软件专业毕业论文外文文献中英文翻译

软件专业毕业论文外文文献中英文翻译

Object landscapes and lifetimes

Technically, OOP is just about abstract data typing, inheritance, and polymorphism, but other issues can be at least as important. The remainder of this section will cover these issues.

One of the most important factors is the way objects are created and destroyed. Where is the data for an object and how is the lifetime of the object controlled? There are different philosophies at work here. C++ takes the approach that control of efficiency is the most important issue, so it gives the programmer a choice. For maximum run-time speed, the storage and lifetime can be determined while the program is being written, by placing the objects on the stack (these are sometimes called automatic or scoped variables) or in the static storage area. This places a priority on the speed of storage allocation and release, and control of these can be very valuable in some situations. However, you sacrifice flexibility because you must know the exact quantity, lifetime, and type of objects while you're writing the program. If you are trying to solve a more general problem such as computer-aided design, warehouse management, or air-traffic control, this is too restrictive.

The second approach is to create objects dynamically in a pool of memory called the heap. In this approach, you don't know until run-time how many objects you need, what their lifetime is, or what their exact type is. Those are determined at the spur of the moment while the program is running. If you need a new object, you simply make it on the heap at the point that you need it. Because the storage is managed dynamically, at run-time, the amount of time required to allocate storage on the heap is significantly longer than the time to create storage on the stack. (Creating storage on the stack is often a single assembly instruction to move the stack pointer down, and another to move it back up.) The dynamic approach makes the generally logical assumption that objects tend to be complicated, so the extra overhead of finding storage and releasing that storage will not have an important impact on the creation of an object. In addition, the greater flexibility is essential to solve the general programming problem.

Java uses the second approach, exclusively]. Every time you want to create an object, you use the new keyword to build a dynamic instance of that object.

There's another issue, however, and that's the lifetime of an object. With languages that allow objects to be created on the stack, the compiler determines how long the object lasts and can automatically destroy it. However, if you create it on the heap the compiler has no knowledge of its lifetime. In a language like C++, you must determine programmatically when to destroy the object, which can lead to memory leaks if you don’t do it correctly (and this is a common problem in C++ programs). Java provides a feature called a garbage collector that automatically discovers when an object is no longer in use and destroys it. A garbage collector is much more convenient because it reduces the number of issues that you must track and the code you must write. More important, the garbage collector provides a much higher level of insurance against the insidious problem of memory leaks (which has brought many a C++ project to its knees).

The rest of this section looks at additional factors concerning object lifetimes and landscapes.

1. The singly rooted hierarchy

One of the issues in OOP that has become especially prominent since the introduction of C++ is whether all classes should ultimately be inherited from a single base class. In Java (as with virtually all other OOP languages) the answer is “yes” and the name of this ultimate base class is simply Object. It turns out that the benefits of the singly rooted hierarchy are many.

All objects in a singly rooted hierarchy have an interface in common, so they are all ultimately the same type. The alternative (provided by C++) is that you don’t know that everything is the same fundamental type. From a backward-compatibility standpoint this fits the model of C better and can be thought of as less restrictive, but when you want to do full-on object-oriented programming you must then build your own hierarchy to provide the same convenience that’s built into other OOP languages. And in any new class library you acquire, some other incompatible interface will be used. It requires effort (and possibly multiple inheritance) to work the new interface into your design. Is the extra “flexibility” of C++ worth it? If you need it—if you have a large investment in C—it’s quite valuable. If you’re starting from scratch, other alternatives such as Java can often be more productive.

All objects in a singly rooted hierarchy (such as Java provides) can be guaranteed to have certain functionality. You know you can perform certain basic operations on every object in your system. A singly rooted hierarchy, along with creating all objects on the heap, greatly simplifies

argument passing (one of the more complex topics in C++).

A singly rooted hierarchy makes it much easier to implement a garbage collector (which is conveniently built into Java). The necessary support can be installed in the base class, and the garbage collector can thus send the appropriate messages to every object in the system. Without a singly rooted hierarchy and a system to manipulate an object via a reference, it is difficult to implement a garbage collector.

Since run-time type information is guaranteed to be in all objects, you’ll never end up with an object whose type you cannot determine. This is especially important with system level operations, such as exception handling, and to allow greater flexibility in programming.

2 .Collection libraries and support for easy collection use

Because a container is a tool that you’ll use frequently, it makes sense to have a library of containers that are built in a reusable fashion, so you can take one off the shelf Because a container is a tool that you’ll use frequently, it makes sense to have a library of containers that are built in a reusable fashion, so you can take one off the shelf and plug it into your program. Java provides such a library, which should satisfy most needs.

