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Translate all code to English (#1836)

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* Review the EN heading format.

* Fix pythontutor headings.

* Fix pythontutor headings.

* bug fixes

* Fix headings in **/summary.md

* Revisit the CN-to-EN translation for Python code using Claude-4.5

* Revisit the CN-to-EN translation for Java code using Claude-4.5

* Revisit the CN-to-EN translation for Cpp code using Claude-4.5.

* Fix the dictionary.

* Fix cpp code translation for the multipart strings.

* Translate Go code to English.

* Update workflows to test EN code.

* Add EN translation for C.

* Add EN translation for CSharp.

* Add EN translation for Swift.

* Trigger the CI check.

* Revert.

* Update en/hash_map.md

* Add the EN version of Dart code.

* Add the EN version of Kotlin code.

* Add missing code files.

* Add the EN version of JavaScript code.

* Add the EN version of TypeScript code.

* Fix the workflows.

* Add the EN version of Ruby code.

* Add the EN version of Rust code.

* Update the CI check for the English version  code.

* Update Python CI check.

* Fix cmakelists for en/C code.

* Fix Ruby comments
This commit is contained in:
Yudong Jin
2025-12-31 07:44:52 +08:00
committed by GitHub
parent 45e1295241
commit 2778a6f9c7
1284 changed files with 71557 additions and 3275 deletions
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en/docs/chapter_dynamic_programming/dp_problem_features.md
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@@ -1,4 +1,4 @@
# Characteristics of dynamic programming problems
# Characteristics of Dynamic Programming Problems
In the previous section, we learned how dynamic programming solves the original problem by decomposing it into subproblems. In fact, subproblem decomposition is a general algorithmic approach, with different emphases in divide and conquer, dynamic programming, and backtracking.
@@ -8,7 +8,7 @@ In the previous section, we learned how dynamic programming solves the original
In fact, dynamic programming is commonly used to solve optimization problems, which not only contain overlapping subproblems but also have two other major characteristics: optimal substructure and no aftereffects.
## Optimal substructure
## Optimal Substructure
We make a slight modification to the stair climbing problem to make it more suitable for demonstrating the concept of optimal substructure.
@@ -48,7 +48,7 @@ This problem can also be space-optimized, compressing from one dimension to zero
[file]{min_cost_climbing_stairs_dp}-[class]{}-[func]{min_cost_climbing_stairs_dp_comp}
```
## No aftereffects
## No Aftereffects
No aftereffects is one of the important characteristics that enable dynamic programming to solve problems effectively. Its definition is: **given a certain state, its future development is only related to the current state and has nothing to do with all past states**.