Code Quality for Generative AI

Supercharge innovation with Code Quality + GenAI

No matter whoโ€™s writing it โ€“ generative AI or humans โ€“ Code Quality is the standard for secure, reliable, and maintainable software

๋ฐ๋ชจ ์š”์ฒญํ•˜๊ธฐ

700๋งŒ ๋ช… ์ด์ƒ์˜ ๊ฐœ๋ฐœ์ž์™€ 40๋งŒ ๋ช…์˜ ์‹ ๋ขฐ๋ฅผ ๋ฐ›์Œ์กฐ์ง

Mercedes Benz
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Nvidia
U.S. Army
Santander
Costco

maximize the advantages of code generated by AI with Sonar

Generative AI produces code based on training data that includes all the same snags as human-created code.ย With AI-generated code, a higher volume of code will be produced at a faster speed, and it is important to know the potential problem areas and maintain a focus on quality.ย With leading Code Quality solutions โ€“ SonarQube Server, SonarQube Cloud, and SonarQube for IDE -ย you can avoid preventable code issues by writing Code Quality from the start.


ai creating code
SOLUTION

Code assisted by AI, quality assured by Sonar

Sonarโ€™s solutions consisting of SonarQube Server and SonarQube Cloud integrated into the Continuous Integration (CI) pipeline alongside SonarQube for IDE in the IDE, unlock the full potential of AI-generated code that is consistent, intentional, adaptable, and responsible. Using Sonar, development teams can minimize risk, ensure code quality, and derive more value from code created by both AI and humans in a predictable and sustainable way. Sonarโ€™s solutions offer the best path toward adopting AI code generation.

SonarQube Cloud

ํด๋ผ์šฐ๋“œ ๊ธฐ๋ฐ˜ DevOps๋ฅผ ์œ„ํ•ด

SonarQube Cloud๋ฅผ ํด๋ผ์šฐ๋“œ DevOps ํ”Œ๋žซํผ๊ณผ ํ†ตํ•ฉํ•˜์—ฌ ์ฝ”๋“œ ํ’ˆ์งˆ๊ณผ ์ฝ”๋“œ ๋ณด์•ˆ์„ ๋ณด์žฅํ•˜๊ณ , ๋†’์€ ํ‘œ์ค€์„ ์œ ์ง€ํ•˜๊ณ , ์ฝ”๋“œ๋ฅผ ์ทจ์•ฝ์ ์œผ๋กœ๋ถ€ํ„ฐ ๋ณดํ˜ธํ•˜์„ธ์š”.

SonarQube Cloud๋ฅผ ์‚ฌ์šฉํ•ด ๋ณด์„ธ์š”
SonarQube Server

์ตœ๊ณ ์˜ ์ œ์–ด๋ฅผ ์œ„ํ•œ ์ž์ฒด ๊ด€๋ฆฌ

ํ”„๋กœ๋•์…˜ ๋‹จ๊ณ„์— ๋“ค์–ด๊ฐ€๊ธฐ ์ „์— ์ฝ”๋“œ ํ’ˆ์งˆ๊ณผ ๋ณด์•ˆ์ด ๋†’์€ ๊ธฐ์ค€์„ ์ถฉ์กฑํ•˜๋Š”์ง€ ์กฐ๊ธฐ์— ํ™•์ธํ•˜์„ธ์š”. ์—”ํ„ฐํ”„๋ผ์ด์ฆˆ DevOps ํ™˜๊ฒฝ์— ํ†ตํ•ฉ๋˜์–ด ํ˜„์žฌ ์›Œํฌํ”Œ๋กœ์šฐ ๋‚ด์—์„œ ์ฝ”๋”ฉ ๋ฌธ์ œ๋ฅผ ์‰ฝ๊ฒŒ ์ฐพ์•„ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

IDE์šฉ SonarQube

๊ฐœ๋ฐœ์ž ํ๋ฆ„ ๋‚ด์—์„œ

์ฝ”๋”ฉ ์‹ค๋ ฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ณ  ๋ฌธ์ œ๋ฅผ ์กฐ๊ธฐ์— ๋ฐœ๊ฒฌํ•˜์„ธ์š”. SonarQube for IDE๋Š” ๋ฆฐํŒ…์„ ํ•œ ๋‹จ๊ณ„ ๋” ๋ฐœ์ „์‹œ์ผœ ์–ด๋–ค ์–ธ์–ด๋‚˜ ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜๋“  ์ฝ”๋”ฉ ์ค‘์— ๋ฌธ์ œ๋ฅผ ์˜ˆ๋ฐฉํ•  ์ˆ˜ ์žˆ๋„๋ก ์ง€์›ํ•ฉ๋‹ˆ๋‹ค.

3000์–ต

๋งค์ผ ๋ถ„์„๋˜๋Š” ์ฝ”๋“œ ์ค„

30+

ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด, ํ”„๋ ˆ์ž„์›Œํฌ ๋ฐ IaC ๊ธฐ์ˆ 

#1

์‚ฌ์šฉ์ž ๋งŒ์กฑ์„ ์œ„ํ•ด (G2)

10์–ต+

๋„์ปค ๋‹ค์šด๋กœ๋“œ

Shivagangadhara J image

"SonarQube๋ฅผ ๊ตฌํ˜„ํ•œ ์ดํ›„ ์šฐ๋ฆฌ ์กฐ์ง์—์„œ๋Š” ์ค‘์š” ์ฝ”๋“œ ๋ฌธ์ œ๊ฐ€ 30% ๊ฐ์†Œํ•˜๊ณ , ์ฝ”๋“œ ํ’ˆ์งˆ ์ ์ˆ˜๊ฐ€ 25% ์ฆ๊ฐ€ํ–ˆ์œผ๋ฉฐ, ์ฝ”๋“œ ์ทจ์•ฝ์„ฑ์ด 20% ๊ฐ์†Œํ•˜๋Š” ์„ฑ๊ณผ๋ฅผ ๊ฑฐ๋‘์—ˆ์Šต๋‹ˆ๋‹ค.โ€

Shivagangadhara J, ํด๋ผ์šฐ๋“œ ์„ค๊ณ„์ž

Shivagangadhara J image

Shivagangadhara J, ํด๋ผ์šฐ๋“œ ์„ค๊ณ„์ž

"SonarQube๋ฅผ ๊ตฌํ˜„ํ•œ ์ดํ›„ ์šฐ๋ฆฌ ์กฐ์ง์—์„œ๋Š” ์ค‘์š” ์ฝ”๋“œ ๋ฌธ์ œ๊ฐ€ 30% ๊ฐ์†Œํ•˜๊ณ , ์ฝ”๋“œ ํ’ˆ์งˆ ์ ์ˆ˜๊ฐ€ 25% ์ฆ๊ฐ€ํ–ˆ์œผ๋ฉฐ, ์ฝ”๋“œ ์ทจ์•ฝ์„ฑ์ด 20% ๊ฐ์†Œํ•˜๋Š” ์„ฑ๊ณผ๋ฅผ ๊ฑฐ๋‘์—ˆ์Šต๋‹ˆ๋‹ค.โ€

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