Titlebook: Conversations About Challenges in Computing; Are Magnus Bruaset,Aslak Tveito Book 2013 Springer International Publishing Switzerland 2013

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,Variation Totale D’une Fonction,ed that question in the context of machine learning and fault detection and Paola Inverardi talked about it in the context of software architecture. While Shepperd looked at reliability from the viewpoint of the software producer, Inverardi argued that the digital world is already moving to a new pa

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https://doi.org/10.1007/BFb0066380cially in the context of privacy, they can’t actually verbalize what they want. They simply know it when they have it. Computer programs, on the other hand, are inherently logical. They are (at least traditionally) based on concepts of Boolean logic. If condition A holds, the program takes action B.

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Are Magnus Bruaset,Aslak TveitoA collection of informal interviews with leading researchers in communication systems, computational sciences, and software engineering.Gives the state of the art plus outlooks to the future.Interview

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Variation Totale d‘une FonctionThe core hypothesis in Magne J?rgensen’s research is that we have a naive view of our own rationality, which goes a long way to explaining why major IT projects take on average 30 to 40 per cent longer than estimated to develop. What lies at the root of this over-optimism?

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A Caring CriticThe core hypothesis in Magne J?rgensen’s research is that we have a naive view of our own rationality, which goes a long way to explaining why major IT projects take on average 30 to 40 per cent longer than estimated to develop. What lies at the root of this over-optimism?

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An introduction to Nevanlinna theory,s in the results that suggest how the software may be flawed. It is really doing the same thing a human would do – learning from the past to predict the future – but a computer can try many more combinations and can detect more deeply hidden patterns than a human can.

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Harmonizing the Babel of Voicess in the results that suggest how the software may be flawed. It is really doing the same thing a human would do – learning from the past to predict the future – but a computer can try many more combinations and can detect more deeply hidden patterns than a human can.

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