Static and dynamic type systems have well-known strengths and weaknesses. In previous work we developed a gradual type system for a functional calculus named λ→. Gradual typing provides the benefits of both static and dynamic checking in a single language by allowing the programmer to control whether a portion of the program is type checked at compile-time or run-time by adding or removing type...

With the steady development of the computing tools, we attended last three decades a considerable increase of the quantity of data stored in databases. So, extracting knowledge from this data is of paramount importance. Data mining is becoming an inescapable tool to reach this goal. Association rule extraction is one of the important tasks in data mining. This powerful technique has a wide rang...

Gradual Ownership Types are a framework allowing programs to be partially annotated with ownership types, while providing the same encapsulation guarantees. The formalism provides a static guarantee of the desired encapsulation property for fully annotated programs, and dynamic guarantees for partially annotated programs via dynamic checks inserted by the compiler. This enables a smooth migrati...

Gradual type systems offer a smooth continuum between static and dynamic typing by permitting the free mixture of typed and untyped code. The runtime systems for these languages—and other languages with hybrid type checking—typically enforce function types by dynamically generating function proxies. This approach can result in unbounded growth in the number of proxies, however, which drasticall...

Problem and motivation. A static type system can be an extremely powerful tool for a programmer, providing early error detection, and offering strong compile-time guarantees on the behavior of a program. However, compared to dynamic typing, static typing often comes at the expense of development speed and flexibility, as statically-typed code might be more difficult to adapt to changing require...