Titlebook: Smart Education and e-Learning 2018; Vladimir L. Uskov,Robert J. Howlett,Ljubo Vlacic Conference proceedings 2019 Springer International P

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Natalya V. Serdyukova,Kirill Potapov wide range of resources, platforms, and execution models. The analysis estimates both lower and upper bounds on the resource usage of a parallel program (without executing it) as functions on input data sizes. In addition, it also infers other meaningful information to better exploit and assess the

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Natalia A. Serdyukova,Vladimir I. Serdyukov,Vladimir A. Slepovet Programming (ASP) and the well-founded semantics (WFS). In particular, we give new iterated fixpoint characterizations of answer sets as well as the WFS via dual programs. We also discuss some applications of non-stratified co-LPs to program transformation such as partial deduction, and a proof p

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Michele T. Cole,Daniel J. Shelley,Louis B. Swartzet Programming (ASP) and the well-founded semantics (WFS). In particular, we give new iterated fixpoint characterizations of answer sets as well as the WFS via dual programs. We also discuss some applications of non-stratified co-LPs to program transformation such as partial deduction, and a proof p

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Leticia Rocha Machado,Jozelina Mendes,Tássia Priscila Grande,Larissa Justin,Patricia Beharet Programming (ASP) and the well-founded semantics (WFS). In particular, we give new iterated fixpoint characterizations of answer sets as well as the WFS via dual programs. We also discuss some applications of non-stratified co-LPs to program transformation such as partial deduction, and a proof p

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Winson C. C. Lee,Gursel Aliciet Programming (ASP) and the well-founded semantics (WFS). In particular, we give new iterated fixpoint characterizations of answer sets as well as the WFS via dual programs. We also discuss some applications of non-stratified co-LPs to program transformation such as partial deduction, and a proof p

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