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NEW QUESTION: 1
Which of the following is an appropriate reason for maintenance testing?
A. Bugs found during unit testing
B. Bugs found in the field after upgrading the operation system
C. Bugs found during system testing
D. Bugs found during integration testing
Answer: B

NEW QUESTION: 2

A. Option F
B. Option B
C. Option A
D. Option D
E. Option E
F. Option H
G. Option G
H. Option C
Answer: C,D,E,G,H
Explanation:
The Java 2 platform includes a new package of concurrency utilities. These are classes that are designed to be used as building blocks in building concurrent classes or applications. Just as the collections framework simplified the organization and manipulation of in-memory data by providing implementations of commonly used data structures, the concurrency utilities simplify the development of concurrent classes by providing implementations of building blocks commonly used in concurrent designs. The concurrency utilities include a highperformance, flexible thread pool; a framework for asynchronous execution of tasks; a host of collection classes optimized for concurrent access; synchronization utilities such as counting semaphores (G); atomic variables; locks; and condition variables.
The concurrency utilities includes:
*Task scheduling framework. The Executor interface standardizes invocation, scheduling, execution, and control of asynchronous tasks according to a set of execution policies. Implementations are provided that enable tasks to be executed within the submitting thread, in a single background thread (as with events in Swing), in a newly created thread, or in a thread pool, and developers can create customized implementations of Executor that support arbitrary execution policies. The built-in implementations offer configurable policies such as queue length limits and saturation policy that can improve the stability of applications by preventing runaway resource use.
*Fork/join framework. Based on the ForkJoinPool class, this framework is an implementation of Executor. It is designed to efficiently run a large number of tasks using a pool of worker threads
(A) . A work-stealing technique is used to keep all the worker threads busy, to take full advantage of multiple processors.
*(C) Concurrent collections. Several new collections classes were added, including the new Queue, BlockingQueue and BlockingDeque interfaces, and high-performance, concurrent implementations of Map, List, and Queue. See the Collections Framework Guide for more information.
*(D) Atomic variables. Utility classes are provided that atomically manipulate single variables (primitive types or references), providing high-performance atomic arithmetic and compare-and-set methods. The atomic variable implementations in the java.util.concurrent.atomic package offer higher performance than would be available by using synchronization (on most platforms), making them useful for implementing high-performance concurrent algorithms and conveniently implementing counters and sequence number generators.
*(E) Synchronizers. General purpose synchronization classes, including semaphores, barriers, latches, phasers, and exchangers, facilitate coordination between threads.
*Locks. While locking is built into the Java language through the synchronized keyword, there are a number of limitations to built-in monitor locks. The java.util.concurrent.locks package provides a high-performance lock implementation with the same memory semantics as synchronization, and it also supports specifying a timeout when attempting to acquire a lock, multiple condition variables per lock, nonnested ("hand-over-hand") holding of multiple locks, and support for interrupting threads that are waiting to acquire a lock.
*Nanosecond-granularity timing. The System.nanoTime method enables access to a nanosecond-granularity time source for making relative time measurements and methods that accept timeouts (such as the BlockingQueue.offer, BlockingQueue.poll, Lock.tryLock, Condition.await, and Thread.sleep) can take timeout values in nanoseconds. The actual precision of the System.nanoTime method is platform-dependent.
Reference: Java SE Documentation, Concurrency Utilities

NEW QUESTION: 3
CloudWatchを使用して、Amazon EC2 Linuxインスタンスのメモリとディスクの使用率を監視できますか?
A. CloudWatchは、インスタンスの実行中にのみメモリとディスク使用量のメトリックを収集できます。
B. LinuxのCloudWatch Monitoringスクリプトを使用するLinux EC2インスタンスでのみ可能です。
C. CloudWatchはディスク使用量のみを測定できます。
D. CloudWatchはメモリ使用量のみを測定できます。
Answer: B
Explanation:
Explanation
Using the Cloudwatch Monitoring scripts for Linux, you can measure memory and disk usage of your Linux EC2 instances.
References:


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