Computer Science Processes - Programming Framework Analysis

This document presents computer science processes analyzed using the Programming Framework methodology. Each process is represented as a computational flowchart with standardized color coding: Red for triggers/inputs, Yellow for structures/objects, Green for processing/operations, Blue for intermediates/states, and Violet for products/outputs. Yellow nodes use black text for optimal readability, while all other colors use white text.

1. QuickSort Algorithm Process

graph TD A[Input Array] --> B[Choose Pivot] B --> C[Partition Array] C --> D[Recursive Sort Left] C --> E[Recursive Sort Right] D --> F[Merge Results] E --> F F --> G[Sorted Array] style A fill:#ff6b6b,color:#fff style B fill:#ffd43b,color:#000 style C fill:#51cf66,color:#fff style D fill:#74c0fc,color:#fff style E fill:#74c0fc,color:#fff style F fill:#51cf66,color:#fff style G fill:#b197fc,color:#fff
Inputs & Data Data Structures & Arrays Operations & Algorithms States & Variables Output & Results
Figure 1. QuickSort Algorithm Process. This computer science process visualization demonstrates the computational logic of the QuickSort algorithm. The flowchart shows input data and parameters, data structures and arrays, algorithmic operations and comparisons, intermediate states and recursive calls, and final sorted output.

2. Binary Search Tree Process

graph TD A[Search Key] --> B[Compare with Root] B --> C[Key less than Root Question] C -->|Yes| D[Search Left Subtree] C -->|No| E[Search Right Subtree] D --> F[Recursive Search] E --> G[Recursive Search] F --> H[Key Found Question] G --> I[Key Found Question] H -->|Yes| J[Return Node] H -->|No| K[Return Null] I -->|Yes| L[Return Node] I -->|No| M[Return Null] J --> N[Search Successful] L --> N K --> O[Search Unsuccessful] M --> O style A fill:#ff6b6b,color:#fff style B fill:#ffd43b,color:#000 style C fill:#51cf66,color:#fff style D fill:#74c0fc,color:#fff style E fill:#74c0fc,color:#fff style F fill:#51cf66,color:#fff style G fill:#51cf66,color:#fff style H fill:#51cf66,color:#fff style I fill:#51cf66,color:#fff style J fill:#74c0fc,color:#fff style K fill:#74c0fc,color:#fff style L fill:#74c0fc,color:#fff style M fill:#74c0fc,color:#fff style N fill:#b197fc,color:#fff style O fill:#b197fc,color:#fff
Inputs & Data Data Structures & Arrays Operations & Algorithms States & Variables Output & Results
Figure 2. Binary Search Tree Process. This computer science process visualization demonstrates the computational logic of binary search tree operations. The flowchart shows search key validation, tree structure analysis, binary search strategy, recursive traversal, and search result determination.

3. Dynamic Programming Process

graph TD %% Problem Definition A[Problem Statement] --> B[Problem Analysis] C[Input Parameters] --> D[Parameter Validation] E[Constraints] --> F[Constraint Analysis] %% Dynamic Programming Setup B --> G[Subproblem Identification] D --> H[State Space Definition] F --> I[Memory Requirements] %% Algorithm Design G --> J[Recursive Relation] H --> K[DP Table Structure] I --> L[Memory Allocation] %% Implementation J --> M[Base Case Definition] K --> N[Table Initialization] L --> O[Array Creation] %% Computation M --> P[Fill Base Cases] N --> Q[Iterative Computation] O --> R[State Transitions] %% Solution Construction P --> S[DP Table Population] Q --> T[Optimal Value Calculation] R --> U[Path Reconstruction] %% Final Result S --> V[Optimal Solution] T --> W[Performance Analysis] U --> X[Solution Verification] %% Styling - Computer Science Color Scheme %% Red: Inputs & Triggers style A fill:#ff6b6b,color:#fff style C fill:#ff6b6b,color:#fff style E fill:#ff6b6b,color:#fff %% Yellow: Structures & Objects style B fill:#ffd43b,color:#000 style D fill:#ffd43b,color:#000 style F fill:#ffd43b,color:#000 style G fill:#ffd43b,color:#000 style H fill:#ffd43b,color:#000 style I fill:#ffd43b,color:#000 style J fill:#ffd43b,color:#000 style K fill:#ffd43b,color:#000 style L fill:#ffd43b,color:#000 style M fill:#ffd43b,color:#000 style N fill:#ffd43b,color:#000 style O fill:#ffd43b,color:#000 %% Green: Processing & Operations style P fill:#51cf66,color:#fff style Q fill:#51cf66,color:#fff style R fill:#51cf66,color:#fff style S fill:#51cf66,color:#fff style T fill:#51cf66,color:#fff style U fill:#51cf66,color:#fff %% Blue: Intermediates & States style V fill:#74c0fc,color:#fff style W fill:#74c0fc,color:#fff style X fill:#74c0fc,color:#fff
Inputs & Data Data Structures & Arrays Operations & Algorithms States & Variables Output & Results
Figure 3. Dynamic Programming Process. This computer science process visualization demonstrates the computational logic of dynamic programming algorithms. The flowchart shows problem analysis, subproblem identification, recursive relation formulation, table-based computation, and optimal solution construction.

