A novel and promising method of software development is the interactive style of development, where code is written and incrementally tested simultaneously. Interpreted dynamic languages such as Ruby, Python, and Lua support this interactive development style. However, because they lack semantic analysis as part of a compilation phase, they do not provide type-checking. The programmer is only informed of type errors when they are encountered in the execution of the programfar too late and often at a less-informative location in the code. We introduce a typing system for Ruby, where types will be determined before execution by inferring principal typings. This system overcomes the obstacles that interactive and dynamic program development imposes on type checking; yielding an effective type-checking facility for dynamic programming languages. Our development is embodied as an extension to irb, the Ruby interactive mode, allowing us to evaluate principal typings for interactive development.

A novel and promising method of software development is the interactive style of development, where code is written and incrementally tested simultaneously. Interpreted dynamic languages such as Ruby, Python, and Lua support this interactive development style. However, because they lack semantic analysis as part of a compilation phase, they do not provide type-checking. The programmer is only informed of type errors when they are encountered in the execution of the programfar too late and often at a less-informative location in the code. We introduce a typing system for Ruby, where types will be determined before execution by inferring principal typings. This system overcomes the obstacles that interactive and dynamic program development imposes on type checking; yielding an effective type-checking facility for dynamic programming languages. Our development is embodied as an extension to irb, the Ruby interactive mode, allowing us to evaluate principal typings for interactive development.

The Ruby programming language is dynamically typed, uses dynamic and late bound dispatch for all operators, method calls and many control structures, and provides extensive metaprogramming and introspective tooling functionality. Unlike other languages where these features are available, in Ruby their use is not avoided and key parts of the Ruby ecosystem use them extensively, even for inner-loop operations. This makes a high-performance implementation of Ruby problematic. Existing implementations either do not attempt to dynamically optimise Ruby programs, or achieve relatively limited success in optimising Ruby programs containing these features. One way that the community has worked around the limitations of existing Ruby implementations is to write extension modules in the C programming language. These are statically compiled and then dynamically linked into the Ruby implementation. Compared to equivalent Ruby, this C code is often more efficient for computationally intensive code. However the interface that these C extensions provides is defined by the non-optimising reference implementation of Ruby. Implementations which want to optimise by using different internal representations must do extensive copying to provide the same interface. This then limits the performance of the C extensions in those implementations. This leaves Ruby in the difficult position where it is not only difficult to implement the language efficiently, but the previous workaround for that problem, C extensions, also limits efforts to improve performance. This thesis describes an implementation of the Ruby programming language which embraces the Ruby language and optimises specifically for Ruby as it is used in practice. It provides a high performance implementation of Ruby's dynamic features, at the same time as providing a high performance implementation of C extensions. The implementation provides a high level of compatibility with existing Ruby implementations and does not limit the available features in order to achieve high performance. Common to all the techniques that are described in this thesis is the concept of specialisation. The conventional approach taken to optimise a dynamic language such as Ruby is to profile the program as it runs. Feedback from the profiling can then be used to specialise the program for the data and control flow it is actually experiencing. This thesis extends and advances that idea by specialising for conditions beyond normal data and control flow. Programs that call a method, or lookup a variable or constant by dynamic name rather than literal syntax can be specialised for the dynamic name by generalising inline caches. Debugging and introspective tooling is implemented by specialising the code for debug conditions such as the presence of a breakpoint or an attached tracing tool. C extensions are interpreted and dynamically optimised rather than being statically compiled, and the interface which the C code is programmed against is provided as an abstraction over the underlying implementation which can then independently specialise. The techniques developed in this thesis have a significant impact on performance of both synthetic benchmarks and kernels from real-world Ruby programs. The implementation of Ruby which has been developed achieves an order of magnitude or better increase in performance compared to the next-best implementation. In many cases the techniques are 'zero-overhead', in that the generated machine code is exactly the same for when the most dynamic features of Ruby are used, as when only static features are used.

