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In Sects. 2 and 3, we present the algorithm and we prove its correctness and complexity.
The correctness and complexity of the DNA algorithm are discussed and proved.
ACL, RAG, ENC, WSM, and SWS worked on the model proposal and the design, correctness, and complexity of the algorithms.
Correctness and complexity of the proposal are empirically validated by means of the development of case studies and a comparison with the Alloy analyzer.
Correctness and complexity proofs are provided and they show that our Dynamic-DSDP performs better, from a communication complexity viewpoint, than the existing protocols.
While presenting the formalisms and algorithm, we will analyze the correctness and complexity of the algorithm, and demonstrate the proposed method with two benchmark CSPs, i.e., n-queen problems and coloring problems.
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Then, correctness proofs and complexity measures are designed for the various levels of abstraction.
The correctness and computational complexity of the algorithm are proved.
We analyze and prove the correctness and time complexity of the algorithms in the proposed scheme.
The proposed scheme is presented in Section 4. We analyze the correctness and time complexity of the scheme, and then evaluate its performance in Section 5. Finally, we conclude the paper and discuss our future work in Section 6.
One of the most promising approaches to this aim is based on the use of lambda-calculus as paradigmatic programming language and the design of type assignment systems for lambda-terms, where types guarantee both the functional correctness and the complexity bound.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com