1970 U.S. Professional Indoor – Doubles
Tom Okker and Marty Riessen were the defending champions, but lost in the second round this year.
Doubles | |
---|---|
1970 U.S. Professional Indoor | |
Champions | |
Runners-up | |
Final score | 6–4, 6–3 |
Ilie Năstase and Ion Ţiriac successfully defended their title, defeating Arthur Ashe and Dennis Ralston 6–4, 6–3 in the final.
Seeds
John Newcombe / Tony Roche (Second Round) Tom Okker / Marty Riessen (Second Round) Robert Lutz / Stan Smith (Second Round) Ken Rosewall / Fred Stolle (First Round)
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 | 3 | ||||||||||||
6 | 6 | ||||||||||||
6 | 6 | ||||||||||||
4 | 3 | ||||||||||||
7 | 4 | 6 | |||||||||||
5 | 6 | 3 | |||||||||||
Top Half
First Round | Second Round | Quarterfinals | Semifinals | ||||||||||||||||||||||||
2 | 4 | 6 | 4 | ||||||||||||||||||||||||
6 | 2 | 5 | |||||||||||||||||||||||||
6 | 5 | 6 | |||||||||||||||||||||||||
2 | 7 | 1 | |||||||||||||||||||||||||
4 | 6 | 5 | |||||||||||||||||||||||||
6 | 4 | 3 | |||||||||||||||||||||||||
1 | 3 | ||||||||||||||||||||||||||
6 | 6 | 6 | 6 | ||||||||||||||||||||||||
4 | 4 | 6 | 4 | 5 | |||||||||||||||||||||||
6 | 2 | 6 | 3 | 6 | 4 | ||||||||||||||||||||||
2 | 6 | 4 | 6 | 4 | 6 | ||||||||||||||||||||||
6 | 6 | 3 | 6 | 4 | |||||||||||||||||||||||
1 | 1 | 5 | 7 | 2 | |||||||||||||||||||||||
7 | 5 | 5 | 7 | 5 | 5 | ||||||||||||||||||||||
4 | 5 | 7 | 3 |
Bottom Half
First Round | Second Round | Quarterfinals | Semifinals | ||||||||||||||||||||||||
3 | 6 | 6 | |||||||||||||||||||||||||
2 | 1 | 3 | 4 | 3 | |||||||||||||||||||||||
7 | 6 | 6 | 6 | ||||||||||||||||||||||||
5 | 3 | 7 | 6 | ||||||||||||||||||||||||
4 | 6 | 5 | 5 | 4 | |||||||||||||||||||||||
6 | 3 | 3 | 1 | 4 | |||||||||||||||||||||||
6 | 6 | ||||||||||||||||||||||||||
7 | 4 | 6 | |||||||||||||||||||||||||
5 | 6 | 3 | |||||||||||||||||||||||||
5 | 5 | ||||||||||||||||||||||||||
7 | 7 | ||||||||||||||||||||||||||
6 | 5 | 6 | |||||||||||||||||||||||||
3 | 7 | 3 | |||||||||||||||||||||||||
7 | 3 | 5 | |||||||||||||||||||||||||
1 | 5 | 6 | 4 | ||||||||||||||||||||||||
gollark: As if that's possible.
gollark: Fearsome.
gollark: I might have to release apioforms from the beecloud.
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
References
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