Downcasting vs. templates/generics

To make these containers reusable, they hold the one universal type in Java that was previously mentioned: Object. The singly rooted hierarchy means that everything is an Object, so a container that holds Objects can hold anything. This makes containers easy to reuse.

To use such a container, you simply add object references to it, and later ask for them back. But, since the container holds only Objects, when you add your object reference into the container it is upcast to Object, thus losing its identity. When you fetch it back, you get an Object reference, and not a reference to the type that you put in. So how do you turn it back into something that has the useful interface of the object that you put into the container?

Here, the cast is used again, but this time you’re not casting up the inheritance hierarchy to a more general type, you cast down the hierarchy to a more specific type. This manner of casting is called downcasting. With upcasting, you know, for example, that a Circle is a type of Shape so it’s safe to upcast, but you don’t know that an Object is necessarily a Circle or a Shape so it’s hardly

safe to downcast unless you know that’s what you’re dealing with.

It’s not completely dangerous, however, because if you downcast to the wrong thing you’ll get a run-time error called an exception, which will be described shortly. When you fetch object references from a container, though, you must have some way to remember exactly what they are so you can perform a proper downcast.

Downcasting and the run-time checks require extra time for the running program, and extra effort from the programmer. Wouldn’t it make sense to somehow create the container so that it knows the types that it holds, eliminating the need for the downcast and a possible mistake? The solution is parameterized types, which are classes that the compiler can automatically customize to work with particular types. For example, with a parameterized container, the compiler could customize that container so that it would accept only Shapes and fetch only Shapes.

Parameterized types are an important part of C++, partly because C++ has no singly rooted hierarchy. In C++, the keyword that implements parameterized types is “template.” Java currently has no parameterized types since it is possible for it to get by—however awkwardly—using the singly rooted hierarchy. However, a current proposal for parameterized types uses a syntax that is strikingly similar to C++ templates.

对象的创建和存在时间

从技术角度说，OOP（面向对象程序设计）只是涉及抽象的数据类型、继承以及多形性，但另一些问题也可能显得非常重要。本节将就这些问题进行探讨。

最重要的问题之一是对象的创建及破坏方式。对象需要的数据位于哪儿，如何控制对象的“存在时间”呢？针对这个问题，解决的方案是各异其趣的。C++认为程序的执行效率是最重要的一个问题，所以它允许程序员作出选择。为获得最快的运行速度，存储以及存在时间可在编写程序时决定，只需将对象放置在堆栈（有时也叫作自动或定域变量）或者静态存储区域即可。这样便为存储空间的分配和释放提供了一个优先级。某些情况下，这种优先级的控制是非常有价值的。然而，我们同时也牺牲了灵活性，因为在编写程序时，必须知道对象的准确的数量、存在时间、以及类型。如果要解决的是一个较常规的问题，如计算机辅助设计、仓储管理或者空中交通控制，这一方法就显得太局限了。

第二个方法是在一个内存池中动态创建对象，该内存池亦叫“堆”或者“内存堆”。若采用这种方式，除非进入运行期，否则根本不知道到底需要多少个对象，也不知道它们的存在时间有多长，以及准确的类型是什么。这些参数都在程序正式运行时才决定的。若需一个新对象，只需在需要它的时候在内存堆里简单地创建它即可。由于存储空间的管理是运行期间动态进行的，所以在内存堆里分配存储空间的时间比在堆栈里创建的时间长得多（在堆栈里创建存储空间一般只需要一个简单的指令，将堆栈指针向下或向下移动即可）。由于动态创建方法使对象本来就倾向于复杂，所以查找存储空间以及释放它所需的额外开销不会为对象的创建造成明显的影响。除此以外，更大的灵活性对于常规编程问题的解决是至关重要的。

C++允许我们决定是在写程序时创建对象，还是在运行期间创建，这种控制方法更加灵活。大家或许认为既然它如此灵活，那么无论如何都应在内存堆里创建对象，而不是在堆栈中创建。

但还要考虑另外一个问题，亦即对象的“存在时间”或者“生存时间”（Lifetime）。若在堆栈或者静态存储空间里创建一个对象，编译器会判断对象的持续时间有多长，到时会自动“破坏”或者“清除”它。程序员可用两种方法来破坏一个对象：用程序化的方式决定何时破坏对象，或者利用由运行环境提供的一种“垃圾收集器”特性，自动寻找那些不再使