The modern landscape of managing effects for the working programmer

The management of side effects is a crucial aspect of modern programming, especially in concurrent and distributed systems. This thesis analyses different approaches for managing side effects in programming languages, specifically focusing on unrestricted side effects, monads, and algebraic effects and handlers. Unrestricted side effects, used in mainstream imperative programming languages, can make programs difficult to reason about. Monads offer a solution to this problem by describing side effects in a composable and referentially transparent way but many find them cumbersome to use. Algebraic effects and handlers can address some of the shortcomings of monads by providing a way to model effects in more modular and flexible way. The thesis discusses the advantages and disadvantages of each of these approaches and compares them based on factors such as expressiveness, safety, and constraints they place on how programs must be implemented. The thesis focuses on ZIO, a Scala library for concurrent and asynchronous programming, which revolves around a ZIO monad with three type parameters. With those three parameters ZIO can encode the majority of practically useful effects in a single monad. ZIO takes inspiration from algebraic effects, combining them with monadic effects. The library provides a range of features, such as declarative concurrency, error handling, and resource management. The thesis presents examples of using ZIO to manage side effects in practical scenarios, highlighting its strengths over other approaches. The applicability of ZIO is evaluated by implementing a server side application using ZIO, and analyzing observations from the development process

Modular interpreters with implicit context propagation

Modular interpreters are a crucial first step towards component-based language development: instead of writing language interpreters from scratch, they can be assembled from reusable, semantic building blocks. Unfortunately, traditional language interpreters can be hard to extend because different language constructs may require different interpreter signatures. For instance, arithmetic interpreters produce a value without any context information, whereas binding constructs require an additional environment.In this paper, we present a practical solution to this problem based on implicit context propagation. By structuring denotational-style interpreters as Object Algebras, base interpreters can be retroactively lifted into new interpreters that have an extended signature. The additional parameters are implicitly propagated behind the scenes, through the evaluation of the base interpreter.Interpreter lifting enables a flexible style of modular and extensible language development. The technique works in mainstream object-oriented languages, does not sacrifice type safety or separate compilation, and can be easily automated, for instance using macros in Scala or dynamic proxies in Java. We illustrate implicit context propagation using a modular definition of Featherweight Java and its extension to support side-effects, and an extensible domain-specific language for state machines. We finally investigate the performance overhead of lifting by running the DeltaBlue benchmark program in Javascript on top of a modular implementation of LambdaJS and a dedicated micro-benchmark. The results show that lifting makes interpreters roughly twice as slow because of additional call overhead. Further research is needed to eliminate this performance penalty

Efficient abstractions for visualization and interaction

Abstractions, such as functions and methods, are an essential tool for any programmer. Abstractions encapsulate the details of a computation: the programmer only needs to know what the abstraction achieves, not how it achieves it. However, using abstractions can come at a cost: the resulting program may be inefficient. This can lead to programmers not using some abstractions, instead writing the entire functionality from the ground up. In this thesis, we present several results that make this situation less likely when programming interactive visualizations. We present results that make abstractions more efficient in the areas of graphics, layout and events

Developing and Measuring Parallel Rule-Based Systems in a Functional Programming Environment

This thesis investigates the suitability of using functional programming for building parallel rule-based systems. A functional version of the well known rule-based system OPS5 was implemented, and there is a discussion on the suitability of functional languages for both building compilers and manipulating state. Functional languages can be used to build compilers that reflect the structure of the original grammar of a language and are, therefore, very suitable. Particular attention is paid to the state requirements and the state manipulation structures of applications such as a rule-based system because, traditionally, functional languages have been considered unable to manipulate state. From the implementation work, issues have arisen that are important for functional programming as a whole. They are in the areas of algorithms and data structures and development environments. There is a more general discussion of state and state manipulation in functional programs and how theoretical work, such as monads, can be used. Techniques for how descriptions of graph algorithms may be interpreted more abstractly to build functional graph algorithms are presented. Beyond the scope of programming, there are issues relating both to the functional language interaction with the operating system and to tools, such as debugging and measurement tools, which help programmers write efficient programs. In both of these areas functional systems are lacking. To address the complete lack of measurement tools for functional languages, a profiling technique was designed which can accurately measure the number of calls to a function , the time spent in a function, and the amount of heap space used by a function. From this design, a profiler was developed for higher-order, lazy, functional languages which allows the programmer to measure and verify the behaviour of a program. This profiling technique is designed primarily for application programmers rather than functional language implementors, and the results presented by the profiler directly reflect the lexical scope of the original program rather than some run-time representation. Finally, there is a discussion of generally available techniques for parallelizing functional programs in order that they may execute on a parallel machine. The techniques which are easier for the parallel systems builder to implement are shown to be least suitable for large functional applications. Those techniques that best suit functional programmers are not yet generally available and usable

Language components for modular DSLs using traits

Recent advances in tooling and modern programming languages have progressively brought back the practice of developing domain-specific languages as a means to improve software development. Consequently, the problem of making composition between languages easier by emphasizing code reuse and componentized programming is a topic of increasing interest in research. In fact, it is not uncommon for different languages to share common features, and, because in the same project different DSLs may coexist to model concepts from different problem areas, it is interesting to study ways to develop modular, extensible languages. Earlier work has shown that traits can be used to modularize the semantics of a language implementation; a lot of attention is often spent on embedded DSLs; even when external DSLs are discussed, the main focus is on modularizing the semantics. In this paper we will show a complete trait-based approach to modularize not only the semantics but also the syntax of external DSLs, thereby simplifying extension and therefore evolution of a language implementation. We show the benefits of implementing these techniques using the Scala programming language

Semantic networks

AbstractA semantic network is a graph of the structure of meaning. This article introduces semantic network systems and their importance in Artificial Intelligence, followed by I. the early background; II. a summary of the basic ideas and issues including link types, frame systems, case relations, link valence, abstraction, inheritance hierarchies and logic extensions; and III. a survey of ‘world-structuring’ systems including ontologies, causal link models, continuous models, relevance, formal dictionaries, semantic primitives and intersecting inference hierarchies. Speed and practical implementation are briefly discussed. The conclusion argues for a synthesis of relational graph theory, graph-grammar theory and order theory based on semantic primitives and multiple intersecting inference hierarchies