2016 French Open – Wheelchair Men's Doubles
Shingo Kunieda and Gordon Reid were the defending champions and successfully defended their title, defeating Michaël Jeremiasz and Stefan Olsson in the final, 6–3, 6–2.
Wheelchair Men's Doubles | |
---|---|
2016 French Open | |
Champions | |
Runners-up | |
Final score | 6–3, 6–2 |
Seeds
Stéphane Houdet / Nicolas Peifer (Semifinals) Shingo Kunieda / Gordon Reid (Champions)
Draw
Key
- Q = Qualifier
- WC = Wild Card
- LL = Lucky Loser
- Alt = Alternate
- SE = Special Exempt
- PR = Protected Ranking
- ITF = ITF entry
- JE = Junior Exempt
- w/o = Walkover
- r = Retired
- d = Defaulted
Finals
Semifinals | Final | ||||||||||||
1 | 4 | 4 | |||||||||||
6 | 6 | ||||||||||||
3 | 2 | ||||||||||||
2 | 6 | 6 | |||||||||||
2 | 3 | ||||||||||||
2 | 6 | 6 | |||||||||||
gollark: It must comfort you to think so.
gollark: > There is burgeoning interest in designing AI-basedsystems to assist humans in designing computing systems,including tools that automatically generate computer code.The most notable of these comes in the form of the first self-described ‘AI pair programmer’, GitHub Copilot, a languagemodel trained over open-source GitHub code. However, codeoften contains bugs—and so, given the vast quantity of unvettedcode that Copilot has processed, it is certain that the languagemodel will have learned from exploitable, buggy code. Thisraises concerns on the security of Copilot’s code contributions.In this work, we systematically investigate the prevalence andconditions that can cause GitHub Copilot to recommend insecurecode. To perform this analysis we prompt Copilot to generatecode in scenarios relevant to high-risk CWEs (e.g. those fromMITRE’s “Top 25” list). We explore Copilot’s performance onthree distinct code generation axes—examining how it performsgiven diversity of weaknesses, diversity of prompts, and diversityof domains. In total, we produce 89 different scenarios forCopilot to complete, producing 1,692 programs. Of these, wefound approximately 40 % to be vulnerable.Index Terms—Cybersecurity, AI, code generation, CWE
gollark: https://arxiv.org/pdf/2108.09293.pdf
gollark: This is probably below basically everywhere's minimum wage.
gollark: (in general)
References
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