This dissertation presents novel approaches to test context aware applications that suffer from a cost prohibitive number of context and GUI events and event combinations. The contributions of this work to test context aware applications under test include: (1) a real-world context events dataset from 82 Android users over a 30-day period, (2) applications of Markov models, Closed Sequential Pattern Mining (CloSPAN), Deep Neural Networks- Long Short Term Memory (LSTM) and Gated Recurrent Units (GRU), and Conditional Random Fields (CRF) applied to predict context patterns, (3) data driven test case generation techniques that insert events at the beginning of each test case in a round-robin manner, iterate through multiple context events at the beginning of each test case in a round-robin manner, and interleave real-world context event sequences and GUI events, and (4) systematically interleaving context with a combinatorial-based approach. The results of our empirical studies indicate (1) CRF outperforms other models thereby predicting context events with F1 score of about 60% for our dataset, (2) the ISFreqOne that iterates over context events at the beginning of each test case in a round-robin manner as well as interleaves real-world context event sequences and GUI events at an interval one achieves up to four times better code coverage than not including context, 0.06 times better coverage than RSContext that inserts random context events at the beginning of each test case, 0.05 times better coverage than ISContext that iterates over context events to insert at the beginning of each test case in a round-robin manner, and 0.04 times better coverage than ISFreqTwo that iterates over context events at the beginning of each test case in a round-robin manner as well as interleaves real-world context event sequences and GUI events at an interval two on an average across four subject applications and, (3) the PairwiseInterleaved technique that selects a different context event at the beginning of each test case by iterating through context covering array in a round-robin manner and systematically interleaves context with GUI events by prioritizing the execution of GUI events in new contexts achieves higher code coverage up to a factor of six when compared to Monkey, up to a factor of 1.3 when compared to a technique that generates test suites without context events, and similar code coverage when compared to ISContext that iterates over context events to insert at the beginning of each test case in a round-robin manner on an average across five subject applications.

To automatically/semi-automatically improve internal structures of a legacy system, there are several challenges: most available software analysis algorithms focus on only one particular granularity level (e.g., method level, class level) without considering possible side effects on other levels during the process; the quality of a software system cannot be judged by a single algorithm; software analysis is a time-consuming process which typically requires lengthy interactions. In this thesis, we present a framework, IFSO (Integrated Framework for automatic/semi-automatic Software refactoring and analysis), as a foundation for automatic/semi-automatic software refactoring and analysis. Our proposed conceptual model, LSR (Layered Software Representation Model), defines an abstract representation for software using a layered approach. Each layer corresponds to a granularity level. The IFSO framework, which is built upon the LSR model for component-based software, represents software at the system level, component level, class level, method level and logic unit level. Each level can be customized by different algorithms such as cohesion metrics, design heuristics, design problem detection and operations independently. Cooperating between levels together, a global view and an interactive environment for software refactoring and analysis are presented by IFSO. A prototype was implemented for evaluation of our technology. Three case studies were developed based on the prototype: three metrics, dead code removing, low coupled unit detection.

The main goal of the work is to introduce new ideas how traditional approaches for designing an operation system and associated software can be improved to be a part of automatic software evolution. It is generally supposed that algorithms found by the genetic programming processes cannot be used for exact calculations but only for approximate solutions. Several examples of software evolution are introduced, to show that quite precise solutions can be achieved. To reach this goal, characteristics of tree-like structures with approaches based on cellular automata features are combined in a new promising technique of algorithm representation, joining benefits of both concepts. An application has been developed based on these new genetic programming concepts and it is supposed it can be a part of a future automatic software evolution process.

