reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized ability to abstractly express high-level algorithms decoupled from implementation details, yet generate efficient, specialized code to handle each case at run time. 12.2 Method Ambiguities It is possible = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your

reasoning about types; Julia simply exposes it to the programmer. The Julia compiler is able to generate efficient code in the presence of Union types with a small number of types 1, by generating specialized automatic specialization allows you to write generic algorithms and expect that the compiler will generate efficient, specialized code to handle each case you need. In cases where the number of potential = myfilter(A, kernel, Replicate()) # replicate the edge by default Together, these two methods generate an infinite recursion with A constantly growing bigger. The better design would be to define your