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This repository has been archived by the owner on Jul 16, 2023. It is now read-only.
❌ - Complexidade de Programação (programming complexity)
✔ - Tamanho da serialização (serialization size)
✔ - Velocidade de serialização (serialization speed)
✔ - Velocidade de desserialização (deserialization speed)
Método:
✔ - Várias repetições (registar o numero)
✔ - Calcular a Média
✔ - Calcular o Desvio-padrao
XML comprimido com Gzip (XML compressed with Gzip)
Parametros:
❌ - Complexidade de Programação (programming complexity)
✔ - Tamanho da serialização (serialization size)
✔ - Velocidade de serialização (serialization speed)
✔ - Velocidade de desserialização (deserialization speed)
Método:
✔ - Várias repetições (registar o numero)
✔ - Calcular a Média
✔ - Calcular o Desvio-padrao
Google Protocol Buffers
Parametros:
❌ - Complexidade de Programação (programming complexity)
✔ - Tamanho da serialização (serialization size)
✔ - Velocidade de serialização (serialization speed)
✔ - Velocidade de desserialização (deserialization speed)
Método:
✔ - Várias repetições (registar o numero)
✔ - Calcular a Média
✔ - Calcular o Desvio-padrao
Condições das experiências
❌ - Características do PC
❌ - Tecnologias e biblioteca utilizadas (registar versões)
❌ - Incluir a Estrutura de Dados (Apenas Código, sem sets e gets)
Notas:
✔ - Students should define a common data structure that they will use for the comparisons (Classe abstrata)
✔ - They should also try to use similar code as much as possible for the text and binary formats, to improve fairness.
✔ - Students should take notice of the time it takes to initialize data structures in the Protocol Buffers and separate this time from serialization/deserialization.
✔ - Students should add data structures and the points of code where they measure times.
❌ - The report should include a short description of the data representation formats that students should use to support a brief critical discussion of results, e.g., why are Protocol Buffers faster than XML.
❓ - Grades will be based on the quality of the report: how do students describe the data representation formats, the experiment, presentation, and discussion of results; how careful were they while doing the experiments; and how many experiments did they run, to cover the different behaviors of the technologies. Be careful about the way the report looks.
❓ - Some Common Errors: Figures without numbers; Too little text alongside the plots;
❓ - Some Common Errors: No analysis of the plots (this should go beyond repeating what is in the plots). A true explanation of what is in the plots should be given if possible. For example, in some cases, text-based representation was good for small data and bad for larger data. Why?