Due to complexity in software, manual testing is not enough to cover all relevant behaviours of it. A different approach to this problem is Symbolic Execution. Symbolic Execution is a software testing technique that tests all possible inputs of a program in the hopes of finding all bugs. Due to the often exponential increase in possible program paths, Symbolic Execution usually cannot exhaustively test a program. To nevertheless cover the most important or error prone areas of a program, search strategies that prioritize these areas are used. Such search strategies navigate the program execution tree, analysing which paths seem interesting enough to execute and which to prune. These strategies are typically grouped into two categories, general purpose searchers, with no specific target but the aim to cover the whole program and targeted searchers which can be directed towards specific areas of interest. To analyse how different searching strategies in Symbolic Execution affect the finding of errors and how they can be combined to improve the general outcome, the experiments conducted consist of several different searchers and combinations of them, each run on the same set of test targets. This set of test targets contains amongst others one of the most heavily tested sets of open source tools, the GNU Coreutils. With these, the different strategies are compared in distinct categories like the total number of errors found or the percentage of covered code. With the results from this thesis the potential of targeted searchers is shown, with an example implementation of the Pathscore-Relevance strategy. Further, the results obtained from the conducted experiments endorse the use of combinations of search strategies. It is also shown that, even simple combinations of strategies can be highly effective. For example, interleaving strategies can provide good results even if the underlying searchers might not perform well by themselves. / På grund av programvarukomplexitet är manuell testning inte tillräcklig för att täcka alla relevanta beteenden av programvaror. Ett annat tillvägagångssätt till detta problem är Symbolisk Exekvering (Symbolic Execution). Symbolisk Exekvering är en mjukvarutestningsteknik som testar alla möjliga inmatningari ett program i hopp om att hitta alla buggar. På grund av den ofta exponentiella ökningeni möjliga programsökvägar kan Symbolisk Exekvering vanligen inte uttömmande testa ettprogram. För att ändå täcka de viktigaste eller felbenägna områdena i ett program, används sökstrategier som prioriterar dessa områden. Sådana sökstrategier navigerar i programexekveringsträdet genom att analysera vilka sökvägar som verkar intressanta nog att utföra och vilka att beskära. Dessa strategier grupperas vanligtvis i två kategorier, sökare med allmänt syfte, utan något specifikt mål förutom att täcka hela programmet, och riktade sökare som kan riktas mot specifika intresseområden. För att analysera hur olika sökstrategier i Symbolisk Exekvering påverkar upptäckandetav fel och hur de kan kombineras för att förbättra det allmänna utfallet, bestod de experimentsom utfördes av flera olika sökare och kombinationer av dem, som alla kördes på samma uppsättning av testmål. Denna uppsättning av testmål innehöll bland annat en av de mest testade uppsättningarna av öppen källkod-verktyg, GNU Coreutils. Med dessa jämfördes de olika strategierna i distinkta kategorier såsom det totala antalet fel som hittats eller procenttalet av täckt kod. Med resultaten från denna avhandling visas potentialen hos riktade sökare, med ett exempeli form av implementeringen av Pathscore-Relevance strategin. Vidare stöder resultaten som erhållits från de utförda experimenten användningen av sökstrategikombinationer. Det visas också att även enkla kombinationer av strategier kan vara mycket effektiva.Interleaving-strategier kan till exempel ge bra resultat även om de underliggande sökarna kanske inte fungerar bra själva.

Testing is the dominant verification technique used in the software industry today. The use of automatic test case execution increases, but the creation of test cases remains manual and thus error prone and expensive. To automate generation and selection of test cases, model-based testing techniques have been suggested. In this thesis two central problems in model-based testing are addressed: the problem of how to formally specify coverage criteria, and the problem of how to generate a test suite from a formal timed system model, such that the test suite satisfies a given coverage criterion. We use model checking techniques to explore the state-space of a model until a set of traces is found that together satisfy the coverage criterion. A key observation is that a coverage criterion can be viewed as consisting of a set of items, which we call coverage items. Each coverage item can be treated as a separate reachability problem. Based on our view of coverage items we define a language, in the form of parameterized observer automata, to formally describe coverage criteria. We show that the language is expressive enough to describe a variety of common coverage criteria described in the literature. Two algorithms for test case generation with observer automata are presented. The first algorithm returns a trace that satisfies all coverage items with a minimum cost. We use this algorithm to generate a test suite with minimal execution time. The second algorithm explores only states that may increase the already found set of coverage items. This algorithm works well together with observer automata. The developed techniques have been implemented in the tool CoVer. The tool has been used in a case study together with Ericsson where a WAP gateway has been tested. The case study shows that the techniques have industrial strength.