The Verification and Validation provides support to improve the quality of the software. Verification and Validation ensures that the product is stable and developed according to the requirements of the end user. This thesis presents a systematic review of dynamic programming languages and verification & validation practices used for dynamic languages. This thesis presents results found in dynamic programming languages and verification & validation over the period of 1985 – 2008. The study is aimed to start from identification of dynamic aspects along with the differences between static and dynamic languages. Furthermore, this thesis is also intends to give overview of the verification and validation practices for dynamic languages. Moreover to validate the verification and validation results, a survey consisting of (i) interviews and (ii) online survey is conducted. After the analysis of systematic review, it has been found that dynamic languages are making progress in some of the areas like integration of common development framework, language enhancement, dynamic aspects etc. The Dynamic languages are lacking in providing a better performance than static languages. There are also some factors found in this study that can raise the popularity of dynamic languages in the industry. Based on the analysis of systematic review, interviews and online survey, it is concluded that there is no difference between the methodologies available for Verification and Validation. It is also revealed that dynamic languages provide support to maintain software quality with their characteristics and dynamic features. Moreover, they also support to test softwares developed with static language. It is concluded that test driven development should be adopted while working with the dynamic languages. Test driven development is supposed to be a mandatory part of dynamic languages. / Farrakh Saeed +46765597558

Evolução de software é uma das atividades mais desafiadoras do processo de desenvolvimento de software. Uma importante questão associada à essa atividade é a correta compreensão do código fonte e outros artefatos que necessitam ser mantidos e evoluídos. Visando auxiliar desenvolvedores na manutenção de código, Integrated Development Environments (IDE’s) proporcionam ferramentas que informam desenvolvedores sobre as dependências e as particularidades do código a ser modificado. No entanto, linguagens dinamicamente tipadas não definem tipos explicitamente no código fonte, o que dificulta a análise estática do código e consequentemente a contrução dessas ferramentas. Como exemplo, a construção de call graphs (grafos de chamadas), utilizados pelas IDE’s para criar ferramentas de navegação de código, é prejudicada pela ausência da definição de tipos. Para abordar o problema da criação de call graphs para linguagens dinamicamente tipadas, propomos uma técnica dividida em passos para a construção de um call graph baseado em informações extraídas da execução de testes. A técnica é dividida em 3 passos, o Passo #1 cria um call graph conservativo e estático que resolve chamadas de métodos baseado apenas em nomes dos métodos, ainda no primeiro passo, testes são executados e seu traço de execução é armazenado para posterior análise. O Passo #2 combina a informação armazenada da execução dos testes e o call graph construído no primeiro passo, o Passo #2 também é responsável pela criação de um conjunto de regras de associação que servirão para guiar desenvolvedores durante a criação de novas partes do código. Nossa avaliação em uma aplicação real de porte grande mostrou que a técnica melhora a precisão do call graph criado removendo arestas desnecessárias (70%), e mostrou-se apta a auxiliar desenvolvedores definindo pontos de navegação no código baseada na análise de regras de associação extraídas do test-case-based call graph. / Evolving enterprise software systems is one of the most challenging activities of the software development process. An important issue associated with this activity is to properly comprehend the source code and other software assets that must be evolved. To assist developers on these evolution tasks, Integrated Development Environments (IDEs) build tools that provides information about the source code and its dependencies. However, dynamically typed languages do not define types explicitly in the source code, which difficult source code analysis and therefore the construction of these tools. As an example, the call graph construction, used by IDE’s to build source code navigation tools, is hampered by the absence of type definition. To address the problem of constructing call graphs for dynamic languages, we propose a technique based on steps to build a call graph based on test runtime information, called test-case-based call graph. The technique is divided in three steps; Step #1 creates a conservative and static call graph that decides target nodes based on method names, and the first step also run tests profiling its execution; Step #2 combines the test runtime information and the conservative call graph built in the first step to create the test-case-based call graph, it also creates a set of association rules to guide developers in the maintenance while creating new pieces of code; Finally, Step #3 uses the test-case-based call graph and the association rules to assist developers in source code navigation tasks. Our evaluation on a large-size real-world software shows that the technique increases call graph precision removing several unnecessary conservative edges ( %70), and assist developers filtering target nodes of method calls based on association rules extracted from the call graph.

