Singly linked lists Doubly linked lists Chapter 2. Linked Lists Singly linked lists Doubly linked lists aka lecture 3
Dynamic data structures Data collections (e.g. stored library records) can vary considerably in size. Arrays not always best solution: Inserting/deleting a new element requires much of array to be rewritten Array size is fixed, must be estimated before use If only few items held, much of array (hence memory) is wasted Solution: dynamic data structures (linked data structures) - don’t need to know how many items to expect - can increase/decrease memory when items added/deleted
Examples Linked lists Trees Binary trees Binary search trees AVL trees B trees Will look at all of these All use objects which are created dynamically, using memory from a special storage area (pool/heap).
Singly Linked Lists (Goodrich § 3.2) A singly linked list is a concrete data structure consisting of a sequence of nodes Each node stores element link to the next node (or null) First node in list referred to as head next elem node A B C D head 4
next node For an easy introduction we will have a list of Strings element The thing above is our Node
The Node Class for String objects next node element
The Node Class for String objects Sometimes called “head” next node element
The Node Class for String objects Sometimes called “tail” next node element
The Node Class for String objects constructors next node element
The Node Class for String objects get next node element
The Node Class for String objects set next node element
Over loading next node element
Don’t like
better
The list
head size
head = null size = 0
if head == null return true; else return false; NO!
head StringList L = size = 3 L.addFront(“pig”) head StringList L = dog owl cat StringList L = L.addFront(“pig”) head size = 4 StringList L = dog owl cat pig
Inserting at the Head Allocate a new node
Inserting at the Head Allocate a new node
Inserting at the Head Allocate a new node New node points to old head
Inserting at the Head Allocate a new node New node points to old head Head points to new node
Inserting at the Head Allocate a new node New node points to old head Head points to new node Increase size counter
Removing at the Head Update head to point to next node in the list
Removing at the Head Update head to point to next node in the list Allow garbage collector to reclaim the former first node
head StringList L = size = 4 head StringList L = size = 3 YIKES! dog owl cat pig head size = 3 StringList L = dog owl cat pig YIKES!
Removing at the Tail Removing at the tail of a singly linked list is not efficient! There is no constant-time way to update the tail to point to the previous node -Would need to keep a record of which node is the last node and which node points to the last node (even then can’t do it in constant time!)
Java code for a singly linked list of Strings In our implementation instance variables are head (reference to head node) and size (number of nodes currently in list) - Different implementations have different instance variables (some store the head and last/tail, some size (some not)). Will see later, depends what we actually want to do with our list. Our implementation is specific to strings. You will need to adapt it to accept values of other types - we will see a generic linked list later.
We have seen this
Simple Remove and Exception We have seen this But not this
The toString method Iterating over a list
The toString method This is a pointer that traverses the list Iterating over a list
The toString method Iterating over a list
The toString method What’s happening here? Iterating over a list
The toString method What’s happening here? implicit cursor.toString() Iterating over a list
The toString method Iterating over a list
The toString method So we don’t have a list (pig,dog,owl,cat,) Iterating over a list
Iterating over a list … and this is a very nice template (pattern) for iterating over a linked list Iterating over a list
Linear Search: isPresent Checking to see if a node containing a given value is in the list: Use a variable temp of type Node, initially pointing to (node pointed to by) head and progressively pointing to nodes along list until temp points to node containing value of interest, or temp points to null (i.e. end of list): > Searching for “when” return true temp temp temp It’s easy when you know how head > Searching for “bucket” temp temp temp temp temp temp temp It’s easy when you know how head ADS2 Lecture 4 return false 45 (Alice’s slide)
Linear Search: isPresent
Linear Search: isPresent Assume we haven’t found what we are looking for
Linear Search: isPresent Our travelling cursor
Linear Search: isPresent Quit if we have hit end-of-list or we found what we are looking for
Linear Search: isPresent Quit if we have hit end-of-list or we found what we are looking for NOTE: we quit if “X or Y” is same as we continue if “¬X and ¬Y” De Morgan’s law!!!!
Linear Search: isPresent Is this what we are looking for?
Linear Search: isPresent Move the cursor down the list
Linear Search: isPresent Did we find it?
Linear Search: isPresent note naming conventions (toString, isPresent, …) note that we do NOT do things like if (x > y) then b = true else b = false please … note, no assumptions about order in data how could we use order if we had it? note, I use “cursor” rather than “temp” (why?)
Linear Search: isPresent NOTE similarity
Linear Search: isPresent Is this better?
Linear Search: isPresent Is this better?
Linear Search: isPresent Is this better?
Linear Search: isPresent Is this better?
Linear Search: isPresent Is this better?
61 ADS2 Lecture 3
Inserting at the Tail Allocate a new node Insert new element Note, need to keep a record of the “last” (or “tail”) node. In Java do this via extra instance variable in list. See lecture 5. Allocate a new node Insert new element Have new node point to null Have old tail node point to new node Update tail to point to new node Exercise for you: Start off with an empty list and add the following Strings, in the order given. This time insert at the tail each time. Starting from the head read off the Strings. “how”, “know”, “you”, “when”, “easy”, “it’s” ADS2 Lecture 3