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- dirty-code · GitHub Topics · GitHub
Dirty code, use for tutorial refactoring design-patterns solid-principles dirty-code code-cleaning code-standards Updated Mar 15, 2019; Java; Andrey-Lomakin exp
- What is Dirty Code? - The creator answers : u DirtyCodeIO - Reddit
Dirty Code is to enable us to express our dirty side shamelessly in a fun and easy way, and connect us with others who feel the same I want to celebrate our diverse sexuality I purposely did not include labels like "gay" or "bi " At Dirty Code we just care about what we have and what we like No shame All acceptance Gyorgy Szucs, the developer
- [65] Erfahrungen mit dirtycode. io? : r GayGermany - Reddit
Ihr kennt sicher die Website dirtycode io Dort kann man anhand von gezeichneten Symbolen den eigenen Pimmel beschreiben
- Clean vs Dirty Code - GitHub
By examining these examples of clean and dirty code, the results were a lot more clear for the Swift implementation, with the clean code implmementation being consistently better Regarding Ionic, the same cannot be said A quick analysis of the implementation showed me that the clean code is mostly faster than dirty code, but this is not a rule
- dirtycow dirty. c at master · firefart dirtycow - GitHub
Dirty Cow exploit - CVE-2016-5195 Contribute to firefart dirtycow development by creating an account on GitHub
- ELI5: The difference between clean and dirty code? : r . . . - Reddit
Some examples of things that make code "dirty": "Magic numbers" The appearance of numbers throughout the code when it's unclear why the number is there or what it means It's better to assign the number to a constant so that it has a symbolic name Deep nesting When there are several levels of loops and conditionals, this suggests that the
- dirty-code · GitHub Topics · GitHub
Add a description, image, and links to the dirty-code topic page so that developers can more easily learn about it Curate this topic Add this topic to your repo
- DIRTY: Augmenting Decompiler Output with Learned Variable . . . - GitHub
├── dirty │ └── utils │ ├── case_study py # Generate results for Table 3 and Table 6 in the paper │ ├── code_processing py # Code canonicalization such as converting literals │ ├── compute_mi py # Compute the mutual information between variables and types as a proof-of-concept for MT │ ├── dataset
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