A typed intermediate language and algorithms for compiling scala by successive rewritings

Scala is a general-purpose programming language developed at EPFL. It combines concepts coming from object-oriented languages with other ones coming from functional languages. Scala is strongly typed and comes with a relatively complex type system, which incorporates several advanced concepts. The Scala compiler consists of successive phases, which rewrite the source code into ever simpler versions until the code is simple enough such that in can be trivially translated into object code. It is expected that each phase generates well-typed Scala code. This thesis starts by describing in details the main language constructions of Scala along with its type system. It then focuses on two rewriting phases whose implementation was much more difficult than expected. Indeed, during the development of the compiler, it was discovered that some programs cannot be simplified by rewriting them if the produced code has to be well-typed Scala code. The two problematic phases are described in details as well as the programs that cannot be correctly rewritten. A typed intermediate language that generalizes some aspects of Scala and thus enables the rewriting of all programs is described. The two rewriting phases are then formally described using this intermediate language.

Programming language abstractions for mobile code

Stéphane Micheloud

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.

EPFL2009

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

Compile-Time Type-Driven Data Representation Transformations in Object-Oriented Languages

Vlad Ureche

High-level languages allow programmers to express data structures and algorithms that abstract over the type of data they handle. This improves code reuse and makes it possible to develop general-purpose libraries. Yet, data abstractions slow down program execution, as they require low-level indirection. In this thesis we explore three compile-time approaches that leverage type systems to reduce the cost of data abstractions, thus improving program performance. In the first part of the thesis we present miniboxing, a compile-time transformation that replaces generic classes by more efficient variants, optimized to handle primitive types. These variants use the miniboxed data encoding, producing speedups of up to 20x compared to generic classes. The miniboxing transformation is the main result of this thesis and motivates the other techniques. Generalizing miniboxing, we show the Late Data Layout (LDL) mechanism, which uses the type system to guide performance-oriented program rewritings. It can be instantiated to perform a host of transformations, such as miniboxing generics, inlining value classes and unboxing primitive types. The LDL mechanism has many desirable properties, such as provable correctness in handling different data representations, reduced number of conversions and built-in support for the object-oriented paradigm. Finally, we show Data-centric Metaprogramming, a technique that allows programmers to go beyond standard compiler optimizations by defining custom representations to be used for their data. These representations are then automatically introduced by the compiler when translating programs. This technique, similar in spirit to metaprogramming, opens new directions in programmer-driven optimizations and shows encouraging results, with speedups of up to 25x. Under the hood, Data-centric Metaprogramming uses the Late Data Layout mechanism.