Un système embarqué est un système électronique et informatique autonome dédié à une tâche précise. Dans le secteur de l’automobile, le nombre de systèmes embarqués dans les voitures a considérablement augmenté au cours de ces dernières années et va certainement continuer à augmenter. Ces systèmes sont dédiés entre autres, à la sécurité, au confort de conduite,et à l’assistance à la conduite. Cette croissance des systèmes est associée avec une croissance en taille des logiciels qui les contrôlent. En conséquence, leur gestion(système et logiciel) devient de plus en plus complexe et problématique. Par ailleurs, la concurrence dans le secteur automobile est très féroce et les temps de mise sur le marché sont de plus en plus courts. Ainsi, pour garantir le bon fonctionnement des systèmes en général et du logiciel en particulier, étant donné leur complexité,et aussi les délais courts de mise sur le marché des produits automobiles, de nouvelles méthodes de développement doivent être considérées. Ainsi, de nombreuses méthodes de développement, incluant de nouveaux standards (de développement) et approches automatiques ont émergé au cours de ces dernières années. Dans le cas particulier de la vérification et validation de logiciel, une des activités critiques qui a connu une avancée significative est la génération de cas de test, avec l’avènement d’approches automatiques.Malgré cela, ces approches peinent souvent à s’imposer en milieu industriel. Une des raisons est que celles ci sont souvent peu adaptées ou peu utilisées dans un contexte industriel.Dans ce contexte, cette thèse vise à proposer une approche de vérification et de validation de logiciels embarqués, basée sur la génération automatique de cas de test. Pour cela, nous avons mis en place une approche permettant de représenter sous forme de modèles abstraits les spécifications d’un logiciel, puis de générer à partir de ces modèles un ensemble de cas de test en considérant en particulier le critère de couverture MC/DC. / An embedded system is a system that performs a specific task and has a computer embedded inside. In the automotive sector, the amount of embedded systems in the vehicle has risen dramatically in recent years and is set to increase. They deal essentially with safety, comfort, and driving assistance. Furthermore, the increase in number and complexity of the systems is associated with a growth in software. As a consequence, their management (system and software) have become more and more complex and problematic. Also, the competition and time-to-market in the automotive industry are very tough. Thus, to guarantee the efficiency and reliability of the embedded systems in the vehicle in general and the software in particular, in view of the complexity as well as the competition and time-to-market law, new development methods should be considered. Therefore, new development methods including new standards, and automatic approaches have emerged over the last years. In the particular case of embedded software verification and validation, one of the most critical activities that has experienced a significant progress is test case generation with the advent of automatic approaches. Despite this, these approaches are not widely used or are not well adapted in industrial context. In that context, our goal in this PhD. thesis is to propose a new verification and validation approach, based on automatic test case generation of embedded embedded. Thus, we have set up an approach that automatically generates test cases, with respect to the MC/DC criterion, from abstract models of the software specifications expressed in the form of state-transition models.

