Programming language abstractions for mobile code

Scala is a general-purpose programming language developed at EPFL. It combines the most important concepts found in object-oriented and functional languages. Scala is a statically typed language; in particular it features an advanced type system and supports local type inference. Furthermore it integrates well with the Java and .net platforms: their libraries are accessible without glue code and the Scala compiler generates code for both execution environments. The Scala programming language has several features that make it desirable as a language for distributed application programming. In particular, it supports first-class functions which are useful in relation with the notions of distributed scope and code mobility. In that context, the missing support for run-time types is one important drawback of the Java run-time environment as a target platform. This thesis focuses on the realisation of a new concept combining essential notions from the functional and distributed programming and implying the extension of the notion of lexical scoping to the distributed context. In short, we claim that the notion of lambda abstraction provides an elegant way for dealing with the dynamic rebinding of local references in a distributed execution environment. The key ideas exposed in this research work have been implemented in our Scala compiler. This helped us to evaluate the used techniques, in particular their impact on the reliability and the performance of distributed programs. So far, most research works related to the present subject have focused on functional programming languages, in particular on the ML language family.

Object-oriented pattern matching

Burak Emir

Pattern matching is a programming language construct considered essential in functional programming. Its purpose is to inspect and decompose data. Instead, object-oriented programming languages do not have a dedicated construct for this purpose. A possible reason for this is that pattern matching is useful when data is defined separately from operations on the data – a scenario that clashes with the object-oriented motto of grouping data and operations. However, programmers are frequently confronted with situations where there is no alternative to expressing data and operations separately – because most data is neither stored in nor does it originate from an object-oriented context. Consequently, object-oriented programmers, too, are in need for elegant and concise solutions to the problem of decomposing data. To this end, we propose a built-in pattern matching construct compatible with object-oriented programming. We claim that it leads to more concise and readable code than standard object-oriented approaches. A pattern in our approach is any computable way of testing and deconstructing an object and binding relevant parts to local names. We introduce pattern matching in two variants, case classes and extractors. We compare the readability, extensibility and performance of built-in pattern matching in these two variants with standard decomposition techniques. It turns out that standard object-oriented approaches to decomposing data are not extensible. Case classes, which have been studied before, require a low notational overhead, but expose their representation, making them hard to change later. The novel extractor mechanism offers loose coupling and extensibility, but comes with a performance overhead. We present a formalization of object-oriented pattern matching with extractors. This is done by giving definitions and proving standard properties for a calculus that provides pattern matching as described before. We then give a formal, optimizing translation from the calculus including pattern matching to its fragment without pattern matching, and prove it correct. Finally, we consider non-obvious interactions between the pattern matching and parametric polymorphism. We review the technique of generalized algebraic data types from functional programming, and show how it can be carried over to the object-oriented style. The main tool is the extension of the type system with subtype constraints, which leads to a very expressive metatheory. Through this theory, we are able to express patterns that operate on existentially quantified types purely by universally quantified extractors.

EPFL2007

Compiling scala for the Java virtual machine

Michel Schinz

Scala is a new programming language developed at EPFL and incorporating the most important concepts of object-oriented and functional languages. It aims at integrating well with the Java and .NET platforms: their respective libraries are accessible without glue code, and the compiler can produce programs for both virtual machines. This thesis focuses on the compilation of two important concepts of Scala : mixin inheritance and run time types. The compilation techniques are presented in the context of the Java virtual machine, but could be adapted easily to other similar environments. Mixin inheritance is a relatively recent form of inheritance, offering new capabilities compared to single inheritance, without the complexity of multiple inheritance. We propose two implementation techniques for mixin inheritance: code copying and delegation. The implementation used in the Scala compiler is then presented and justified. Run time types make it possible for a program to examine the type of its values during execution. This possibility is interesting in itself, offering new capabilities to the programmer. Furthermore, run time types are also required to implement other high level concepts, like pattern matching, type-safe serialisation and reflection. We propose an implementation technique based on the representation of types as values, and show how to use the run time types of the underlying virtual machine to implement those of Scala. The techniques presented in this thesis have been implemented in our Scala compiler, scalac. This enabled us to evaluate these techniques, in particular their impact on the performances of programs. This evaluation was performed on several real, non-trivial programs.

EPFL2005

Compiling Scala for Performance

Iulian Dragos

Scala is a new programming language bringing together object-oriented and functional programming. Its defining features are uniformity and extensibility. Scala offers great flexibility for programmers, allowing them to grow the language through libraries. Oftentimes what seems like a language feature is in fact implemented in a library, effectively giving programmers the power of language designers. The downside of this flexibility is that familiar looking code may hide unexpected performance costs. It is important for Scala compilers to bring down this cost as much as possible. We identify several areas of impact for Scala performance: higher-order functions and closures, and generic containers used with primitive types. We present two complementary approaches for improving performance in these areas: optimizations and specialization. Compiler optimization can bring down the cost through a combination of aggressive inlining of higher-order functions, an extended version of copy-propagation and dead-code elimination. Both anonymous functions and boxing can be eliminated by this approach. We show on a number of benchmarks that these language features can be up to 5 times faster when properly optimized, on current day JVMs. We propose a new approach to compiling parametric polymorphism for performance at primitive types. We mix a homogeneous translation scheme with user-directed specialization for primitive types. Type parameters may be annotated to require specialization of code depending on them. We propose definition-site specialization for primitive types, achieving separate compilation and no boxing when both the definition and call site are specialized. Specialized classes are compatible with unspecialized code, and specialization agnostic code can work with specialized instances, meaning that specialization is opportunistic. We present a formalism of a small subset of Scala with specialization and prove that specialization preserves types. We implemented this translation in the Scala compiler and report on improvements on a set of benchmarks, showing that specialization can make programs more than two times faster.