WebAssembly has become the fourth official web language, along with HTML, CSS and JavaScript since 2019. WebAssembly allows web browsers to execute existing programs or libraries written in other languages, such as C/C++ and Rust. In addition, WebAssembly evolves to be part of edge-cloud computing platforms. Despite being designed with security as a premise, WebAssembly is not exempt from vulnerabilities. Therefore, potential vulnerabilities and flaws are included in its distribution and execution, highlighting a software monoculture problem. On the other hand, while software diversity has been shown to mitigate monoculture, no diversification approach has been proposed for WebAssembly. This work proposes software diversity as a preemptive solution to mitigate software monoculture for WebAssembly. Besides, we provide implementations for our approaches, including a generic LLVM superdiversifier that potentially extends our ideas to other programming languages. We empirically demonstrate the impact of our approach by providing Randomization and Multivariant Execution (MVE) for WebAssembly. Our results show that our approaches can provide an automated end-to-end solution for the diversification of WebAssembly programs. The main contributions of this work are: We highlight the lack of diversification techniques for WebAssembly through an exhaustive literature review. We provide randomization and multivariant execution for WebAssembly with the implementation of two tools, CROW and MEWE respectively. We include constant inferring as a new code transformation to generate software diversification for WebAssembly. We empirically demonstrate the impact of our technique by evaluating the static and dynamic behavior of the generated diversification. Our approaches harden observable properties commonly used to conduct attacks, such as static code analysis, execution traces, and execution time. / WebAssembly har sedan 2019 blivit det fjärde officiella webbspråket, tillsammans med HTML, CSS och JavaScript sedan 2019. Detta nya språk tillåter webbläsaren att köra befintliga program eller bibliotek skrivna på andra språk, såsom C/C++ och Rust. Dessutom utvecklas WebAssembly för att vara en del av edge-cloud dator -beräkningsplattformar. Trots att WebAssembly är designatd med säkerhet i fokus som en premiss är det inte undantaget från sårbarheter. Därför ingår potentiella sårbarheter och brister i dess distribution och exekvering, vilket belyser ett av problemen med mjukvarumonokultur. MÅ andra sidan, medan mångfald av programvara har visat sig mildra monokultur, har ingen diversifieringsmetod föreslagits för WebAssembly. Denna avhandling föreslår en mångfald av programvara som en förebyggande lösning med syfte att minska programvarumonokultur för WebAssembly. Dessutom tillhandahåller vi implementeringar för våra tillvägagångssätt, däriblandinklusive en generisk LLVM- superdiversifierare som potentiellt utökar våra idéer till andra programmeringsspråk. Vi visar effekten av vårt tillvägagångssätt empiriskt genom att tillhandahålla rRandomisering och mMultivariante Exekvering (MVE) för WebAssembly. Våra resultat visar att våra tillvägagångssätt kan ge en automatiserad end-to-end lösning för diversifiering av program i WebAssembly. Detta arbetes viktigaste bidragen från detta arbete är: Vi lyfter fram bristen på diversifieringstekniker för WebAssembly genom en uttömmande litteraturgenomgång. Vi tillhandahåller en implementationeringen av två verktyg, CROW och MEWE, som genomför tillhandahåller randomisering och multivariant exekvering för WebAssembly. Vi inkluderar “constant inferring” som en ny kod-transformation för att generera mjukvarudiversifiering för WebAssembly. Vi demonstrerar empiriskt effekten av vår teknik genom att utvärdera det statiska och dynamiska beteendet hos den genererade diversifieringen. Våra metoder härdar mot observerbara egenskaper som vanligtvis används för att utföra attacker, som statisk kodanalys, exekveringsspår och exekveringstid. / <p>QC 20220909</p>

Mélanger des parties de mots est une façon qui peut sembler étonnante pour produire de nouvelles formes linguistiques. Cela est devenu une manière très utilisée pour inventer des noms pour le quotidien, les noms de marque, les noms utilisés dans les codes informatiques des logiciels, par exemple avec alicament (aliment and médicament), aspivenin (aspirer and venin). Il existe plusieurs façon de mélanger des mots pour en former d'autres, ce qui rend difficile l'analyse des mots produits. Dans cette thèse, nous nous proposons une approche d'analyse automatique des évocations de mots produits à l'aide de mélanges, en considérant des méthodes de classification de type top-k. Nous comparons trois méthodes d'analyse des parties d'un mot : n-grammes, syllabes et cellules morpho-phonologiques. Nous proposons deux algorithmes d'extraction des syllables ainsi que des méthodes d'évaluation.L'algorithme Enqualitum est proposé pour identifier les mots étant évoqués par le mot analysé. Notre proposition a été utilisée en particulier dans le domaine de l'analyse automatique en génie logiciel pour lequel nous avons proposé l'algorithme Sword pour produire un découpage pertinent des noms apparaissant dans les programmes. Les expérimentations ont démontré l'intérêt de nos propositions. / Lexical blending is amazing in the sense of morphological productivity, involving the coinage of a new lexeme by fusing parts of at least two source words. Since new things need new words, blending has become a frequent productive word creation such as smog (smoke and fog), or alicament (aliment and médicament) (a French blend word), etc. The challenge is to design methods to discover how the first source word and the second source word are combined. The thesis aims at automatic analysis blend words in order to find the source words they evoke. The contributions of the thesis can divided into two main parts. First, the contribution to automatic blend word analysis, we develop top-k classification and its evaluation framework to predict concepts of blend words. We investigate three different features of words: character N-grams, syllables and morpho-phonological stems. Moreover, we propose a novel approach to automatically identify blend source words, named Enqualitum. The experiments are conducted on both synthetic French blend words and words from a French thesaurus. Second, the contribution to software engineering application, we apply the idea of learning character patterns of identifiers to predict concepts of source codes and also introduce a method to automate semantic context in source codes. The experiments are conducted on real identifier names from open source software packages. The results show the usefulness and the effectiveness of our proposed approaches.

