Tree
A tree is a connected, acyclic structure of nodes, commonly organized hierarchically through parent-child relationships and optionally around a designated root.
Functional Programming in Scala, Second Edition
A recursive data structure whose values are formed from nodes such as leaves and branches, with this section focusing on structural shape during combination.
- How it is used
- Models recursive binary data while motivating structural recursion and reusable tree operations.
- How deep it goes
- Develops implementations for size, maximum, depth, map, and fold through pattern matching and recursive calls.
- Examples
- Uses node counting, positive-value search, maximum, depth, shape-preserving map, and fold-derived operations.
- What you can do after
- Build it from scratch by defining a binary Tree and deriving recursive operations or a fold.
Read how Functional Programming in Scala, Second Edition explains tree →
Grokking Algorithms, Second Edition
A tree is a connected graph with no cycles, so no path of edges leads back to an earlier vertex.
- How it is used
- Organizes directory traversal and motivates specialized trees for searching, compression, and database storage.
- How deep it goes
- Defines trees as connected acyclic graphs and works through rooted terminology and queue-based traversal.
- Examples
- Uses a file-directory traversal and searches for 7 and 8 in a binary search tree.
- What you can do after
- Apply it via Python's os and collections.deque to list files throughout a directory tree.
Read how Grokking Algorithms, Second Edition explains tree →
Object-Oriented Software Design in C++
A hierarchical data structure composed of nodes connected by parent-child relationships without cycles.
- How it is used
- Organizes hierarchical collections and supports repeated operations over their nodes.
- How deep it goes
- Defines roots, intermediate nodes, leaves, aggregation, traversal, and Visitor-based operations, but does not formalize tree variants.
- Examples
- Uses store departments and products plus intramural sports, games, residence halls, and generated reports.
- What you can do after
- Build it from scratch by modeling nodes, aggregation, traversal, and operations over a hierarchical collection.
Read how Object-Oriented Software Design in C++ explains tree →
Classic Computer Science Problems in Swift: Essential techniques for practicing programmers
- How it is used
- Frames trees as the structure sought when finding a minimum spanning tree for a weighted network.
- How deep it goes
- Defines trees through unique paths and cycles, then distinguishes connected graphs, spanning trees, and minimum spanning trees.
- Examples
- Uses a cycle among vertices B, C, and D, then removes the edge between C and D to form a tree.
- What you can do after
- Understand how removing an edge from a cycle can turn a graph into a tree.
Functional Programming in JavaScript
A hierarchical data structure of nodes connected by parent-child relationships with a root.
- How it is used
- Uses trees to make recursive processing of hierarchical data concrete in JavaScript.
- How deep it goes
- Defines roots, parents, children, nodes, and recursive mapping with JavaScript classes.
- Examples
- Uses a mathematician student hierarchy, chained append calls, and recursive name mapping.
- What you can do after
- Builds a JavaScript tree and recursively transforms every node.
Read how Functional Programming in JavaScript explains tree →
Optimization Algorithms: AI techniques for design, planning, and control problems
A connected acyclic data structure consisting of nodes linked by hierarchical edges.
- How it is used
- Defines a cycle-free, connected structure within graph theory and blind-search algorithm terminology.
- How deep it goes
- Provides a concise definition and classification, but stops short of tree operations, traversal algorithms, and complexity analysis.
- Examples
- Uses NetworkX code for undirected, directed, multigraph, acyclic, and weighted graph examples.
- What you can do after
- Evaluate whether a graph fits the defining connected, cycle-free, self-loop-free structure of a tree.
Grokking Data Structures
A tree is a hierarchical data structure whose elements are connected by parent-child relationships without cycles.
- How it is used
- Models hierarchical relationships, branching choices, and specialized storage or search structures.
- How deep it goes
- Defines nodes, subtrees, roots, leaves, branching, and graph properties, then points toward specialized trees without implementation details.
- Examples
- Uses breakfast choices, hierarchical relationships, linked-list comparisons, and applications including databases, indexing, priority queues, and classification.
- What you can do after
- Evaluate whether branching relationships call for a tree instead of a linear structure such as a linked list.
Advanced Algorithms and Data Structures
A tree is a hierarchical data structure composed of nodes connected by parent-child relationships without cycles.
- How it is used
- Uses hierarchical parent-child organization to represent partitions and support dynamic dictionary search.
- How deep it goes
- Explains parent-pointer representation, recursive root finding, merging, balanced-search assumptions, and traversal costs.
- Examples
- Uses parent mappings for partitions, a spell-checking dictionary, and a binary search for the missing word “antic.”
- What you can do after
- Build parent-pointer partitions and implement root finding and merging while estimating tree-height costs.
Read how Advanced Algorithms and Data Structures explains tree →
Software Design for Python Programmers
A tree is a hierarchical data structure composed of nodes connected in parent-child relationships.
- How it is used
- Organizes hierarchical data for repeated root-to-leaf passes using different algorithms.
- How deep it goes
- Explains roots, leaves, heterogeneous nodes, aggregation, and traversal, then demonstrates the structure with Python classes.
- Examples
- Uses store products and intramural sports reports to illustrate roots, departments, sports, games, halls, and leaves.
- What you can do after
- Apply it via the Visitor Design Pattern to run multiple reports over one hierarchical data collection.
Read how Software Design for Python Programmers explains tree →
Grokking AI Algorithms, Second Edition
A tree is a connected acyclic data structure organized into nodes with a single root and hierarchical parent-child relationships.
- How it is used
- Represents hierarchical values and search possibilities, especially paths through maze-like problems.
- How deep it goes
- Defines core terminology and traces BFS traversal, but stops short of formal proofs or broader implementation trade-offs.
- Examples
- Uses labeled tree diagrams, a maze movement tree, BFS visit sequences, and a Python BFS listing.
- What you can do after
- Apply it via breadth-first search to generate branches, visit nodes by depth, and reconstruct a path to a goal.
Read how Grokking AI Algorithms, Second Edition explains tree →
100 Java Mistakes and How to Avoid Them
A tree-like data structure organizes elements into parent-child relationships and ordinarily has no cycles.
- How it is used
- Uses tree traversal to expose when apparently finite recursion becomes infinite.
- How deep it goes
- Explains recursive traversal and distinguishes legal cycles from construction mistakes, but stops short of implementation code.
- Examples
- Uses recursive tree traversal and self-referential collection behavior to demonstrate cycle-related failure.
- What you can do after
- Diagnose traversal failures by checking for cycles and either tracking visited nodes or repairing invalid structure construction.
Read how 100 Java Mistakes and How to Avoid Them explains tree →
Related concepts
- binary treeincludes · A binary tree is a tree data structure in which each node has at most two children.
- graphkind of · A graph is a mathematical structure consisting of vertices connected by edges that represent relationships or connections.
- acyclic graphkind of · An acyclic graph is a graph that contains no cycles.
- minimum spanning treeincludes · A minimum spanning tree is a spanning tree of a connected, weighted, undirected graph having the smallest possible total edge weight.
- directory structureincludes · A directory structure is the hierarchical arrangement of directories and files in a filesystem or software project.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.