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| - | The final alternative relies on the Java concept of **iterator** of collections. Informally, a collection of elements has the property that its elements can be //enumerated// or //iterated//. Any such collection is an ''Iterable'' (extends the Java interface Iterable). Here, ''RVList'' is such an iterable collection, which takes its elements at construction, from an array. ''RVList'' is **generic**, hence its elements can be of any type ''T''. | + | //Features:// |
| + | * The solution relies on the observation that **reversing a list** is a particular type of **folding operation**. Consider the sequence ''1,2,3'', the ''+'' operation and the initial value ''0''. Folding the sequence with ''+'' and ''0'', amounts to summing up the numbers from the sequence: | ||
| + | <code> | ||
| + | fold({1,2,3},+,0) = | ||
| + | fold({2,3},+,1+0) = | ||
| + | fold({3},+,2+1+0) = | ||
| + | fold({},+,3+2+1+0) = | ||
| + | 3+2+1+0 | ||
| + | </code> | ||
| - | The fundamental trait of an ''Iterable'' object is that it implements the method ''iterator'', which returns just that. An **iterator** is an object which allows enumerating all elements of the collection at hand, via the methods ''hasNext'' and ''next''. Sometimes (as in the case of a ''Set'') the order is unimportant. Here, the order matters - elements are explored in their reverse order. Technically, the iterator object is an **anonymous class**. | + | * However, the folding operation need not be arithmetic (nor the initial value - a number). Suppose we replace ''+'' by ''cons'' ('':'') and ''0'' by the empty list ''[]''. The result of the folding operation is ''3:2:1:[]'', which is precisely the reversed list. In this solution, the ''fold'' operation is implemented in an abstract fashion, with respect to a generic binary operation ''op'' and a generic initial value ''init''. |
| + | * List reversal is a **particular case of a fold operation** | ||
| + | |||
| + | //Possible usages:// | ||
| + | * This solution is also characteristic to the functional programming style, more specifically, programming with **higher-order functions**. A higher-order function (like ''fold'') takes other functions (like ''op'') and implements some functionality in terms of it. In a functional programming language, implementing (and using) a ''fold'' is much simpler and elegant than in an imperative language (like Java). | ||
| + | * Using higher-order functions is very useful when writing programs over large data (for processing like that done in Machine Learning). Such processing is done using a combination of //map-reduce// functions: //map// transforms data uniformly, and //reduce// computes a new (reduced) value from it. Map-reduce programs are easily to parallelise (however, reversal is not a demonstration for that). | ||
| - | This alternative focuses on **list traversal**, and on the **generality** of the approach. Basically, any Java collection (for which order makes sense) can be transformed to an array (via the ''toArray'' method) and subsequently - an ''RVList'' which can be traversed in reverse order via its iterator. | ||
| ==== Why so many reversals? ==== | ==== Why so many reversals? ==== | ||
| - | The reason for choosing reversal as a running example is that the task is algorithmically trivial: take the sequence of elements of the collection at hand, be it array of list (or anything else), in their **reverse** order. | + | Note that **reversal** is an algorithmically trivial task: take the sequence of elements of the collection at hand, be it array of list (or anything else), in their **reverse** order. |
| - | However, there are **many different ways** for implementing reversal, and each makes perfect sense in some setting. Moreover, some of these ways are: **subtle**, **conceptually challenging**, and require **higher skill/knowledge** in operating the programming language at hand. | + | Our point is that, apart from mastering algorithms, a skilled programmer needs **solid knowledge** on programming concepts and on the way programming languages (and the hardware they employ) are designed. In some cases, these concepts may be subtle (e.g. programming with Monads in Haskell) and may supersede the algorithm at hand in complexity. However, they are crucial in developing a **efficient**, **secure** and **correct** applications. |
| - | Our point, and one of the major objectives of this lecture, is to emphasise that, apart from developing fast and correct algorithms, a task of equal challenge and importance is **writing down the code**, in the **suitable programming language**. | + | This lecture will focus on different ways of **writing code** for specific algorithms, in different programming languages, with an emphasis on Functional Languages (Haskell) and Logic-based Languages (Prolog). |
| We have clear metrics for choosing algorithms. Do we also have metrics for **code writing**? For instance: | We have clear metrics for choosing algorithms. Do we also have metrics for **code writing**? For instance: | ||
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| ==== How many other ways? ==== | ==== How many other ways? ==== | ||
| - | There are many possible variations to our three examples, but a few elements do stand out: | + | There are many possible variations (and combinations) to our examples, but a few elements do stand out: |
| - | * the functional style for **representing a list** in the second example - very akin to Abstract Datatypes | + | * the functional style for **representing a list** - very akin to Abstract Datatypes |
| - | * the functional style for reversal - relying on recursion, in the same example | + | * the functional style for reversal - relying on recursion, relying on folding |
| * the Object Oriented style for **traversing a list** in the third example - which although is tightly linked to Java Collections, can be migrated to any other object-oriented language. | * the Object Oriented style for **traversing a list** in the third example - which although is tightly linked to Java Collections, can be migrated to any other object-oriented language. | ||
| - | These **elements of style** are frequently called **design patterns** - generic ways of writing code, which can be deployed for different implementations. | + | Such **elements of style** are may be called **design patterns**, i.e. generic ways of writing code, which can be deployed for different implementations. |
| - | Some elements of style may have some common ground, or rely on certain traits of the programming language. These latter are called programming **paradigms**. For instance, writing programs as recursive functions as well as representing data as ADTs (recall that constructors //are// functions) are both styles of the **functional** paradigm. | + | Some elements of style may have some common ground, or require certain traits from the programming language. These latter are called programming **paradigms**. For instance, writing programs as recursive functions, using higher-order functions and representing data as ADTs (recall that constructors //are// functions) are both styles of the **functional** paradigm. |
| In this lecture, we shall go over the following paradigms: | In this lecture, we shall go over the following paradigms: | ||