Cette thèse s’est attaquée sous diverses formes au test automatique des services Web : une première partie est consacrée au test fonctionnel à travers le test de robustesse. La seconde partie étend les travaux précédents pour le test de propriétés non fonctionnelles, telles que les propriétés de testabilité et de sécurité. Nous avons abordé ces problématiques à la fois d’un point de vue théorique et pratique. Nous avons pour cela proposé une nouvelle méthode de test automatique de robustesse des services Web non composés, à savoir les services Web persistants (stateful) et ceux non persistants. Cette méthode consiste à évaluer la robustesse d’un service Web par rapport aux opérations déclarées dans sa description WSDL, en examinant les réponses reçues lorsque ces opérations sont invoquées avec des aléas et en prenant en compte l’environnement SOAP. Les services Web persistants sont modélisés grâce aux systèmes symboliques. Notre méthode de test de robustesse dédiée aux services Web persistants consiste à compléter la spécification du service Web afin de décrire l’ensemble des comportements corrects et incorrects. Puis, en utilisant cette spécification complétée, les services Web sont testés en y intégrant des aléas. Un verdict est ensuite rendu. Nous avons aussi réalisé une étude sur la testabilité des services Web composés avec le langage BPEL. Nous avons décrit précisément les problèmes liés à l’observabilité qui réduisent la faisabilité du test de services Web. Par conséquent, nous avons évalué des facteurs de la testabilité et proposé des solutions afin d’améliorer cette dernière. Pour cela, nous avons proposé une approche permettant, en premier lieu, de transformer la spécification ABPEL en STS. Cette transformation consiste à convertir successivement et de façon récursive chaque activité structurée en un graphe de sous-activités. Ensuite, nous avons proposé des algorithmes d’améliorations permettant de réduire ces problèmes de testabilité. Finalement, nous avons présenté une méthode de test de sécurité des services Web persistants. Cette dernière consiste à évaluer quelques propriétés de sécurité, tel que l’authentification, l’autorisation et la disponibilité, grâce à un ensemble de règles. Ces règles ont été crée, avec le langage formel Nomad. Cette méthodologie de test consiste d’abord à transformer ces règles en objectifs de test en se basant sur la description WSDL, ensuite à compléter, en parallèle, la spécification du service Web persistant et enfin à effectuer le produit synchronisé afin de générer les cas de test. / This PhD thesis focuses on diverse forms of automated Web services testing : on the one hand, is dedicated to functional testing through robustness testing. On the other hand, is extends previous works on the non-functional properties testing, such as the testability and security properties. We have been exploring these issues both from a theoretical and practical perspective. We proposed a robustness testing method which generates and executes test cases automatically from WSDL descriptions. We analyze the Web service over hazards to find those which may be used for testing. We show that few hazards can be really handled and then we improve the robustness issue detection by separating the SOAP processor behavior from the Web service one. Stateful Web services are modeled with Symbolic Systems. A second method dedicated to stateful Web services consists in completing the Web service specification to describe correct and incorrect behaviors. By using this completed specification, the Web services are tested with relevant hazards and a verdict is returned. We study the BPEL testability on a well-known testability criterion called observability. To evaluate, we have chosen to transform ABPEL specifications into STS to apply existing methods. Then, from STS testability issues, we deduce some patterns of ABPEL testability degradation. These latter help to finally propose testability enhancement methods of ABPEL specifications. Finally, we proposed a security testing method for stateful Web Services. We define some specific security rules with the Nomad language. Afterwards, we construct test cases from a symbolic specification and test purposes derived from the previous rules. Moreover, to validate our proposal, we have applied our testing approach on real size case studies.