Η μεταπτυχιακή διπλωματική εργασία έχει ως στόχο να δημιουργήσει ένα ανοικτού κώδικα λογισμικό (scisola) -σε python-, το οποίο να παρέχει τις ακόλουθες λειτουργίες: Αυτοματοποίηση του υπολογισμού ΤΣΡ με σύνδεση στο σύστημα του SeisComP3. Αποθήκευση των αποτελεσμάτων σε βάση δεδομένων. Δυνατότητα παραμετροποίησης του λογισμικού από το χρήστη με χρήση γραφικού περιβάλλοντος (configuration). Δυνατότητα προβολής των αποτελεσμάτων με χρήση γραφικού περιβάλλοντος (review). Δυνατότητα τροποποίησης των αποτελεσμάτων βάση επιλογής του χρήστη με χρήση γραφικού περιβάλλοντος (revision). / This master thesis contributes by providing an open-source software application (scisola) -written in python-. It supports: Automatic calculation of moment tensors; the seismic event notification, station information and the corresponding waveforms are provided by the SeisComP3 system through different utilities and services like slinktool and seedlink server respectively. The moment tensor is calculated through the ISOLA software in parallel mode using multiple threads through multiprocessing python libraries for much faster calculations. Result storing in database for better data management. Extensive configuration changes based on the needs of each researcher, through a user friendly graphical interface. A graphical overview of the moment tensor calculation and the corresponding data fit. Moment tensor revision in case the user wishes to alter the automatically suggested result.

Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2017-09-13T17:19:44Z No. of bitstreams: 2 Dissertação - Vinícius Paulo Lopes de Oliveira - 2017.pdf: 2066886 bytes, checksum: c610d8e21e23795d1cea6eeca17b5e5e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-09-19T13:58:48Z (GMT) No. of bitstreams: 2 Dissertação - Vinícius Paulo Lopes de Oliveira - 2017.pdf: 2066886 bytes, checksum: c610d8e21e23795d1cea6eeca17b5e5e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-09-19T13:58:48Z (GMT). No. of bitstreams: 2 Dissertação - Vinícius Paulo Lopes de Oliveira - 2017.pdf: 2066886 bytes, checksum: c610d8e21e23795d1cea6eeca17b5e5e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-08-14 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Maintenance and software repair are responsible for most of the cost of a software in the course of its life. Software repair through genetic evolution may repair errors and improve software, reducing its high cost. GenProg is a technique that uses this approach and through patches evolution it is capable to fix errors in large and small softwares. A patch composed by low-granularity operations compromise the manipulation of these operations. These operations consist of three subspaces: operation, location of application of the operation and what the operation will apply at the location of the fault (operator, fault and fix, respectively). The recombination and mutation operators applied to a low granulation representation limits the ability of the technique to navigate in search space efficiently. It is proposed the reformulation of the representation, in order to allow greater search capability. Theoretical analysis of the representation showed that the new representation has a greater locality than the original one. Through experimentation, validation and genotypic analysis it is shown that the proposed changes have led to a better performance with respect to the original operators and parameters in terms of efficiency, in the first experiments the operator UnifSingle with memorization was 48.88% more effective than the Original operator and then the operator OPSingle_V2 was 26% more effective than the operator UnifSingle with memorization. Some characteristics of these cross-operators were observed through a genotype distance analysis and their influence on the automatic software reapair problem. The proposed mutation operator shown superior results if compared to original. Combination between operator UniSingle with memorization showed the best efficacy among all combinations of operators and parameters (28.29% superior to the best result of the original GenProg). / Manutenção e reparo de software é responsável pela maior parte do custo de um software no decorrer de sua vida. O reparo de software por meio de evolução genética pode reparar erros e/ou melhorar softwares, diminuindo seu alto custo. GenProg é uma técnica em desenvolvimento que utiliza esta abordagem e por meio de evolução de patches é capaz de reparar erros em grandes e pequenos softwares. Um patch é composto por operações de edições de baixa granularidade o que compromete a separação e edição dessas operações. Essas operações são formadas por três subespaços: operação, local da aplicação da operação e o que a operação irá aplicar no local da falha (operator, fault, fix, respectivamente). Os operadores de recombinação e mutação aplicados às representações de baixa granularidade limita a habilidade da técnica de navegar no espaço de busca de forma eficiente. É proposto neste estudo, a reformulação da representação, do operador de cruzamento e mutação a fim de permitir uma maior capacidade de busca. Análises teóricas da representação demonstraram que a nova representação possui localidade maior que a original. Por meio de experimentações, validações e análises genotípicas é mostrado que as mudanças propostas levaram a uma melhoria em relação aos operadores e parâmetros originais em termos de eficácia, sendo que nos experimentos iniciais o operador UnifSingle com memorização apresentou eficácia 45,88% superior ao melhor caso do operador Original e em seguida o operador posteriormente proposto OPSingle_V2 apresentou eficácia 26% superior ao UnifSingle com memorização. Foram observadas algumas características desses operadores de cruzamento por meio de uma análise por distância genotípica e suas influências no problema de reparo automatizado de software. O operador de mutação proposto apresentou resultados superiores ao operador de mutação original e combinado com operador UnifSingle com memorização, apresentou a melhor eficácia entre todas as combinações de operadores e parâmetros.