• CI . . . . 5 matches
       = CI, [CITP] 개념도 =
       = CI의 이점 =
       2008년 JOLT 상을 수상한 책인 Continuous Integration: Improving Software Quality and Reducing Risk 에서...
       = 성공적인 CI 수행의 요건 =
       = [CI 도구] =
• 국가코드 . . . . 5 matches
       CÔTE D'IVOIRE CI
       HOLY SEE (VATICAN CITY STATE) VA
       SAINT LUCIA LC
       SAO TOME AND PRINCIPE ST
       VATICAN CITY STATE see HOLY SEE
• (번역)PleaseStopCallingDatabasesCPOrAP . . . . 2 matches
       Instead, we should use more precise terminology to reason about our trade-offs.
       If you want to refer to CAP as a theorem (as opposed to a vague hand-wavy concept in your database’s marketing materials), you have to be precise.
       Mathematics requires precision.
        * Consistency in CAP actually means linearizability, which is a very specific (and very strong) notion of consistency.
        In particular it has got nothing to do with the C in ACID, even though that C also stands for “consistency”.
        특히 ACID에서 C와는 전혀 관련이 없습니다.
        It’s not sufficient for some node to be able to handle the request: any non-failing node needs to be able to handle it.
       Also note that the CAP theorem doesn’t just describe any old system, but a very specific model of a system:
       If your use of words matches the precise definitions of the proof, then the CAP theorem applies to you.
       Just after the final score is announced, Alice refreshes the page, sees the winner announced, and excitedly tells Bob about it.
       This is a fairly expensive guarantee to provide, because it requires a lot of coordination. Even the CPU in your computer doesn’t provide linearizable access to your local RAM! On modern CPUs, you need to use an explicit memory barrier instruction in order to get linearizability. And even testing whether a system provides linearizability is tricky.
• CI도구 . . . . 2 matches
       [CITP]구현에 들어가는 도구들
        * [CI] 서버: CruiseControl, [Hudson]
• jEdit . . . . 2 matches
       options.pmd.rules.SuspiciousHashcodeMethodName=true
       options.pmd.rules.EmptyStaticInitializer=true
       encoding.opt-out.x-ISCII91=true
       encoding.opt-out.US-ASCII=true
       xml.cache.public-id.14=-//NetBeans//DTD Module Automatic Dependencies 1.0//EN
       encoding.opt-out.x-MacIceland=true
       options.pmd.rules.ExplicitCallToFinalize=true
       options.pmd.rules.SuspiciousOctalEscapeRule=true
       options.pmd.rules.NonStaticInitializer=true
• 소스품질관리도구 . . . . 2 matches
       참고 : [CI], [CI 도구], [http://jbrugge.com/glean/tools.html Glean:Tools]
• CITP . . . . 1 match
       참조 : [CI]
• CopyingOffsetsOfAConsumerGroupToAnotherConsumerGroupInKafka0.10WithPythonScript . . . . 1 match
       Consumer group `grp1` is rebalancing.
        * STOP above script(poll-without-commit.py) with Ctrl+C and WAIT for grp2 to go into REBALANCING state.
       Consumer group `grp2` is rebalancing.
• CruiseControl . . . . 1 match
       [CI 도구], 빌드 프로세스 자동화 도구
• Hudson . . . . 1 match
       [CI도구] >
       http://hudson-ci.org/
• LinuxH/w정보알아내기 . . . . 1 match
       PCI정보 : cat /proc/pci
• OurSoftwareDependencyProblem . . . . 1 match
       #keywords translation, dependencies
       developers reuse software written by others every day, in the form of software dependencies, and the situation goes mostly unexamined.
       My own background includes a decade of working with Google’s internal source code system, which treats software dependencies as a first-class concept,1 and also developing support for dependencies in the Go programming language.2
       Software dependencies carry with them serious risks that are too often overlooked.
       The shift to easy, fine-grained software reuse has happened so quickly that we do not yet understand the best practices for choosing and using dependencies effectively, or even for deciding when they are appropriate and when not.
       designing, writing, testing, debugging, and maintaining a specific unit of code.
       Taking on externally-written dependencies is an old practice:
       Before dependency managers, publishing an eight-line code library would have been unthinkable: too much overhead for too little benefit. But NPM has driven the overhead approximately to zero, with the result that nearly-trivial functionality can be packaged and reused. In late January 2019, the escape-string-regexp package is explicitly depended upon by almost a thousand other NPM packages, not to mention all the packages developers write for their own use and don’t share.
       Decades ago, most developers already trusted others to write software they depended on, such as operating systems and compilers. That software was bought from known sources, often with some kind of support agreement. There was still a potential for bugs or outright mischief,3 but at least we knew who we were dealing with and usually had commercial or legal recourses available.
