Achieving high software quality today involves manual analysis, test planning, documentation of testing strategy and test cases, and development of automated test scripts to support regression testing. This thesis is motivated by the opportunity to bridge the gap between current test automation and true test automation by investigating learning-based solutions to software testing. We present an approach that combines a trainable web component classifier, a test case description language, and a trainable test generation and execution system that can learn to generate new test cases. Training data was collected and hand-labeled across 7 systems, 95 web pages, and 17,360 elements. A total of 250 test flows were also manually hand-crafted for training purposes. Various machine learning algorithms were evaluated. Results showed that Random Forest classifiers performed well on several web component classification problems. In addition, Long Short-Term Memory neural networks were able to model and generate new valid test flows.

[pt] Inúmeras linguagens de programação oferecem suporte a finalizadores e referências fracas. Não obstante, de maneira geral esses mecanismos são relativamente pouco conhecidos e pouco usados por programadores. Mesmo entre pesquisadores e desenvolvedores de linguagens não existe muito consenso quanto à sua semântica, que varia consideravelmente entre diferentes implementações. Neste trabalho buscamos explorar os conceitos de finalizadores e de referências fracas, suprindo a ausência de uma especificação clara e abrangente, e permitindo uma melhor compreensão, implementação e uso dos mecanismos correspondentes. Como ponto de partida realizamos um amplo levantamento sobre como é feito o suporte a finalizadores e referências fracas em diferentes linguagens de programação, identificando as características comuns, os problemas, e as questões semânticas mais relevantes associadas às implementações consideradas. Para garantir uma maior precisão em nossa análise, utilizamos um modelo abstrato de uma linguagem de programação com gerenciamento automático de memória. Através deste modelo especificamos formalmente a semântica de finalizadores e referências fracas, incluindo descrições das suas principais variantes e mecanismos relacionados. Além disso, provamos certas propriedades inerentes a linguagens de programação com gerenciamento automático de memória, indicando como estas são afetadas pela introdução de finalizadores e referências fracas. Por fim, consideramos possíveis estratégias de implementação desses mecanismos em diferentes tipos de sistemas. Algumas das opções semânticas investigadas impõe um custo de processamento expressivo, o que frequentemente inviabiliza a sua adoção na prática. / [en] Most mainstream programming languages support finalizers and weak references. In spite of that, these abstractions are still modestly known by programmers in general. Even among language designers there seems to be no common view on how to define their semantics, and language implementations certainly reflect that. In this thesis we explore the concepts of finalizer and weak reference by discussing several important issues that, as far as we know, have not been explored by other authors. After presenting a survey on how finalizers and weak references are supported by actual programming languages, we thoroughly examine their semantics and discuss alternative implementation strategies. We also use an operational approach to develop a formal model for reasoning about garbage collection and its interaction with client programs. By explicitly representing low-level details, such as heap memory and its addresses, we were able to clearly specify memory management actions, and prove several important memory-related language invariants. Using this model we describe a formal semantics for finalizers and weak references, exploring some of its many subtleties. We believe that the topics covered here can serve as a relevant reference for further investigations, and also help to guide actual implementations.