Evolução de software é uma das atividades mais desafiadoras do processo de desenvolvimento de software. Uma importante questão associada à essa atividade é a correta compreensão do código fonte e outros artefatos que necessitam ser mantidos e evoluídos. Visando auxiliar desenvolvedores na manutenção de código, Integrated Development Environments (IDE’s) proporcionam ferramentas que informam desenvolvedores sobre as dependências e as particularidades do código a ser modificado. No entanto, linguagens dinamicamente tipadas não definem tipos explicitamente no código fonte, o que dificulta a análise estática do código e consequentemente a contrução dessas ferramentas. Como exemplo, a construção de call graphs (grafos de chamadas), utilizados pelas IDE’s para criar ferramentas de navegação de código, é prejudicada pela ausência da definição de tipos. Para abordar o problema da criação de call graphs para linguagens dinamicamente tipadas, propomos uma técnica dividida em passos para a construção de um call graph baseado em informações extraídas da execução de testes. A técnica é dividida em 3 passos, o Passo #1 cria um call graph conservativo e estático que resolve chamadas de métodos baseado apenas em nomes dos métodos, ainda no primeiro passo, testes são executados e seu traço de execução é armazenado para posterior análise. O Passo #2 combina a informação armazenada da execução dos testes e o call graph construído no primeiro passo, o Passo #2 também é responsável pela criação de um conjunto de regras de associação que servirão para guiar desenvolvedores durante a criação de novas partes do código. Nossa avaliação em uma aplicação real de porte grande mostrou que a técnica melhora a precisão do call graph criado removendo arestas desnecessárias (70%), e mostrou-se apta a auxiliar desenvolvedores definindo pontos de navegação no código baseada na análise de regras de associação extraídas do test-case-based call graph. / Evolving enterprise software systems is one of the most challenging activities of the software development process. An important issue associated with this activity is to properly comprehend the source code and other software assets that must be evolved. To assist developers on these evolution tasks, Integrated Development Environments (IDEs) build tools that provides information about the source code and its dependencies. However, dynamically typed languages do not define types explicitly in the source code, which difficult source code analysis and therefore the construction of these tools. As an example, the call graph construction, used by IDE’s to build source code navigation tools, is hampered by the absence of type definition. To address the problem of constructing call graphs for dynamic languages, we propose a technique based on steps to build a call graph based on test runtime information, called test-case-based call graph. The technique is divided in three steps; Step #1 creates a conservative and static call graph that decides target nodes based on method names, and the first step also run tests profiling its execution; Step #2 combines the test runtime information and the conservative call graph built in the first step to create the test-case-based call graph, it also creates a set of association rules to guide developers in the maintenance while creating new pieces of code; Finally, Step #3 uses the test-case-based call graph and the association rules to assist developers in source code navigation tasks. Our evaluation on a large-size real-world software shows that the technique increases call graph precision removing several unnecessary conservative edges ( %70), and assist developers filtering target nodes of method calls based on association rules extracted from the call graph.

