perf: npc/monster storage with vector indexing

[dudantas]

Description

This PR modifies the internal storage of NPCs and monsters in the Game class from std::unordered_map to a combination of std::vector and std::unordered_map indexes for improved lookup efficiency and better memory locality.

Resolves this:

Motivation

Previously, every time a search was performed for an NPC or a monster, the unordered map was iterated, and even though it provides average O(1) complexity for lookups, the actual cost becomes significant when handling a large dataset (e.g., 80,000 monsters). This cost arises from the overhead of hashing and poor memory locality, as unordered maps store elements in a hash table.

Switching to a vector with index-based lookup improves the following:

1. Memory locality: Vectors store elements contiguously in memory, improving cache efficiency when accessing elements sequentially or repeatedly.
2. Lookup efficiency: Using an unordered map as an index to the vector allows leveraging direct index-based access (constant time) to the actual data, combining the best of both structures.

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Behaviour

Actual

• Lookups for monsters or NPCs require multiple hash operations and traversals, resulting in higher overhead for large datasets.

Expected

• Lookups are performed efficiently by first finding the index from the unordered map and then directly accessing the data in the vector.

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Type of change

• Performance improvement (non-breaking change which improves efficiency)

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How Has This Been Tested

• Performed stress tests with datasets containing 80,000+ NPCs and monsters to compare the lookup time and resource utilization.
• Verified that all existing functionality works without modifications.

Tests performed:

• Lookups for existing and non-existing monsters/NPCs.
• Addition and removal of monsters/NPCs.
• Ensured consistency between the unordered map index and the vector.

Checklist

• My code follows the style guidelines of this project.
• I have performed a self-review of my own code.
• I checked the PR checks reports.
• I have commented my code, particularly in hard-to-understand areas.
• My changes generate no new warnings.
• I have added tests that prove my fix is effective or that my feature works.

[sonarqubecloud]

Quality Gate passed

Issues
2 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud