From 32dde5f82f0bd8b51c6bb3ecf5bb04d6052ebd14 Mon Sep 17 00:00:00 2001 From: Beatrix CHAN Date: Sat, 20 Sep 2025 12:27:46 +0100 Subject: [PATCH] translation: Update `chapter_data_structure/classification_of_data_structure.md` (#1800) * Update classification_of_data_structure.md * Update classification_of_data_structure.md * Fix punctuation and formatting in data structure chapter --------- Co-authored-by: Yudong Jin --- .../classification_of_data_structure.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/en/docs/chapter_data_structure/classification_of_data_structure.md b/en/docs/chapter_data_structure/classification_of_data_structure.md index b848eceb9..548e08c64 100644 --- a/en/docs/chapter_data_structure/classification_of_data_structure.md +++ b/en/docs/chapter_data_structure/classification_of_data_structure.md @@ -8,7 +8,7 @@ Common data structures include arrays, linked lists, stacks, queues, hash tables As shown in the figure below, logical structures can be divided into two major categories: "linear" and "non-linear". Linear structures are more intuitive, indicating data is arranged linearly in logical relationships; non-linear structures, conversely, are arranged non-linearly. -- **Linear data structures**: Arrays, Linked Lists, Stacks, Queues, Hash Tables. +- **Linear data structures**: Arrays, Linked Lists, Stacks, Queues, Hash Tables, where elements have a one-to-one sequential relationship. - **Non-linear data structures**: Trees, Heaps, Graphs, Hash Tables. Non-linear data structures can be further divided into tree structures and network structures. @@ -30,7 +30,7 @@ Non-linear data structures can be further divided into tree structures and netwo It's worth noting that comparing memory to an Excel spreadsheet is a simplified analogy. The actual working mechanism of memory is more complex, involving concepts like address space, memory management, cache mechanisms, virtual memory, and physical memory. -Memory is a shared resource for all programs. When a block of memory is occupied by one program, it cannot be simultaneously used by other programs. **Therefore, considering memory resources is crucial in designing data structures and algorithms**. For instance, the algorithm's peak memory usage should not exceed the remaining free memory of the system; if there is a lack of contiguous memory blocks, then the data structure chosen must be able to be stored in non-contiguous memory blocks. +Memory is a shared resource for all programs. When a block of memory is occupied by one program, it cannot be simultaneously used by other programs. **Therefore, memory resources are an important consideration in the design of data structures and algorithms**. For instance, the algorithm's peak memory usage should not exceed the remaining free memory of the system; if there is a lack of contiguous memory blocks, then the data structure chosen must be able to be stored in non-contiguous memory blocks. As illustrated in the figure below, **the physical structure reflects the way data is stored in computer memory** and it can be divided into contiguous space storage (arrays) and non-contiguous space storage (linked lists). The two types of physical structures exhibit complementary characteristics in terms of time efficiency and space efficiency.