The actor paradigm supports the natural expression of concurrency. It has inspired the development of several actor-based languages, whose adoption depends, to a large extent, on the runtime characteristics ( the performance and scaling behaviour) of programs written in these languages.

This paper investigates the relative runtime characteristics of Akka, CAF and Pony, based on the Savina benchmarks. We observe that the scaling of many of the Savina benchmarks does not reflect their categorization (into essentially sequential, concurrent and parallel), that many programs have similar runtime characteristics, and that their runtime behaviour may drastically change nature ( go from essentially sequential to parallel) by tweaking some parameters.

These observations lead to our proposal of a single benchmark program which we designed so that through tweaking of some knobs (we hope) we can simulate most of the programs of the Savina suite.

The age of multi-core computers is upon us, yet current programming languages, typically designed for single-core computers and adapted post hoc for multi-cores, remain tied to the constraints of a sequential mindset and are thus in many ways inadequate. New programming language designs are required that break away from this old-fashioned mindset. To address this need, we have been developing a new programming language called Encore, in the context of the European Project UpScale. The paper presents a motivation for the Encore language, examples of its main constructs, several larger programs, a formalisation of its core, and a discussion of some future directions our work will take. The work is ongoing and we started more or less from scratch. That means that a lot of work has to be done, but also that we need not be tied to decisions made for sequential language designs. Any design decision can be made in favour of good performance and scalability. For this reason, Encore offers an interesting platform for future exploration into object-oriented parallel programming.

Expressive actor models combine aspects of functional programming into the pure actor model enriched with futures. Such functional features include first-class closures which can be passed between actors and chained on futures. Combined with mutable objects, this opens the door to race conditions. In some situations, closures may not be evaluated by the actor that created them yet may access fields or objects owned by that actor. In other situations, closures may be safely fired off to run as a separate task.

This paper discusses the problem of who can safely evaluate a closure to avoid race conditions, and presents the current solution to the problem adopted by the Encore language. The solution integrates with Encore's capability type system, which influences whether a closure is attached and must be evaluated by the creating actor, or whether it can be detached and evaluated independently of its creator.

Encore's current solution to this problem is not final or optimal. We conclude by discussing a number of open problems related to dealing with closures in the actor model.

Functional programming languages are well-suited for developing compilers, and compilers for functional languages are often themselves written in a functional language. Functional abstractions, such as monads, allow abstracting away some of the repetitive structure of a compiler, removing boilerplate code and making extensions simpler. Even so, functional languages are rarely used to implement compilers for languages of other paradigms.

This paper reports on the experience of a four-year long project where we developed a compiler for a concurrent, object-oriented language using the functional language Haskell. The focus of the paper is the implementation of the type checker, but the design works well in static analysis tools, such as tracking uniqueness of variables to ensure data-race freedom. The paper starts from a simple type checker to which we add more complex features, such as type state, with minimal changes to the overall initial design.

To program parallel systems efficiently and easily, a wide range of programming models have been proposed, eachwith different choices concerning synchronization and communication between parallel entities. Among them, the actor model is based on loosely coupled parallel entities that communicate by means of asynchronous messages and mailboxes. Some actor languages provide a strong integration with object-oriented concepts; these are often called active object languages. This article reviews four major actor and active object languages and compares them according to carefully chosen dimensions that cover central aspects of the programming paradigms and their implementation.

Speculative, parallel abstractions allow that, once a result is computed, the remaining (unnecessary) speculative computations can be safely stopped. However, it is difficult to know when it is safe to stop an ongoing computation. This paper presents a refinement of the parallel speculative ParT abstraction with an affine type system that allows in-place updates, and killing speculative computations using thread-local reasoning. There is ongoing work to prove the soundness of the calculus and implement it in the Encore language.

In many actor-based programming models, asynchronous method calls communicate their results using futures, where the fulfilment occurs under-the-hood. Promises play a similar role to futures, except that they must be explicitly created and explicitly fulfilled; this makes promises more flexible than futures, though promises lack fulfilment guarantees: they can be fulfilled once, multiple times or not at all. Unfortunately, futures are too rigid to exploit many available concurrent and parallel patterns. For instance, many computations block on a future to get its result only to return that result immediately (to fulfil their own future). To make futures more flexible, we explore a construct, forward, that delegates the responsibility for fulfilling the current implicit future to another computation. Forward reduces synchronisation and gives futures promise-like capabilities. This paper presents a formalisation of the forward construct, defined in a high-level source language, and a compilation strategy from the high-level language to a low-level, promised-based target language. The translation is shown to preserve semantics. Based on this foundation, we describe the implementation of forward in the parallel, actor-based language Encore, which compiles to C.

