster autoscaler component can watch for pods in your cluster that can't be scheduled because of resource constraints. When issues are detected, the number of nodes is increased to meet the application demand. Nodes are also regularly checked for a lack of running pods, with the number of nodes then decreased as needed. This ability to automatically scale up or down the number of nodes in your AKS cluster lets you run an efficient, cost-effective cluster.
References:
https://docs.microsoft.com/en-us/azure/aks/cluster-autoscaler