Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Improving the Network Scalability of Erlang

As the number of cores grows in commodity architectures so does the likelihood of failures. A distributed actor model potentially facilitates the development of reliable and scalable software on these architectures. Key components include lightweight processes which ‘share nothing’ and hence can fail independently. Erlang is not only increasingly widely used, but the underlying actor model has been a beacon for programming language design, influencing for example Scala, Clojure and Cloud Haskell. While the Erlang distributed actor model is inherently scalable, we demonstrate that it is limited by some pragmatic factors. We address two network scalability issues here: globally registered process names must be updated on every node (virtual machine) in the system, and any Erlang nodes that communicate maintain an active connection. That is, there is a fully connected O(n2) network of n nodes. We present the design, implementation, and initial evaluation of a conservative extension of Erlang — Scalable Distributed (SD) Erlang. SD Erlang partitions the global namespace and connection network using s_groups. An s_group is a set of nodes with its own process namespace and with a fully connected network within the s_group, but only individual connections outside it. As a node may belong to more than one s_group it is possible to construct arbitrary connection topologies like trees or rings. We present an operational semantics for the s_group functions, and outline the validation of conformance between the implementation and the semantics using the QuickCheck automatic testing tool. Our preliminary evaluation in comparison with distributed Erlang shows that SD Erlang dramatically improves network scalability even if the number of global operations is tiny (0.01%). Moreover, even in the absence of global operations the reduced connection maintenance overheads mean that SD Erlang scales better beyond 80 nodes (1920 cores)

situ-f: a domain specific language and a first step towards the realization of situ framework

Situ proposes a human centered, dynamic reasoning framework for domain experts to evolve their software. It formally models the relationship between externally observed situation sequences and the rapid evolution of that software system, using real-time usage information from users and contextual capturing on the behavior of a software system relative to its runtime environment. Situf is a continuing effort under Situ framework. In this effort, a domain specific, functional programming language named Situf is presented from its design, semantics and a feasibility test through theoretical validation. The targeted users of this language mainly include domain experts and engineers who are versed in the major concepts and paradigms regarding human-centric situations. As argued there, human-centric situations are vitally important to infer a user\u27s intention and therefore, to drive software service evolution. Situf is designed particularly to encourage domain experts and engineers to think and work with situations. An attribute grammar based approach is developed so that through Situf , relevant real-time contexts can be systematically aggregated around situations. A computational semantics is offered to precisely describe the runtime behavior of a Situf program. While the Situf language serves as the critical centerpiece of this work, its functioning necessarily requires environmental support from Situ elements outside the language itself, such that altogether they give rise to a Situ oriented system. This environment, named Situf -based environment, is also introduced

1957-2007: 50 Years of Higher Order Programming Languages

Fifty years ago one of the greatest breakthroughs in computer programming and in the history of computers happened – the appearance of FORTRAN, the first higher-order programming language. From that time until now hundreds of programming languages were invented, different programming paradigms were defined, all with the main goal to make computer programming easier and closer to as many people as possible. Many battles were fought among scientists as well as among developers around concepts of programming, programming languages and paradigms. It can be said that programming paradigms and programming languages were very often a trigger for many changes and improvements in computer science as well as in computer industry. Definitely, computer programming is one of the cornerstones of computer science. Today there are many tools that give a help in the process of programming, but there is still a programming tasks that can be solved only manually. Therefore, programming is still one of the most creative parts of interaction with computers. Programmers should chose programming language in accordance to task they have to solve, but very often, they chose it in accordance to their personal preferences, their beliefs and many other subjective reasons. Nevertheless, the market of programming languages can be merciless to languages as history was merciless to some people, even whole nations. Programming languages and developers get born, live and die leaving more or less tracks and successors, and not always the best survives. The history of programming languages is closely connected to the history of computers and computer science itself. Every single thing from one of them has its reflexions onto the other. This paper gives a short overview of last fifty years of computer programming and computer programming languages, but also gives many ideas that influenced other aspects of computer science. Particularly, programming paradigms are described, their intentions and goals, as well as the most of the significant languages of all paradigms

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Programmiersprachen und Rechenkonzepte

Seit 1984 veranstaltet die GI-Fachgruppe "Programmiersprachen und Rechenkonzepte" regelmäßig im Frühjahr einen Workshop im Physikzentrum Bad Honnef. Das Treffen dient in erster Linie dem gegenseitigen Kennenlernen, dem Erfahrungsaustausch, der Diskussion und der Vertiefung gegenseitiger Kontakte. In diesem Forum werden Vorträge und Demonstrationen sowohl bereits abgeschlossener als auch noch laufender Arbeiten vorgestellt, unter anderem (aber nicht ausschließlich) zu Themen wie - Sprachen, Sprachparadigmen, - Korrektheit von Entwurf und Implementierung, -Werkzeuge, -Software-/Hardware-Architekturen, -Spezifikation, Entwurf, - Validierung, Verifikation, - Implementierung, Integration, - Sicherheit (Safety und Security), - eingebettete Systeme, - hardware-nahe Programmierung. In diesem Technischen Bericht sind einige der präsentierten Arbeiten zusammen gestellt

An Analysis of Introductory Programming Courses at UK Universities

Context: In the context of exploring the art, science and engineering of programming, the question of which programming languages should be taught first has been fiercely debated since computer science teaching started in universities. Failure to grasp programming readily almost certainly implies failure to progress in computer science.Inquiry: What first programming languages are being taught? There have been regular national-scale surveys in Australia and New Zealand, with the only US survey reporting on a small subset of universities. This the first such national survey of universities in the UK.Approach: We report the results of the first survey of introductory programming courses (N=80) taught at UK universities as part of their first year computer science (or related) degree programmes, conducted in the first half of 2016. We report on student numbers, programming paradigm, programming languages and environment/tools used, as well as the underpinning rationale for these choices.Knowledge: The results in this first UK survey indicate a dominance of Java at a time when universities are still generally teaching students who are new to programming (and computer science), despite the fact that Python is perceived, by the same respondents, to be both easier to teach as well as to learn.Grounding: We compare the results of this survey with a related survey conducted since 2010 (as well as earlier surveys from 2001 and 2003) in Australia and New Zealand.Importance: This survey provides a starting point for valuable pedagogic baseline data for the analysis of the art, science and engineering of programming, in the context of substantial computer science curriculum reform in UK schools, as well as increasing scrutiny of teaching excellence and graduate employability for UK universities

Aspects of functional programming

This thesis explores the application of functional programming in new areas and its implementation using new technologies. We show how functional languages can be used to implement solutions to problems in fuzzy logic using a number of languages: Haskell, Ginger and Aladin. A compiler for the weakly-typed, lazy language Ginger is developed using Java byte-code as its target code. This is used as the inspiration for an implementation of Aladin, a simple functional language which has two novel features: its primitives are designed to be written in any language, and evaluation is controlled by declaring the strictness of all functions. Efficient denotational and operational semantics are given for this machine and an implementation is devel- oped using these semantics. We then show that by using the advantages of Aladin (simplicity and strictness control) we can employ partial evaluation to achieve con- siderable speed-ups in the running times of Aladin programs