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We would like to pause at this point for an important observation: We have defined three functions median, grade, and read_hw that operate on homework vectors Each of these functions treats the corresponding parameter in a fundamentally different way from the others, and each treatment has a purpose The median function ( 411/53) has a parameter of type vector<double> Therefore, calling that function causes the argument to be copied, even though that argument might be a huge vector Despite the inefficiency, vector<double> is the right parameter type for median, because this type ensures that taking the median of a vector doesn't change the vector The median function sorts its parameter If it did not copy its argument, then calling median(homework) would change the value of homework The grade function that takes a homework vector ( 412/54) has a parameter of type const vector<double>& In this type, the & asks the implementation not to copy the argument, and the const promises that the program will not change the parameter Such parameters are an important technique for making programs more efficient They are a good idea whenever the function will not change the parameter's value, and the parameter is of a type, such as vector or string, with values that might be time-consuming to copy It is usually not worth the bother to use const references for parameters of simple built-in types, such as int or double Such small objects are usually fast enough to copy that there's little, if any, overhead in passing them by value The read_hw function has a parameter of type vector<double>&, without the const Again, the & asks the implementation to bind the parameter directly to the argument, thus avoiding having to copy the argument But here, the reason to avoid the copy is that the function intends to change the argument's value Arguments that correspond to nonconst reference parameters must be lvalues that is, they must be nontemporary objects Arguments that are passed by value or bound to a const reference can be any value For example, suppose we have a function that returns an empty vector: vector<double> emptyvec() { vector<double> v; // no elements return v; }.

As the model changes, we would like the view to automatically adjust so that it always displays the current model state To accomplish this, create a new listener in the FavoritesManagerEditPart to refresh the edit parts based upon the model changes

private final FavoritesManagerListener modelListener = new FavoritesManagerListener() { public void favoritesChanged(FavoritesManagerEvent event) { refresh(); } };

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There are a number of obvious violations of this principle in the Java platform libraries For example, a stack is not a vector, so Stack should not extend Vector Similarly, a property list is not a hash table so Properties should not extend Hashtable In both cases, composition would have been appropriate If you use inheritance where composition is appropriate, you needlessly expose implementation details The resulting API ties you to the original implementation, forever limiting the performance of your class More seriously, by exposing the internals you let the client access them directly At the very least, this can lead to confusing semantics For example, if p refers to a Properties instance, then pgetProperty(key) may yield different results from pget(key): The former method takes defaults into account, while the latter method, which is inherited from Hashtable, does not Most seriously, the client may be able to corrupt invariants of the subclass by modifying the superclass directly In the case of Properties, the designers intended that only strings be allowed as keys and values, but direct access to the underlying Hashtable allows this invariant to be violated Once this invariant is violated, it is no longer possible to use other parts of the Properties API (load and store) By the time this problem was discovered, it was too late to correct it because clients depended on the use of nonstring keys and values There is one last set of questions you should ask yourself before deciding to use inheritance rather than composition Does the class that you're contemplating extending have any flaws in its API If so, are you comfortable propagating those flaws into the API of your class Inheritance propagates any flaws in the superclass's API, while composition allows you to design a new API that hides these flaws To summarize, inheritance is powerful, but it is problematic because it violates encapsulation It is appropriate only when a genuine subtype relationship exists between the subclass and the superclass Even then, inheritance may lead to fragility if the subclass is in a different package from the superclass and the superclass is not designed for extension To avoid this fragility, use composition and forwarding instead of inheritance, especially if an appropriate interface to implement a wrapper class exists Not only are wrapper classes more robust than subclasses, they are also more powerful.

We could call this function, and use the result as an argument to our second grade function from 412/54: grade(midterm, final, emptyvec());

When a model change occurs, the edit part should act accordingly by refreshing whatever has changed from the model For simplicity, our model listener described above uses the refresh() method, which is appropriate for small to medium sized models As models become larger, the time to execute the refresh() method increases in a linear fashion If at some point performance becomes sluggish, consider using explicit calls to addChild() and removeChild() rather than calling refresh() Edit parts have the methods activate() and deactivate() which are called when the edit part is added and removed These methods provide the ideal place to add and remove model listeners Add the following methods to FavoritesManagerEditPart so that it will receive notifications as the model changes

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