<p>    </p> <p>Programs that use loops to operate over arrays and matrices are generally known as <em>regular programs</em>. These programs appear in critical applications such as image processing, differential equation solvers, and machine learning. Over the past few decades, extensive research has been done on composing, verifying, and applying scheduling transformations like loop interchange and loop tiling for regular programs. As a result, we have general frameworks such as the polyhedral model to handle transformations for loop-based programs. Similarly, programs that use recursion and loops to manipulate pointer-based data structures are known as <em>irregular programs</em>. Irregular programs also appear in essential applications such as scientific simulations, data mining, and graphics rendering. However, there is no analogous framework for recursive programs. In the last decade, although many scheduling transformations have been developed for irregular programs, they are ad-hoc in various aspects, such as being developed for a specific application and lacking portability. This dissertation examines principled ways to handle scheduling transformations for recursive programs through a unified framework resulting in performance enhancement. </p> <p>Finding principled approaches to optimize irregular programs at compile-time is a long-standing problem. We specifically focus on scheduling transformations that reorder a program’s operations to improve performance by enhancing locality and exploiting parallelism. In the first part of this dissertation, we present PolyRec, a unified general framework that can compose and apply scheduling transformations to nested recursive programs and reason about the correctness of composed transformations. PolyRec is a first-of-its-kind unified general transformation framework for irregular programs consisting of nested recursion and loops. It is built on solid theoretical foundations from the world of automata and transducers and provides a fundamentally novel way to think about recursive programs and scheduling transformations for them. The core idea is designing mechanisms to strike a balance between the expressivity in representing the set of dynamic instances of computations, transformations, and dependences and the decidability of checking the correctness of composed transformations. We use <em>multi-tape </em>automata and transducers to represent the set of dynamic instances of computations and transformations, respectively. These machines are similar yet more expressive than their classical single-tape counterparts. While in general decidable properties of classical machines are undecidable for multi-tape machines, we have proven that those properties are decidable for the class of machines we consider, and we present algorithms to verify these properties. Therefore these machines provide the building blocks to compose and verify scheduling transformations for nested recursion and loops. The crux of the PolyRec framework is its regular string-based representation of dynamic instances that allows to lexicographically order instances identically to their execution order. All the transformations considered in PolyRec require different ordering of these strings representable only with <em>additive </em>changes to the strings. </p> <p>Loop transformations such as <em>skewing </em>require performing arithmetic on the representation of dynamic instances. In the second part of this dissertation, we explore this space of transformations by introducing skewing to nested recursion. Skewing plays an essential role in producing easily parallelizable loop nests from seemingly difficult ones due to dependences carried across loops. The inclusion of skewing for nested recursion to PolyRec requires significant extensions to representing dynamic instances and transformations that facilitate <em>performing arithmetic using strings</em>. First, we prove that the machines that represent the transformations are still composable. Then we prove that the representation of dependences and the algorithm that checks the correctness of composed transformations hold with minimal changes. Our new extended framework is known as UniRec, since it resembles the unimodular transformations for perfectly nested loop nests, which consider any combination of the primary transformations interchange, reversal, and skewing. UniRec opens possibilities of producing newly composed transformations for nested recursion and loops and verifying their correctness. We claim that UniRec completely subsumes the unimodular framework for loop transformations since nested recursion is more general than loop nests. </p>

<p>Static program analyzers are vital tools to produce useful insights about programs without executing these programs. These insights can be used to improve the quality of programs, e.g., detecting defects in programs, or optimizing programs to use fewer resources. However, building static program analyzers that are simultaneously sound, performant, and flexible is notoriously challenging.</p> <p>This dissertation aims to address this challenge by exploring the potential of applying correct-by-construction metaprogramming techniques to build static program analyzers. Metaprogramming techniques manipulate and transform programs as data objects.  In this thesis, we consider static program analyzers as the objects to be manipulated or transformed. We show that metaprogramming techniques can improve our understanding, the construction, flexibility, and performance of program analyzers.</p> <p>We first study the inter-derivation of abstract interpreters. Using off-the-shelf program transformation techniques such as refunctionalization, we demonstrate that big-step abstract interpreters can be mechanically derived from their small-step counterparts, thus building a functional correspondence between two different styles of abstract interpretation.</p> <p>To build high-performance program analyzers, we exploit the first Futamura projection to build compilers for abstract interpretation and symbolic execution. The first Futamura projection states that specializing an interpreter with respect to an input program is a process equivalent to compilation, thus providing a practical way to repurpose interpreters for compilation and code generation. We systematically apply this idea to build program-analysis compilers by writing analyzers as staged interpreters using higher-level abstractions. The staged interpreter can be used for generating sound and performant analysis code given a specific input program. Moreover, the approach enables using abstractions without regret: by using higher-level program abstractions, the analyzer can be written in a way that is close to its high-level specification (e.g. big-step operational semantics), and by compilation, the analyzer is performant since it does not need to pay the runtime overhead of using these abstraction mechanisms.</p> <p>We also develop novel type systems that track sharing and separation in higher-order imperative languages. Such type systems are useful both for general-purpose programming languages and for optimization of domain-specific metaprograms such as those program-analysis compilers.</p> <p><br></p>