4. Graph Traversal Process

graph TD %% Graph Representation A[Graph Structure] --> B[Graph Analysis] C[Starting Vertex] --> D[Vertex Validation] E[Traversal Type] --> F[Algorithm Selection] %% Data Structure Setup B --> G[Adjacency List/Matrix] D --> H[Vertex Initialization] F --> I[Queue/Stack Selection] %% Traversal Initialization G --> J[Graph Representation] H --> K[Visited Array] I --> L[Data Structure Creation] %% Traversal Process J --> M[Neighbor Discovery] K --> N[Visit Tracking] L --> O[Element Management] %% Algorithm Execution M --> P[Neighbor Processing] N --> Q[Visit Marking] O --> R[Element Removal] %% Completion P --> S[Traversal Complete] Q --> T[All Vertices Visited] R --> U[Data Structure Empty] %% Final Result S --> V[Traversal Order] T --> W[Connected Components] U --> X[Algorithm Termination] %% Styling - Computer Science Color Scheme %% Red: Inputs & Triggers style A fill:#ff6b6b,color:#fff style C fill:#ff6b6b,color:#fff style E fill:#ff6b6b,color:#fff %% Yellow: Structures & Objects style B fill:#ffd43b,color:#000 style D fill:#ffd43b,color:#000 style F fill:#ffd43b,color:#000 style G fill:#ffd43b,color:#000 style H fill:#ffd43b,color:#000 style I fill:#ffd43b,color:#000 style J fill:#ffd43b,color:#000 style K fill:#ffd43b,color:#000 style L fill:#ffd43b,color:#000 %% Green: Processing & Operations style M fill:#51cf66,color:#fff style N fill:#51cf66,color:#fff style O fill:#51cf66,color:#fff style P fill:#51cf66,color:#fff style Q fill:#51cf66,color:#fff style R fill:#51cf66,color:#fff style S fill:#51cf66,color:#fff style T fill:#51cf66,color:#fff style U fill:#51cf66,color:#fff %% Blue: Intermediates & States style V fill:#74c0fc,color:#fff style W fill:#74c0fc,color:#fff style X fill:#74c0fc,color:#fff
Inputs & Data Data Structures & Arrays Operations & Algorithms States & Variables Output & Results
Figure 4. Graph Traversal Process. This computer science process visualization demonstrates the computational logic of graph traversal algorithms. The flowchart shows graph representation, vertex initialization, neighbor discovery, visit tracking, and traversal completion.

5. Memory Management Process

graph TD %% Memory Request A[Memory Request] --> B[Request Analysis] C[Size Requirements] --> D[Size Validation] E[Memory Type] --> F[Type Selection] %% Memory Allocation B --> G[Free List Search] D --> H[Block Size Check] F --> I[Allocation Strategy] %% Block Management G --> J[Free Block Identification] H --> K[Block Splitting] I --> L[Allocation Method] %% Memory Assignment J --> M[Block Assignment] K --> N[Remaining Block] L --> O[Memory Marking] %% Deallocation M --> P[Memory Usage] N --> Q[Free Block Update] O --> R[Allocation Complete] %% Cleanup P --> S[Memory Release] Q --> T[Free List Update] R --> U[Fragmentation Check] %% Final State S --> V[Memory Freed] T --> W[Free List Maintained] U --> X[Memory Management Complete] %% Styling - Computer Science Color Scheme %% Red: Inputs & Triggers style A fill:#ff6b6b,color:#fff style C fill:#ff6b6b,color:#fff style E fill:#ff6b6b,color:#fff %% Yellow: Structures & Objects style B fill:#ffd43b,color:#000 style D fill:#ffd43b,color:#000 style F fill:#ffd43b,color:#000 style G fill:#ffd43b,color:#000 style H fill:#ffd43b,color:#000 style I fill:#ffd43b,color:#000 style J fill:#ffd43b,color:#000 style K fill:#ffd43b,color:#000 style L fill:#ffd43b,color:#000 style M fill:#ffd43b,color:#000 style N fill:#ffd43b,color:#000 style O fill:#ffd43b,color:#000 %% Green: Processing & Operations style P fill:#51cf66,color:#fff style Q fill:#51cf66,color:#fff style R fill:#51cf66,color:#fff style S fill:#51cf66,color:#fff style T fill:#51cf66,color:#fff style U fill:#51cf66,color:#fff %% Blue: Intermediates & States style V fill:#74c0fc,color:#fff style W fill:#74c0fc,color:#fff style X fill:#74c0fc,color:#fff
Inputs & Data Data Structures & Arrays Operations & Algorithms States & Variables Output & Results
Figure 5. Memory Management Process. This computer science process visualization demonstrates the computational logic of memory management systems. The flowchart shows memory request analysis, free block search, allocation strategy, block management, and memory cleanup operations.

Contact Information

Gary Welz

Retired Faculty Member

John Jay College, CUNY (Department of Mathematics and Computer Science)

Borough of Manhattan Community College, CUNY

CUNY Graduate Center (New Media Lab)

Email: gwelz@jjay.cuny.edu