Dynamically typed languages

Dynamically typed languages such as Python and Ruby have experienced a rapid grown in popularity in recent times. However, there is much confusion as to what makes these languages interesting relative to statically typed languages, and little knowledge of their rich history. In this chapter I explore the general topic of dynamically typed languages, how they differ from statically typed languages, their history, and their defining features

A Concurrent Language with a Uniform Treatment of Regions and Locks

A challenge for programming language research is to design and implement multi-threaded low-level languages providing static guarantees for memory safety and freedom from data races. Towards this goal, we present a concurrent language employing safe region-based memory management and hierarchical locking of regions. Both regions and locks are treated uniformly, and the language supports ownership transfer, early deallocation of regions and early release of locks in a safe manner

Linguistic Reflection in Java

Reflective systems allow their own structures to be altered from within. Here we are concerned with a style of reflection, called linguistic reflection, which is the ability of a running program to generate new program fragments and to integrate these into its own execution. In particular we describe how this kind of reflection may be provided in the compiler-based, strongly typed object-oriented programming language Java. The advantages of the programming technique include attaining high levels of genericity and accommodating system evolution. These advantages are illustrated by an example taken from persistent programming which shows how linguistic reflection allows functionality (program code) to be generated on demand (Just-In-Time) from a generic specification and integrated into the evolving running program. The technique is evaluated against alternative implementation approaches with respect to efficiency, safety and ease of use.Comment: 25 pages. Source code for examples at http://www-ppg.dcs.st-and.ac.uk/Java/ReflectionExample/ Dynamic compilation package at http://www-ppg.dcs.st-and.ac.uk/Java/DynamicCompilation

In the Age of Web: Typed Functional-First Programming Revisited

Most programming languages were designed before the age of web. This matters because the web changes many assumptions that typed functional language designers take for granted. For example, programs do not run in a closed world, but must instead interact with (changing and likely unreliable) services and data sources, communication is often asynchronous or event-driven, and programs need to interoperate with untyped environments. In this paper, we present how the F# language and libraries face the challenges posed by the web. Technically, this comprises using type providers for integration with external information sources and for integration with untyped programming environments, using lightweight meta-programming for targeting JavaScript and computation expressions for writing asynchronous code. In this inquiry, the holistic perspective is more important than each of the features in isolation. We use a practical case study as a starting point and look at how F# language and libraries approach the challenges posed by the web. The specific lessons learned are perhaps less interesting than our attempt to uncover hidden assumptions that no longer hold in the age of web.Comment: In Proceedings ML/OCaml 2014, arXiv:1512.0143

Dynamically typed languages.

Dynamically typed languages such as Python and Ruby have experienced a rapid grown in popularity in recent times. However, there is much confusion as to what makes these languages interesting relative to statically typed languages, and little knowledge of their rich history. In this chapter I explore the general topic of dynamically typed languages, how they differ from statically typed languages, their history, and their defining features

Safer typing of complex API usage through Java generics

When several incompatible implementations of a single API are in use in a Java program, the danger exists that instances from different implementations may inadvertently be mixed, leading to errors. In this paper we show how to use generics to prevent such mixing. The core idea of the approach is to add a type parameter to the interfaces of the API, and tie the classes that make up an implementation to a unique choice of type parameter. In this way methods of the API can only be invoked with arguments that belong to the same implementation. We show that the presence of a type parameter in the interfaces does not violate the principle of interface-based programming: clients can still completely abstract over the choice of implementation. In addition, we demonstrate how code can be reused between different implementations, how implementations can be defined as extensions of other implementations, and how different implementations may be mixed in a controlled and safe manner. To explore the feasibility of the approach, gauge its usability, and identify any issues that may crop up in practical usage, we have refactored a fairly large existing API-based application suite, and we report on the experience gained in the process