Despite much scepticism and problems for its adoption, the Model-Driven Development (MDD) is being used and improved to provide many inherent benefits for industry. One of its greatest benefits is the ability to handle the complexity of software development by raising the abstraction level. Models are expressed using concepts that are not related to a specific implementation technology (e.g. Unified Modelling Language -UML, Object Constraint Language -OCL, Action Language for Foundational UML -ALF), which means that the models can be easier to specify, maintain and document. As in Model-Driven Engineering (MDE), the primary artefacts are the conceptual models, efforts are focused on their creation, testing and evolution at different levels of abstraction through transformations because if a conceptual schema has defects, these are passed on to the following stages, including coding. Thus, one of the challenges for researchers and developers in Model-Driven Development is being able to identify defects early on, at the conceptual schema level, as this helps reduce development costs and improve software quality. Over the last decade, little research work has been performed in this area. Some of the causes of this are the high theoretical complexity of testing conceptual schemas and the lack of adequate software support. This research area thus admits new methods and techniques, facing challenges such as generation of test cases using information external to the conceptual schemas (i.e. requirements), the measurement of possible automation, selection and prioritization of test cases, the need for an efficient support tool using standard semantics, the opportune feedback to support the software quality assurance process and facilitate making decisions based on the analysis and interpretation of the results. The aim of this thesis is to mitigate some of the problems that affect conceptual schema validation by providing a novel testing-based validation framework based on Model-Driven Development. The use of MDD improves abstraction, automation and reuse, which allows us to alleviate the complexity of our validation framework. Furthermore, by leveraging MDD techniques (such as metamodeling, model transformations, and models at runtime), our framework supports four phases of the testing process: test design, test case generation, test case execution and the evaluation of the results. In order to provide software support for our proposal, we developed the CoSTest ALF-based testing environment. To ensure that CoSTest offers the necessary functionality, we first identified a set of functional requirements. Then, after these requirements were identified, we defined the architecture and testing environment of the validation framework, and finally we implemented the architecture in the Eclipse context. CoSTest has been developed to test several properties on the executable model, such as syntactic correctness (i.e. all the elements in the model conform to the syntax of the language in which it is described), consistency between the structural and behavioural parts (its integrity constraints) and completeness (i.e. all possible changes on the system state can be performed through the execution of the operations defined in the executable model). For defective models, the CoSTest report returns a meaningful feedback that helps locate and repair any defects detected. / A pesar del escepticismo y dificultades en su adopción, el Desarrollo Orientado por Modelos (MDD, por sus siglas en inglés) está siendo usado y mejorado para proveer muchos beneficios inherentes a la industria. Uno de sus mayores beneficios es la capacidad de manejar la complejidad del desarrollo de software elevando el nivel de abstracción. Los modelos se expresan utilizando conceptos que no están relacionados con una tecnología de implementación específica (por ejemplo, Lenguaje de Modelado Unificado -UML, Lenguaje de Restricción de Objetos -OCL, Lenguaje de Acción para el Foundational UML - ALF), lo que significa que los modelos pueden ser más fáciles de especificar, mantener y documentar. Debido a que en una Ingeniería dirigida por modelos (MDE), los artefactos primarios son los modelos conceptuales, los esfuerzos se centran en su creación, prueba y evolución a diferentes niveles de abstracción a través de transformaciones, porque si un esquema conceptual tiene defectos, éstos se pasan a las siguientes etapas, incluida la codificación. Por lo tanto, uno de los retos para los investigadores y desarrolladores in MDD es poder identificar los defectos temprano, a nivel de esquemas conceptuales, ya que esto ayudaría a reducir los costos de desarrollo y mejorar la calidad del software. Durante la última década, pocos trabajos de investigación se han realizado en esta área. Algunas de las causas de esta realidad son la alta complejidad teórica de probar esquemas conceptuales y la falta de soporte de software adecuado. Por lo tanto, este área de investigación admite nuevos métodos y técnicas, enfrentando retos como la generación de casos de prueba utilizando información externa a los esquemas conceptuales (es decir, los requisitos), la medición de una posible automatización, selección y priorización de casos de prueba, la necesidad de una herramienta de soporte eficiente que utilice una semántica estándar, la retroalimentación oportuna para apoyar el proceso de aseguramiento