Jan Vraný

Efficient method lookup customization for smalltalk

Programming languages are still evolving, and programming languages and language features are being designed and implemented every year. Since it is not a trivial task to provide a runtime system for a new language, existing runtime systems such as the Java Virtual Machine or the Common Language Runtime are used to host the new language. However, most of the high-performance runtime systems were designed for a specific language with a specific semantics. Therefore, if the new language semantics differs from the semantics hard-coded in a runtime system, it has to be emulated on top of features supported by the runtime. The emulation causes performance overhead. To overcome the limitations of an emulation, a runtime system may provide a meta-object protocol to alter the runtime semantics. The protocol should fulfill opposing goals: it should be flexible, easy to use, fast and easy to implement at the same time. We propose a simple meta-object protocol for customization of a method lookup in Smalltalk. A programmer may define his own custom method lookup routine in Smalltalk and let the runtime system to call it when needed. Therefore there is no need to modify the runtime system itself. Our solution provides reasonable performance thanks to low-level support in a runtime system, nevertheless the changes to the runtime system are small and local. At the same time, it provides the flexibility to implement a wide range of features present in modern programming languages. The presented approach has been implemented and validated on a Smalltalk virtual machine.

CRAB—CombinatoRial Auction Body Software System

Auctions are important market mechanisms for the allocation of goods and services. Combinatorial auctions are those auctions in which buyers can place bids on combinations of items. Combinatorial auctions have many applications. The paper presents the CRAB software system. CRAB is a non-commercial software system for generating, solving, and testing of combinatorial auction problems. The system solves problems by Balas’ method or by the primal-dual algorithm. CRAB is implemented in Ruby and it is distributed as the file crab.rb. The system is freely available on web pages for all interested users.

On the integration of Smalltalk and Java: practical experience with STX:LIBJAVA

After decades of development in programming languages and programming environments, Smalltalk is still one of few environments that provide advanced features and is still widely used in the industry. However, as Java became prevalent, the ability to call Java code from Smalltalk and vice versa becomes important. Traditional approaches to integrate the Java and Smalltalk languages are through low-level communication between separate Java and Smalltalk virtual machines. We are not aware of any attempt to execute and integrate the Java language directly in the Smalltalk environment. A direct integration allows for very tight and almost seamless integration of the languages and their objects within a single environment. Yet integration and language interoperability impose challenging issues related to method naming conventions, method overloading, exception handling and thread-locking mechanisms. In this paper we describe ways to overcome these challenges and to integrate Java into the Smalltalk environment. Using techniques described in this paper, the programmer can call Java code from Smalltalk using standard Smalltalk idioms while the semantics of each language remains preserved. We present STX:LIBJAVA --- an implementation of Java virtual machine within Smalltalk/X --- as a validation of our approach.

Multilanguage Debugger Architecture

When debugging applications written in several programming languages, current debuggers usually fail to provide programmers with the same quality of user experience that is common for single-language application debugging. As a result, development of multilanguage applications tends to be more expensive both in terms of development and maintenance costs. In this paper, we propose a flexible architecture that facilitates integration of multiple single-language debuggers into a single multilanguage debugger. In addition, we describe its proof-of-concept implementation that allows debugging of applications written in Smalltalk, XQuery and JavaScript.

Optimizing Parser Combinators

Parser combinators are a popular approach to parsing. Parser combinators follow the structure of an underlying grammar, are modular, well-structured, easy to maintain, and can recognize a large variety of languages including context-sensitive ones. However, their universality and flexibility introduces a noticeable performance overhead. Time-wise, parser combinators cannot compete with parsers generated by well-performing parser generators or optimized handwritten code. Techniques exist to achieve a linear asymptotic performance of parser combinators, yet there is still a significant constant multiplier. This can be further lowered using meta-programming techniques. In this work we present a more traditional approach to optimization --- a compiler --- applied to the domain of parser combinators. A parser combinator compiler (pc-compiler) analyzes a parser combinator, applies parser combinatorspecific optimizations and, generates an equivalent high-performance top-down parser. Such a compiler preserves the advantages of parser combinators while complementing them with better performance.

On the integration of Smalltalk and Java

After decades of development in programming languages and programming environments, Smalltalk is still one of few environments that provide advanced features and is used in the industry. However, as Java became prevalent, the ability to call a Java code from Smalltalk became important. A traditional approach to integrate the Java and Smalltalk languages is through low-level communication between separate Java and Smalltalk virtual machines. To our best knowledge there is no other project attempting to execute and integrate the Java language directly in the Smalltalk environment. A direct integration allows for a very tight integration of the languages and their objects within a single environment. Yet integration and language interoperability impose challenging issues related to method naming conventions, method overloading, exception handling and thread-locking mechanisms.In this paper we describe ways to overcome these challenges and to integrate Java into the Smalltalk environment. We focus on a possibility to call a Java code from Smalltalk using standard Smalltalk idioms while the semantics of both languages remains preserved. We present stx:libjava - an implementation of a Java virtual machine within Smalltalk/X - as a validation of our approach. We identify and solve problems imposed by Java and Smalltalk integration.STX:LIBJAVA, a JVM implementation built into Smalltalk/X is presented.Interoperability features of STX:LIBJAVA (e.g. dynamic proxy methods) are shown.We validated our implementation on various Java projects, e.g. Groovy or Tomcat.Performance comparation of Oracle JVM and STX:LIBJAVA is provided.

Efficient parsing with parser combinators

Abstract Parser combinators offer a universal and flexible approach to parsing. They follow the structure of an underlying grammar, are modular, well-structured, easy to maintain, and can recognize a large variety of languages including context-sensitive ones. However, these advantages introduce a noticeable performance overhead mainly because the same powerful parsing algorithm is used to recognize even simple languages. Time-wise, parser combinators cannot compete with parsers generated by well-performing parser generators or optimized hand-written code. Techniques exist to achieve a linear asymptotic performance of parser combinators, yet there is a significant constant multiplier. The multiplier can be lowered to some degree, but this requires advanced meta-programming techniques, such as staging or macros, that depend heavily on the underlying language technology. In this work we present a language-agnostic solution. We optimize the performance of parsing combinators with specializations of parsing strategies. For each combinator, we analyze the language parsed by the combinator and choose the most efficient parsing strategy. By adapting a parsing strategy for different parser combinators we achieve performance comparable to that of hand-written or optimized parsers while preserving the advantages of parsers combinators.