Looking Towards a Future where Software is Controlled by the Public (and not the other way round)

Nowadays, software has a ubiquitous presence in everyday life and this phenomenon gives rise to a range of challenges that affect both individuals and society as a whole. In this article we argue that in the future, the domain of software should no longer belong to technical experts and system integrators alone. Instead it should transition to a firmly engaged public domain, similar to city planning, social welfare and security. The challenge that lies at the heart of this problem is the ability to understand, on a technical level, what all the different software actually is and what it does with our information

Code Specialization for Memory Efficient Hash Tries

The hash trie data structure is a common part in standard collection libraries of JVM programming languages such as Clojure and Scala. It enables fast immutable implementations of maps, sets, and vectors, but it requires considerably more memory than an equivalent array-based data structure. This hinders the scalability of functional programs and the further adoption of this otherwise attractive style of programming. In this paper we present a product family of hash tries. We generate Java source code to specialize them using knowledge of JVM object memory layout. The number of possible specializations is exponential. The optimization challenge is thus to find a minimal set of variants which lead to a maximal loss in memory footprint on any given data. Using a set of experiments we measured the distribution of internal tree node sizes in hash tries. We used the results as a guidance to decide which variants of the family to generate and which variants should be left to the generic implementation. A preliminary validating experiment on the implementation of sets and maps shows that this technique leads to a median decrease of 55% in memory footprint for maps (and 78% for sets), while still maintaining comparable performance. Our combination of data analysis and code specialization proved to be effective

Parse Forest Diagnostics with Dr. Ambiguity

In this paper we propose and evaluate a method for locating causes of ambiguity in context-free grammars by automatic analysis of parse forests. A parse forest is the set of parse trees of an ambiguous sentence. % an output of a static ambiguity detection tool that has detected ambiguity in a context-free grammar or of a general parser that has accidentally parsed an ambiguous sentence. Deducing causes of ambiguity from observing parse forests is hard for grammar engineers because of (a) the size of the parse forests, (b) the complex shape of parse forests, and (c) the diversity of causes of ambiguity. We first analyze the diversity of ambiguities in grammars for programming languages and the diversity of solutions to these ambiguities. Then we introduce \drambiguity: a parse forest diagnostics tools that explains the causes of ambiguity by analyzing differences between parse trees and proposes solutions. We demonstrate its effectiveness using a small experiment with a grammar for Java 5

Faster ambiguity detection by grammar filtering

Real programming languages are often defined using ambiguous context-free grammars. Some ambiguity is intentional while other ambiguity is accidental. A good grammar development environment should therefore contain a static ambiguity checker to help the grammar engineer. Ambiguity of context-free grammars is an undecidable property. Nevertheless, various imperfect ambiguity checkers exist. Exhaustive methods are accurate, but suffer from non-termination. Termination is guaranteed by approximative methods, at the expense of accuracy. In this paper we combine an approximative method with an exhaustive method. We present an extension to the Noncanonical Unambiguity Test that identifies production rules that do not contribute to the ambiguity of a grammar and show how this information can be used to significantly reduce the search space of exhaustive methods. Our experimental evaluation on a number of real world grammars shows orders of magnitude gains in efficiency in some cases and negligible losses of efficiency in others

Towards Multilingual Programming Environments

Software projects consist of different kinds of artifacts: build files, configuration files, markup files, source code in different software languages, and so on. At the same time, however, most integrated development environments (IDEs) are focused on a single (programming) language. Even if a programming environment supports multiple languages (e.g., Eclipse), IDE features such as cross-referencing, refactoring, or debugging, do not often cross language boundaries. What would it mean for programming environment to be truly multilingual? In this short paper we sketch a vision of a system that integrates IDE support across language boundaries. We propose to build this system on a foundation of unified source code models and metaprogramming. Nevertheless, a number of important and hard research questions still need to be addressed

Using the Meta-Environment for Domain Specific Language Engineering

The development of a domain specific language (DSL) can be a difficult and costly undertaking. Language workbenches aim to provide integrated development support to ease this process. The Meta-Environment is a language workbench providing parsing, analysis, transformation, syntax highlighting and formatting support for the development of programming languages. In this paper we elaborate on the suitability of it for DSL engineering by reporting on our experience in developing a little language for markup generation

Towards multilingual programming environments

Software projects consist of different kinds of artifacts: build files, configuration files, markup files, source code in different software languages, and so on. At the same time, however, most integrated development environments (IDEs) are focused on a single (programming) language. Even if a programming environment supports multiple languages (e.g., Eclipse), IDE features such as cross-referencing, refactoring, or debugging, do not often cross language boundaries. What would it mean for programming environment to be truly multilingual? In this short paper we sketch a vision of a system that integrates IDE support across language boundaries. We propose to build this system on a foundation of unified source code models and metaprogramming. Nevertheless, a number of important and hard research questions still need to be addressed