The presented diploma thesis examines the possibilities of developing algorithmic thinking in primary school pupils. Algorithmic thinking is a necessary tool for effective analysis of the problem and the creation of a procedure for its subsequent repeatable solution. The main research topic of this work is effective and efficient ways of developing algorithmic thinking, especially how to formulate a problem and how to develop algorithmic thinking with the greatest effect in the educational process. The work summarizes various ways of developing algorithmic thinking and the approach to its teaching. The concepts of computer thinking, algorithmic thinking, algorithm and algorithmization are defined and analyzed. Furthermore, contemporary means of developing algorithmic thinking described in the literature are specified. They are then critically evaluated and at the end of the theoretical part the most suitable set of means is selected and the way of their use is proposed. Action research was carried out in the circle of informatics at the primary school in Prague. The verification of the effectiveness of the selected instruments took place during fifteen sixty-minute lessons. The focus of this research lies in increasing the quality of pedagogical practice of the teacher, in the development of his didactic...

Static analysis tools can aid programmers by reporting potential programming mistakes prior to the execution of a program. Funqual is a static analysis tool that reads C++17 code ``in the wild'' and checks that the function call graph follows a set of rules which can be defined by the user. This sort of analysis can help the programmer to avoid errors such as accidentally calling blocking functions in time-sensitive contexts or accidentally allocating memory in heap-sensitive environments. To accomplish this, we create a type system whereby functions can be given user-defined type qualifiers and where users can define their own restrictions on the call graph based on these type qualifiers. We demonstrate that this tool, when used with hand-crafted rules, can catch certain types of errors which commonly occur in the wild. We claim that this tool can be used in a production setting to catch certain kinds of errors in code before that code is even run.

[pt] Produzir tecnologia tem se mostrado uma habilidade cada vez mais indispensável na sociedade moderna. Os usuários estão deixando de ser simples consumidores e passando a ser produtores, usando a tecnologia para expressarem suas ideias. Nesse contexto, o aprendizado do chamado raciocínio computacional deve ser tão importante quanto o de disciplinas básicas, como a leitura, a escrita e a aritmética. Ao desenvolver tal habilidade o aluno vai conseguir se expressar através do software. Diversos projetos ao redor do mundo têm suas tecnologias e didáticas próprias a fim de auxiliar o aluno a desenvolver tal capacidade. Porém, sabemos que em um contexto que está em constante evolução como é o caso da informática, não podemos deixar que o aluno fique preso a uma única ferramenta ou meio de se expressar. Ferramentas podem ficar obsoletas e ele perderia seu poder de produtor de tecnologia. Pensando nisso, foi elaborado um modelo de transferência do aprendizado do raciocínio computacional a ser incorporado a sistemas de documentação ativa que apoiam o ensino-aprendizado desta habilidade. O modelo auxiliará o designer na criação de um artefato tecnológico que seja capaz de ajudar alunos e professores a aprenderem uma nova linguagem de programação. O modelo, que é baseado na Engenharia Semiótica, é a principal contribuição científica dessa dissertação de mestrado. / [en] Producing technology has been an increasingly essential ability in modern society. The users are no longer simple consumers but actually, also, technology producers, using technology to express their ideas. In this context, the learning of the so-called computational thinking should be as important as learning basic disciplines such as reading, writing and arithmetic. As long as the student can develop this ability, he will be able to express himself or herself through the software. Many projects around the world have their own technologies and pedagogy to help the student develop such capacity. However, we know that in a context that is constantly evolving as is the case of informatics, we cannot allow the student to be attached to a single tool or means. Tools may become obsolete and students would lose their technology producer status. With this in mind, we designed a learning transfer model of computational thinking, which will assist the designer in the creation of a technological artifact to help students and teachers learn a new programming language. The model, which is based on the Semiotic Engineering, is the main scientific contribution of this master s dissertation.