Concurrent programs often make use of futures, handles to the results of asynchronous operations. Futures provide means to communicate not yet computed results, and simplify the implementation of operations that synchronise on the result of such asynchronous operations. Futures can be characterised as implicit or explicit, depending on the typing discipline used to type them. Current future implementations suffer from "future proliferation", either at the type-level or at run-time. The former adds future type wrappers, which hinders subtype polymorphism and exposes the client to the internal asynchronous communication architecture. The latter increases latency, by traversing nested future structures at run-time. Many languages suffer both kinds. Previous work offer partial solutions to the future proliferation problems; in this paper we show how these solutions can be integrated in an elegant and coherent way, which is more expressive than either system in isolation. We describe our proposal formally, and state and prove its key properties, in two related calculi, based on the two possible families of future constructs (data-flow futures and control-flow futures). The former relies on static type information to avoid unwanted future creation, and the latter uses an algebraic data type with dynamic checks. We also discuss how to implement our new system efficiently.

An achievement-driven methodology strives to give students more control of their learning with enough flexibility to engage them in deeper learning.

We observed in the course Advanced Software Design, which uses the achievement-driven methodology, that students fail to get high grades, which may hamper deeper learning. To motivate students to pursue and get higher grades we added gamification elements to the course.

To measure the success of our gamification implementation, students filled out a questionaire rating the enjoyment and motivation produced by the game. We built a statistical regression model where enjoyment and motivation explain 55% of the variation in grades. However, only the relationship between motivation and grade is significant, which implies that notivation drives the overall effect of the model. The results suggest that the more the students were motivated by the game, the higher their grades on the course (and vice versa). This implies that if gamification indeed motivates students, then it makes them go beyond what is expected.

The ubiquity of multicore computers has forced programming language designers to rethink how languages express parallelism and concurrency. This has resulted in new language constructs and new combinations or revisions of existing constructs. In this line, we extended the programming languages Encore (actor-based), and Clojure (functional) with an asynchronous parallel abstraction called ParT, a data structure that can dually be seen as a collection of asynchronous values (integrating with futures) or a handle to a parallel computation, plus a collection of combinators for manipulating the data structure. The combinators can express parallel pipelines and speculative parallelism. This paper presents a typed calculus capturing the essence of ParT, abstracting away from details of the Encore and Clojure programming languages. The calculus includes tasks, futures, and combinators similar to those of Orc but implemented in a non-blocking fashion. Furthermore, the calculus strongly mimics how ParT is implemented, and it can serve as the basis for adaptation of ParT into different languages and for further extensions.

Dynamic languages like Erlang, Clojure, JavaScript, and E adopted data-race freedom by design. To enforce data-race freedom, these languages either deep copy objects during actor (thread) communication or proxy back to their owning thread. We present Dala, a simple programming model that ensures data-race freedom while supporting efficient inter-thread communication. Dala is a dynamic, concurrent, capability-based language that relies on three core capa- bilities: immutable values can be shared freely; isolated mutable objects can be transferred between threads but not aliased; local objects can be aliased within their owning thread but not dereferenced by other threads. The addition of a fourth capability, unsafe, allows data races and we show how data-race free programs interact with unsafe programs. We present a formal model of Dala, prove data race-freedom and the dynamic gradual guarantee. These theorems guarantee data race-freedom when using safe capabilities and show that the addition of capabili- ties is semantics preserving modulo permission and cast errors.

Multicore and manycore computers are the norm nowadays, and users have expectations that their programs can do multiple things concurrently. To support that, developers use concur- rency abstractions such as threads, promises, futures, and/or channels to exchange information. All these abstractions introduce trade-offs between the concurrency model and the language guarantees, and developers accept these trade-offs for the benefits of concurrent programming.

Many concurrent languages are multi-paradigm, e.g., mix the functional and object-oriented paradigms. This is beneficial to developers because they can choose the most suitable approach when solving a problem. From the point of view of concurrency, purely functional programming languages are data-race free since they only support immutable data. Object-oriented languages do not get a free lunch, and neither do multi-paradigm languages that have imperative features.

The main problem is uncontrolled concurrent access to shared mutable state, which may inadvertently introduce data-races. A data-race happens when two concurrent memory operations target the same location, at least one of them is a write, and there is no synchronisation operation involved. Data-races make programs to exhibit (unwanted) non-deterministic behaviour.

The contribution of this thesis is two-fold. First, this thesis introduces new concurrent abstractions in a purely functional, statically typed programming language (Paper I – Paper III); these abstractions allow developers to write concurrent control- and delegation-based patterns. Second, this thesis introduces a capability-based dynamic programming model, named Dala, that extends the applicability of the concurrent abstractions to an imperative setting while maintaining data-race freedom (Paper IV). Developers can also use the Dala model to migrate unsafe programs, i.e., programs that may suffer data-races, to data-race free programs.

Erlang is a functional programming language with structural type-checking. Opaque types are the only types with a nominal component, where their names are used for type-checking. Using opaque types for nominal typing is possible, but it limits the use of pattern-matching and deconstruction to the module where it is defined. To distinguish types by names without imposing extra constraints, we introduce the new concept of nominal types for Erlang, together with a well-tested type-checking implementation in Dialyzer. We define a new syntax for declaring nominal types and a set of rules that specify how nominal types should be type-checked with respect to other nominal types and non-nominal types, which is designed to ensure backwards compatibility. Nominal type-checking is implemented on top of Dialyzer's structural type-checking logic. Through testing in the Erlang/OTP codebase, we show that nominal types can encode Erlang's opaque types, thereby improving Dialyzer's performance and maintainability.