kaichen.org valuation and analysis

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Title Home - Kai Chen’s
Description Kai Chen Home Research Publication Tool People [中文] Professor Kai Chen received his Ph.D. degree in the University of Chinese Academy of Science in 2010;
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WebSite kaichen faviconkaichen.org
Host IP 185.199.111.153
Location -
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kaichen.org Valuation
US$1,583,775
Last updated: 2023-05-13 00:03:29

kaichen.org has Semrush global rank of 6,682,962. kaichen.org has an estimated worth of US$ 1,583,775, based on its estimated Ads revenue. kaichen.org receives approximately 182,744 unique visitors each day. Its web server is located in -, with IP address 185.199.111.153. According to SiteAdvisor, kaichen.org is safe to visit.

Traffic & Worth Estimates
Purchase/Sale Value US$1,583,775
Daily Ads Revenue US$1,462
Monthly Ads Revenue US$43,859
Yearly Ads Revenue US$526,301
Daily Unique Visitors 12,183
Note: All traffic and earnings values are estimates.
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Host Type TTL Data
kaichen.org. A 1800 IP: kaichenorg.github.io.
kaichenorg.github.io. A 3599 IP: 185.199.111.153
kaichenorg.github.io. A 3599 IP: 185.199.110.153
kaichenorg.github.io. A 3599 IP: 185.199.109.153
kaichenorg.github.io. A 3599 IP: 185.199.108.153
kaichen.org. AAAA 1799 IPV6: kaichenorg.github.io.
kaichenorg.github.io. AAAA 3600 IPV6: 2606:50c0:8003::153
kaichenorg.github.io. AAAA 3600 IPV6: 2606:50c0:8000::153
kaichenorg.github.io. AAAA 3600 IPV6: 2606:50c0:8001::153
kaichenorg.github.io. AAAA 3600 IPV6: 2606:50c0:8002::153
kaichen.org. NS 1799 NS Record: kaichenorg.github.io.
kaichen.org. MX 1799 MX Record: kaichenorg.github.io.
kaichen.org. TXT 1800 TXT Record: kaichenorg.github.io.
HtmlToTextCheckTime:2023-05-13 00:03:29
Kai Chen Home Research Publication Tool People [中文] Professor Kai Chen received his Ph.D. degree in the University of Chinese Academy of Science in 2010; then he joined the Chinese Academy of Science in January 2010. He became the Associate Professor in September 2012 and became the full Professor in October 2015. His research interests include software analysis and testing; smartphones and privacy. AURC: Detecting Errors in Program Code and Documentation We present AURC, a static framework for detecting code bugs of incorrect return checks and document defects. We observe that three objects participate in the API invocation, the document, the caller (code that invokes API), and the callee (the source code of API). Mutual corroboration of these three objects boosts the detection of code and documentation errors. We evaluated AURC on ten popular codebases. AURC discovered 529 new bugs and 224 new document defects. Maintainers acknowledge our findings and have accepted 222 code patches
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