As was recognized by same of the most reputable physicists of the world such as Galilee and Einstein, the basic laws of physics must inevitably be founded upon invariance principles. Galilean and special relativity stand as historical landmarks that emphasize this message. It's no wonder that the great developments of modern physics (such as those in elementary particle physics) have been keyed upon this concept. The modern formulation of classical mechanics (see Abraham and Marsden [1]) is based upon "qualitative" or geometric analysis. This is primarily due to the works of Poincare. Poincare showed the value of such geometric analysis in the solution of otherwise insoluble problems in stability theory. It seems that the insights of Poincare have proven fruitful by the now famous works of Kolmogorov, Arnold, and Moser. The concepts used in this geometric theory are again based upon invariance principles, or symmetries. The work of Sophus Lie from 1873 to 1893 laid the groundwork for the analysis of invariance or symmetry principles in modern physics. His primary studies were those of partial differential equations. This led him to the study of the theory of transformations and inevitably to the analysis of abstract groups and differential geometry. Here we show same further applications of Lie group theory through the use of transformation groups. We emphasize the use of transformation invariance to find conservation laws and dynamical properties in chemical physics.

<pre>The proliferation of digital data, driven by factors like social media, e-commerce, etc., has created an increasing demand for highly processed data at higher levels of fidelity, which puts increasing demands on modern data processing systems. In the past, data processing systems faced bottlenecks due to limited main memory availability. However, as main memory becomes more abundant, their optimization focus has shifted from disk I/O to optimized computation through techniques like compilation. This dissertation addresses several critical limitations within such compilation-based data processing systems.<br><br>In modern data analytics pipelines, combination of workloads from various paradigms, such as traditional DBMS and Machine Learning, is common. <br>These pipelines are typically managed by specialized systems designed for specific workload types. While these specialized systems optimize their individual performance, substantial performance loss occurs when they are combined to handle mixed workloads. This loss is mainly due to overheads at system boundaries, including data copying and format conversions, as well as the general inability to perform cross-system optimizations.<br><br>This dissertation tackles this problem in two angles. First, it proposes an efficient post-hoc integration of individual systems using generative programming via the construction of common intermediate layers. This approach preserves the best-of-breed performance of individual workloads while achieving state-of-the-art performance for combined workloads. Second, we introduce a high-level query language capable of expressing various workload types, acting as a general substrate to implement combined workloads. This allows the generation of optimized code for end-to-end workloads through<br>the construction of an intermediate representation (IR).<br><br>The dissertation then shifts focus to data processing systems used for incremental view maintenance (IVM). While existing IVM systems achieve high performance through compilation and novel algorithms, they have limitations in handling specific query classes. Notably, they are incapable of handling queries involving correlated nested aggregate subqueries. To address this, our work proposes a novel indexing scheme based on a new data structure and a corresponding set of algorithms that fully incrementalize such queries. This approach result in substantial asymptotic speedups and order-of-magnitude performance improvements for workloads of practical importance.<br><br>Finally, the dissertation explores efficient and expressive fixed-point computations, with a focus on Datalog--a language widely used for declarative program analysis. Although existing Datalog engines rely on compilation and specialized code generation to achieve performance, they lack the flexibility to support extensions required for complex program analysis. Our work introduces a new Datalog engine built using generative programming techniques that offers both flexibility and state-of-the-art performance through specialized code generation.</pre><p></p>

[pt] A maioria das linguagens de programação modernas fornece ferramentas para programação concorrente sem restringir seu uso. Assim, fica a cargo do programador evitar a ocorrência de condições de corrida. Nessa dissertação, revisitamos o modelo de monitores, projetados para prevenir condições de corrida ao limitar o acesso à variáveis compartilhadas, e mostramos que monitores podem ser implementados em linguagens de programação com semântica referencial, dadas as regras de tipagem apropriadas. Nós descrevemos a linguagem de programação Aria, projetada com monitores nativos seguindo a proposta original do modelo. Através da resolução de problemas clássicos de concorrência, nós avaliamos o uso de monitores em Aria para sincronização em diferentes níveis de granularidade, e extendemos a linguagem com novos recursos a fim de contemplar as limitações do modelo envolvendo desempenho e expressividade. / [en] Most current programming languages do not restrict the use of the concurrency primitives they provide, leaving it to the programmer to detect data races. In this dissertation, we revisit the monitor model, which guards against data races by guaranteeing that accesses to shared variables occur only inside monitors, and show that this concept can be implemented in a programming language with referential semantics, given appropriate typing rules. We describe the Aria programming language, designed with native monitors according to these rules. Through the discussion of classic concurrency problems, we evaluate the use of Aria monitors for synchronization at different levels of granularity and extend the language with new features to address the limitations of monitors regarding performance and expressiveness.