Abstract
The existing multi-layer tree is of dynamic linked list type which has many limitations and is complicated due to the pointer-node structure. Static array representation gives more flexibility in programming of algorithms and operations like insertion, deletion, and search. It also reduces the storage space. This paper presents a new method for representing multi-layer forest data structure in array format. It also explains various tree operations, unique data compression algorithm and migration algorithm between traditional approach and the proposed data structure. Most of the fundamental algorithms like those from artificial intelligence that employ decision trees are based on trees/forest data structure. The current paper brings a completely new idea in the representation of these data structures without employing recursion and targeting memory optimizations with reduced code complexities. The applications of forest data structures are many and span over various interdisciplinary areas of Engineering, Medicine, Aviation, Locomotive, Marine, etc. The proposed novel approach not just introduces a new method to look at the tree data structure but also provides the flexibility to adapt to the existing methods as per the user needs. A few such applications in Simulink debugging and the Forest visualisation have been discussed in detail in this paper.
Highlights
Storing information and being able to process it as per the requirement is the most essential feature of a database or computer science in general
For proof of concept that the proposed method is generalized to all multi-layer trees and to be able to use the traditional linked list approach when required, we have proposed a method for re-construction of the linked list data structure from the proposed tree storage algorithm
With the traditional approach of linked lists and recursion, tree traversal is a depth first approach but for our data structure we move to breadth first idea which is more appropriate in certain applications
Summary
Storing information and being able to process it as per the requirement is the most essential feature of a database or computer science in general. For proof of concept that the proposed method is generalized to all multi-layer trees and to be able to use the traditional linked list approach when required, we have proposed a method for re-construction of the linked list data structure from the proposed tree storage algorithm. The algorithm is not just used from a storage or data structure point of view but can be used in algorithms like the decision tree, random forest, and other pruning applications.
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