       The phenomenon of open-source software, distributed at no cost over the internet, has displaced many of those earlier software purchases. When reuse was difficult, there were fewer projects publishing reusable code packages. Even though their licenses typically disclaimed, among other things, any “implied warranties of merchantability and fitness for a particular purpose,” the projects built up well-known reputations that often factored heavily into people’s decisions about which to use. The commercial and legal support for trusting our software sources was replaced by reputational support. Many common early packages still enjoy good reputations: consider BLAS (published 1979), Netlib (1987), libjpeg (1991), LAPACK (1992), HP STL (1994), and zlib (1995).
       Dependency managers have scaled this open-source code reuse model down: now, developers can share code at the granularity of individual functions of tens of lines. This is a major technical accomplishment. There are myriad available packages, and writing code can involve such a large number of them, but the commercial, legal, and reputational support mechanisms for trusting the code have not carried over. We are trusting more code with less justification for doing so.
       No matter what the expected cost, experiences with larger dependencies suggest some approaches for estimating and reducing the risks of adding a software dependency. It is likely that better tooling is needed to help reduce the costs of these approaches, much as dependency managers have focused to date on reducing the costs of download and installation.
       A basic inspection can give you a sense of how likely you are to run into problems trying to use this code. If the inspection reveals likely minor problems, you can take steps to prepare for or maybe avoid them. If the inspection reveals major problems, it may be best not to use the package: maybe you’ll find a more suitable one, or maybe you need to develop one yourself. Remember that open-source packages are published by their authors in the hope that they will be useful but with no guarantee of usability or support. In the middle of a production outage, you’ll be the one debugging it. As the original GNU General Public License warned, “The entire risk as to the quality and performance of the program is with you. Should the program prove defective, you assume the cost of all necessary servicing, repair or correction.”4
       The rest of this section outlines some considerations when inspecting a package and deciding whether to depend on it.
       Is the code well-written? Read some of it. Does it look like the authors have been careful, conscientious, and consistent? Does it look like code you’d want to debug? You may need to.
       Keep an open mind to development practices you may not be familiar with. For example, the SQLite library ships as a single 200,000-line C source file and a single 11,000-line header, the “amalgamation.” The sheer size of these files should raise an initial red flag, but closer investigation would turn up the actual development source code, a traditional file tree with over a hundred C source files, tests, and support scripts. It turns out that the single-file distribution is built automatically from the original sources and is easier for end users, especially those without dependency managers. (The compiled code also runs faster, because the compiler can see more optimization opportunities.)
       Find the package’s issue tracker. Are there many open bug reports? How long have they been open? Are there many fixed bugs? Have any bugs been fixed recently? If you see lots of open issues about what look like real bugs, especially if they have been open for a long time, that’s not a good sign. On the other hand, if the closed issues show that bugs are rarely found and promptly fixed, that’s great.
       Will you be processing untrusted inputs with the package? If so, does it seem to be robust against malicious inputs? Does it have a history of security problems listed in the National Vulnerability Database (NVD)?11
       For example, when Jeff Dean and I started work on Google Code Search12—grep over public source code—in 2006, the popular PCRE regular expression library seemed like an obvious choice. In an early discussion with Google’s security team, however, we learned that PCRE had a history of problems like buffer overflows, especially in its parser. We could have learned the same by searching for PCRE in the NVD. That discovery didn’t immediately cause us to abandon PCRE, but it did make us think more carefully about testing and isolation.
       Is the code properly licensed? Does it have a license at all? Is the license acceptable for your project or company? A surprising fraction of projects on GitHub have no clear license. Your project or company may impose further restrictions on the allowed licenses of dependencies. For example, Google disallows the use of code licensed under AGPL-like licenses (too onerous) as well as WTFPL-like licenses (too vague).13
• ProcMailSample1 . . . . 1 match
       * ^To:.*undisclosed-recipients:;
       * ^Subject:.*[Ss]ummer.*[Ss]pecials
       * ^Subject:.*A (new|funny|nice|humor|excite|good|powerful|WinXP|(IE 6.0)) (game|tool|website|patch)$
       # CIH 바이러스
       * ^Subject: Check ur friends Circle$
       * ^Subject: excite$
• SRE . . . . 1 match
       ["CIA triad"]
• ci . . . . 1 match
       [CI]
• jcifs . . . . 1 match
       * jcifs를 이용해 Windows 파일공유서버에서 파일 읽어와 콘솔에 뿌리기 예제
       import jcifs.smb.NtlmPasswordAuthentication;
       import jcifs.smb.SmbFile;
       import jcifs.smb.SmbFileInputStream;
       public class JCIFS_Test {
• 캐릭터와인코딩 . . . . 1 match
       [ASCII 코드]
• 코틀린마이크로서비스개발-후안안토니오 . . . . 1 match
        - Spring Cloud Architecture: Config Server, Service 탐색, Load Balancer, Gateway, Circuit Breaker
       12.5. CI/CD 처리

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