Verification - Revision history

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2025-08-26T23:07:24Z

‎References

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Tom at 02:05, 2 December 2022

2022-12-02T02:05:12Z

Tom: /* Formal Verification of Software */

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‎Formal Verification of Software

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‎Formal Verification of Software

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‎Formal Verification of Software

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2022-12-02T01:58:39Z

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2022-12-02T01:55:46Z

‎Formal Verification of Software

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2021-09-16T23:27:08Z

‎Formal Verification of Software

@@ Line 10: / Line 10: @@
 * [https://techcrunch.com/2016/05/16/how-can-we-control-intelligent-systems-no-one-fully-understands/ How can we control intelligent systems no one fully understands?] is an article from 2016-05-16 that makes the point the complex systems are never predictable.
 * Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7 pp 13ff. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking. Somehow the idea persists that [[Program Compliance]] could include formal verification, which seems unrealistic in the extreme.
 ==References==
 [[Category: Glossary]]

@@ Line 9: / Line 9: @@
 * [https://cacm.acm.org/magazines/2021/7/253452-formal-software-verification-measures-up/fulltext?mobile=false Formal Software Verification Measures Up] article seems to claim that we will be able to prove that programs will deliver only correct results, "real soon now" in spite of the fact that for most systems humans are not capable of defining what a correct result might be. The book "The Alinement Problem"<ref>Brain Christian, ''The Alinement Problem'' ISBN 978-0393635829</ref> explains in great detail why setting goals for computer systems is not even close to a solution.<blockquote>The disconnect between intention and results―between what mathematician Norbert Wiener described as “the purpose put into the machine” and “the purpose we really desire”―defines the essence of “the alignment problem."</blockquote>
 * [https://techcrunch.com/2016/05/16/how-can-we-control-intelligent-systems-no-one-fully-understands/ How can we control intelligent systems no one fully understands?] is an article from 2016-05-16 that makes the point the complex systems are never predictable.
-* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7 pp 13ff. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking. Somehow the idea persists that code compliance could include formal verification, which seems unrealistic in the extreme.
+* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7 pp 13ff. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking. Somehow the idea persists that [[Program Compliance]] could include formal verification, which seems unrealistic in the extreme.
 ==References==
 [[Category: Glossary]]

@@ Line 9: / Line 9: @@
 * [https://cacm.acm.org/magazines/2021/7/253452-formal-software-verification-measures-up/fulltext?mobile=false Formal Software Verification Measures Up] article seems to claim that we will be able to prove that programs will deliver only correct results, "real soon now" in spite of the fact that for most systems humans are not capable of defining what a correct result might be. The book "The Alinement Problem"<ref>Brain Christian, ''The Alinement Problem'' ISBN 978-0393635829</ref> explains in great detail why setting goals for computer systems is not even close to a solution.<blockquote>The disconnect between intention and results―between what mathematician Norbert Wiener described as “the purpose put into the machine” and “the purpose we really desire”―defines the essence of “the alignment problem."</blockquote>
 * [https://techcrunch.com/2016/05/16/how-can-we-control-intelligent-systems-no-one-fully-understands/ How can we control intelligent systems no one fully understands?] is an article from 2016-05-16 that makes the point the complex systems are never predictable.
-* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7 pp 13ff. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking.
+* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7 pp 13ff. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking. Somehow the idea persists that code compliance could include formal verification, which seems unrealistic in the extreme.
 ==References==
 [[Category: Glossary]]

@@ Line 9: / Line 9: @@
 * [https://cacm.acm.org/magazines/2021/7/253452-formal-software-verification-measures-up/fulltext?mobile=false Formal Software Verification Measures Up] article seems to claim that we will be able to prove that programs will deliver only correct results, "real soon now" in spite of the fact that for most systems humans are not capable of defining what a correct result might be. The book "The Alinement Problem"<ref>Brain Christian, ''The Alinement Problem'' ISBN 978-0393635829</ref> explains in great detail why setting goals for computer systems is not even close to a solution.<blockquote>The disconnect between intention and results―between what mathematician Norbert Wiener described as “the purpose put into the machine” and “the purpose we really desire”―defines the essence of “the alignment problem."</blockquote>
 * [https://techcrunch.com/2016/05/16/how-can-we-control-intelligent-systems-no-one-fully-understands/ How can we control intelligent systems no one fully understands?] is an article from 2016-05-16 that makes the point the complex systems are never predictable.
-* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking.
+* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7 pp 13ff. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking.
 ==References==
 [[Category: Glossary]]

@@ Line 9: / Line 9: @@
 * [https://cacm.acm.org/magazines/2021/7/253452-formal-software-verification-measures-up/fulltext?mobile=false Formal Software Verification Measures Up] article seems to claim that we will be able to prove that programs will deliver only correct results, "real soon now" in spite of the fact that for most systems humans are not capable of defining what a correct result might be. The book "The Alinement Problem"<ref>Brain Christian, ''The Alinement Problem'' ISBN 978-0393635829</ref> explains in great detail why setting goals for computer systems is not even close to a solution.<blockquote>The disconnect between intention and results―between what mathematician Norbert Wiener described as “the purpose put into the machine” and “the purpose we really desire”―defines the essence of “the alignment problem."</blockquote>
 * [https://techcrunch.com/2016/05/16/how-can-we-control-intelligent-systems-no-one-fully-understands/ How can we control intelligent systems no one fully understands?] is an article from 2016-05-16 that makes the point the complex systems are never predictable.
-* Yet academic s are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever model any nature [[Ecosystem]].
+* Yet academics are quite sure that no one should every run a program that produces any result that's part part of its original design<ref>Samual Greengard, "Formal Software Verification Measures up'' '''CACM 64''' no 7. (2021-07)</ref> and made the caim in 2021 that "successfully verifying code hinges on a critical factor: the ability to construct a mathematical model that proves the code is error-free and results in the desired outcome." Which seems to imply that no code could ever predict the outcome of any natural [[Ecosystem]] even over quite short terms, geologically speaking.
 ==References==
 [[Category: Glossary]]