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Dynamic Linked Structures: Maximizing Efficiency in Data Management

Explore the dynamic world of linked structures, like linear linked lists, in data management. Learn their advantages, representation, operations such as insertion and deletion, traversal techniques, and search patterns.

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Dynamic Linked Structures: Maximizing Efficiency in Data Management

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  1. Linear Linked Structures A bank is a place where they lend you an umbrella in fair weather and ask for it back when it begins to rain. Robert Frost (1874-1963)

  2. Dynamic Structures • collections • limitations of static structures (i.e. arrays) • fixed size • waste space • rearrangement of entries • sharing between structures? • dynamic data structures • change size over time • storage proportional to amount of information • linked structures • nodes (objects) connected together by references • dynamic allocation/deallocation • in array proximity implicit, in linked structure it is explicit • linear linked structures • aka linked lists

  3. Sequentially-linked Structures • each node indicates its successor (via a reference) • first node located via reference • last node has no successor (null) • each node represents one entity • empty collection has null reference

  4. Representation • nodes are objects • dynamic creation • let entity objects be nodes? • add reference field • disadvantages • object must “know” it is on list • multiple lists • must modify class

  5. Node Wrapper Class • separate class references objects • wrapper class, mixin • fields • reference (p.theStudent) • link (p.next) • constructor • visibility • class • fields • as sequentially-linked structure • general case • initial (empty) state • multiple lists • different sequence of Nodes, same objects

  6. Operations • insertion • where? • deletion • which node? • traversal • “visit” all nodes • like array traversal • search • special traversal • simple vs exhaustive

  7. Insertion • insert where? • front • end • in some order (e.g. sorted) • at front • new entry points to previous front • list reference points to new entry • pattern • O(1) • repeated application • reverse order

  8. Deletion • delete which node? • first • last • matching a key • only if not empty • delete first • move list pointer to second node • garbage collection • node • entity • pattern • O(1)

  9. Traversal • sequential processing • to get to nth node must first get to (n-1)st node • travelling pointer • start at first node • move to node's successor • p = p.next • termination • no more nodes (p == null) • pattern • O(n) • vs array traversal • sequential traversal pattern

  10. Search • search key • two outcomes • success • failure • variant of traversal • two exits • end of list • found item • pattern • O(n)

  11. Insertion at End of List • for insertion in order • find end of list • traversal • 2 travelling pointers • initial state • q is predecessor of p • insert • pattern • traverse • updating p & q • insert • 2 cases • q == null (empty list) • q != null (at end) • O(n)

  12. Deletion of Last Node • must modify second last node • find second last node • traversal • 2 travelling pointers • test • pattern • pre test • error • traverse • delete • 2 cases • q == null (only node) • q != null (last node) • O(n)

  13. The End

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