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Chapter 9: Minimum And Maximum

This generated chapter is split into sections because the merged source exceeds the public reference threshold.

Learning objectives​

  • Explain the main ideas and vocabulary in Minimum And Maximum.
  • Work through the source examples for Minimum And Maximum without depending on raw chunk order.
  • Use Minimum And Maximum as selective reference when learner modules point back to Introduction To Algorithms Clrs.

Prerequisites​

  • Earlier prerequisite concepts leading into Chapter 9: Minimum And Maximum.

Module targets​

  • module-02-sorting-searching-structures

AI companion modes​

  • Explain simply
  • Socratic tutor
  • Quiz me
  • Challenge my understanding
  • Diagnose my confusion
  • Generate extra practice
  • Revision mode
  • Connect forward / backward

Source-of-truth note​

This unit is anchored to Introduction To Algorithms Clrs and the source chapter "Chapter 9: Minimum And Maximum". Use external resources only to clarify, extend, or modernize details without replacing the chapter's conceptual spine.

External enrichment​

No chapter-specific enrichment resources are curated yet. Add them in the unit manifest when a source clearly improves learning.

Source provenance​

  • Primary source: Introduction To Algorithms Clrs
  • Source chapter 09: Chapter 9: Minimum And Maximum
  • Raw source file: 072-9-1-minimum-and-maximum.md
  • Raw source file: 073-9-2-selection-in-expected-linear-time.md
  • Raw source file: 074-9-2-selection-in-expected-linear-time.md
  • Raw source file: 075-9-3-selection-in-worst-case-linear-time.md
  • Raw source file: 076-9-3-selection-in-worst-case-linear-time.md
  • Raw source file: 077-9-3-selection-in-worst-case-linear-time.md
  • Raw source file: 078-9-3-selection-in-worst-case-linear-time.md

Sections​

  • No section routes are currently published for this chapter.