Evolução de software é uma das atividades mais desafiadoras do processo de desenvolvimento de software. Uma importante questão associada à essa atividade é a correta compreensão do código fonte e outros artefatos que necessitam ser mantidos e evoluídos. Visando auxiliar desenvolvedores na manutenção de código, Integrated Development Environments (IDE’s) proporcionam ferramentas que informam desenvolvedores sobre as dependências e as particularidades do código a ser modificado. No entanto, linguagens dinamicamente tipadas não definem tipos explicitamente no código fonte, o que dificulta a análise estática do código e consequentemente a contrução dessas ferramentas. Como exemplo, a construção de call graphs (grafos de chamadas), utilizados pelas IDE’s para criar ferramentas de navegação de código, é prejudicada pela ausência da definição de tipos. Para abordar o problema da criação de call graphs para linguagens dinamicamente tipadas, propomos uma técnica dividida em passos para a construção de um call graph baseado em informações extraídas da execução de testes. A técnica é dividida em 3 passos, o Passo #1 cria um call graph conservativo e estático que resolve chamadas de métodos baseado apenas em nomes dos métodos, ainda no primeiro passo, testes são executados e seu traço de execução é armazenado para posterior análise. O Passo #2 combina a informação armazenada da execução dos testes e o call graph construído no primeiro passo, o Passo #2 também é responsável pela criação de um conjunto de regras de associação que servirão para guiar desenvolvedores durante a criação de novas partes do código. Nossa avaliação em uma aplicação real de porte grande mostrou que a técnica melhora a precisão do call graph criado removendo arestas desnecessárias (70%), e mostrou-se apta a auxiliar desenvolvedores definindo pontos de navegação no código baseada na análise de regras de associação extraídas do test-case-based call graph. / Evolving enterprise software systems is one of the most challenging activities of the software development process. An important issue associated with this activity is to properly comprehend the source code and other software assets that must be evolved. To assist developers on these evolution tasks, Integrated Development Environments (IDEs) build tools that provides information about the source code and its dependencies. However, dynamically typed languages do not define types explicitly in the source code, which difficult source code analysis and therefore the construction of these tools. As an example, the call graph construction, used by IDE’s to build source code navigation tools, is hampered by the absence of type definition. To address the problem of constructing call graphs for dynamic languages, we propose a technique based on steps to build a call graph based on test runtime information, called test-case-based call graph. The technique is divided in three steps; Step #1 creates a conservative and static call graph that decides target nodes based on method names, and the first step also run tests profiling its execution; Step #2 combines the test runtime information and the conservative call graph built in the first step to create the test-case-based call graph, it also creates a set of association rules to guide developers in the maintenance while creating new pieces of code; Finally, Step #3 uses the test-case-based call graph and the association rules to assist developers in source code navigation tasks. Our evaluation on a large-size real-world software shows that the technique increases call graph precision removing several unnecessary conservative edges ( %70), and assist developers filtering target nodes of method calls based on association rules extracted from the call graph.

Dynamically Typed Assembly Language (D-TAL) is not only a lightweight and effective solution to the gap generated by the drop in security produced by the translation of high-level language instructions to low-level language instructions, but it considerably eases up the burden generated by the level of complexity required to implement typed assembly languages statically. Although there are tradeoffs between the static and dynamic approaches, focusing on a dynamic approach leads to simpler, easier to reason about, and more feasible ways to understand deployment of types over monomorphically-typed or untyped intermediate languages. On this occasion, DISM, a simple but powerful and mature untyped assembly language, is extended by the addition of type annotations (on memory and registers) to produce an instance of D-TAL. Strong-DISM, the resulting language, statically, lends itself to simpler analysis about type access and security as the correlation between datatypes and instructions with their respective memory and registers becomes simpler to observe; while dynamically, it disallows operations and further eliminates conditions that from high level languages could be used to violate/circumvent security.

[pt] Linguagens dinâmicas provêm flexibilidade e simplicidade em troca de menos informação em tempo de compilação, o que resulta em perda de desempenho. Atacando este problema no contexto de Lua, a linguagem de programação Pallene surge como uma alternativa. Neste trabalho, examinamos o atual estado de Pallene, procurando por padrões responsáveis por perdas de desempenho. Baseado nestes padrões, propusemos e implementamos uma série de otimizações usando técnicas de análise estática. / [en] Dynamic languages provide flexibility and simplicity in exchange for less compile-time information, leading to slower run times. Addressing this problem in the Lua context, the Pallene programming language appears as an alternative. In this work, we studied the current state of Pallene, searching for patterns that caused performance losses. Based on these patterns, we proposed and implemented several optimizations with the use of static analysis techniques.

Adaptive software becomes more and more important as computing is increasingly context-dependent. Runtime adaptability can be achieved by dynamically selecting and applying context-specific code. Role-oriented programming has been proposed as a paradigm to enable runtime adaptive software by design. Roles change the objects’ behavior at runtime, thus adapting the software to a given context. The cost of adaptivity is however a high runtime overhead stemming from executing compositions of behavior-modifying code. It has been shown that the overhead can be reduced by optimizing dispatch plans at runtime when contexts do not change, but no method exists to reduce the overhead in cases with high context variability. This paper presents a novel approach to implement polymorphic role dispatch, taking advantage of run-time information to effectively guard abstractions and enable reuse even in the presence of variable contexts. The concept of polymorphic inline caches is extended to role invocations. We evaluate the implementation with a benchmark for role-oriented programming languages achieving a geometric mean speedup of 4.0× (3.8× up to 4.5×) with static contexts, and close to no overhead in the case of varying contexts over the current implementation of contextual roles in Object Teams