de la calidad del software y facilitar la toma de decisiones basadas en el análisis y la interpretación de los resultados. El objetivo de esta tesis es mitigar algunos de los problemas que afectan la validación de los esquemas conceptuales, proporcionando un nuevo marco de validación basado en pruebas que fue construido usando un desarrollo dirigido por modelos. El uso de MDD permite un aumento en la abstracción, automatización y reutilización que nos permite aliviar la complejidad de nuestro marco de validación. Además, al aprovechar las técnicas MDD (como el metamodelado, las transformaciones de modelos y los modelos en tiempo de ejecución), nuestro marco soporta cuatro fases del proceso de prueba: diseño de pruebas, generación de casos de prueba, ejecución de casos de prueba y la evaluación de los resultados. Con el fin de proporcionar soporte de software para nuestra propuesta, hemos desarrollado CoSTest, un entorno de pruebas basado en el lenguaje ALF. Para asegurar que CoSTest ofrece la funcionalidad necesaria, primero identificamos un conjunto de requisitos funcionales. Luego, después de identificar estos requisitos, definimos la arquitectura y el ambiente de pruebas de nuestro marco de validación y, finalmente, implementamos la arquitectura en el contexto de Eclipse. CoSTest ha sido desarrollado para probar varias propiedades sobre el modelo ejecutable como la corrección sintáctica (es decir, todos los elementos del modelo se ajustan a la sintaxis del lenguaje en el que se describe), consistencia entre la parte estructural y el comportamiento (sus restricciones de integridad) y completitud (es decir, todos los cambios posibles en el estado del sistema se pueden realizar a través de la ejecución de las operaciones definidas en el modelo ejecutable). Para los modelos defectuosos, el informe de CoSTest devuelve una retroalimentación significativa que ayuda a localizar y reparar los defectos detec / A pesar de l'escepticisme i les dificultats en la seua adopció, el Desenvolupament Orientat per Models (MDD, segons les sigles en anglès) està sent usat i millorat per tal de proveir molts beneficis potencials inherents a l' indústria. Un dels majors beneficis és la capacitat de manejar la complexitat del desenvolupament del programari elevant el nivell d'abstracció. Els models s'expressen mitjançant conceptes que no estan relacionats amb una tecnologia d'implementació específica (per exemple, el Llenguatge de Modelat Unificat - UML, Llenguatge de Restricció d'Objectes -OCL, Llenguatge d'Acció per al Foundational UML - ALF), el que significa que els models poder ser més fàcils d'especificar, mantindre i documentar. A causa de que en una Enginyeria dirigida per models (MDE), els artefactes primaris són els models conceptuals, els esforços es centren en la seua creació, prova i evolució a diferents nivells d'abstracció mitjançant transformacions, perquè si un esquema conceptual té defectes, aquestos es passen a les següents etapes, inclosa la codificació. Per tant, un del reptes per als investigadors i desenvolupadors en MDD és poder identificar els defectes des del principi, a nivell de esquemes conceptuals, perquè açò ajudaria a reduir els costos de desenvolupament i millora de la qualitat del programari. Durant l'última dècada, pocs treballs d'investigació s'han fet en aquesta àrea. Algunes de les causes d'aquesta realitat són l'alta complexitat teòrica de provar esquemes conceptuals i la falta de suport de programari adequat. Per tant, aquesta àrea d'investigació admet nous mètodes i tècniques, enfrontant reptes com la generació de casos de prova mitjançant informació externa als esquemes conceptuals (es a dir, requisits), la medició de una possible automatització, selecció i priorització de casos de prova, la necessitat de una ferramenta de suport rentable que utilitze una semàntica estàndard, la retroalimentació oportuna per suportar el procés d'assegurament de la qualitat del programari i la facilitat per a prendre decisions basades en l'anàlisi i la interpretació dels resultats. En aquesta tesi intentem mitigar alguns dels problemes que afecten a la validació dels esquemes conceptuals, proporcionant un nou marc de validació basat en proves que va ser construït mitjançant un desenvolupament dirigit per models. L'ús de MDD permet un augment en l'abstracció, automatització i reutilització que ens permet alleujar la complexitat del nostre marc de validació. A més a més, al aprofitar les tècniques MDD (com el metamodelat, les transformacions de models i els models en temps d'execució), el nostre marc suporta quatre fases del procés de prova: disseny, generació i execució de casos de prova, així com l'avaluació de resultats del procés de prova. Amb la finalitat de proporcionar suport de programari per a la nostra proposta, hem desenvolupat un entorn de proves basat en el llenguatge ALF que s'anomena CoSTest. Per tal d'assegurar que CoSTest ofereix la funcionalitat necessària, identifiquem un conjunt de requisits funcionals abans de desenvolupar la ferramenta. Després d'identificar aquestos requisits, definim l'arquitectura i l'ambient de proves del nostre marc de validació, i finalment, implementem l'arquitectura en el context Eclipse. CoSTest ha sigut desenvolupat per provar diverses propietats sobre el model executable com la correcció sintàctica (és a dir, tots els elements del model s'ajusten a la sintaxi del llenguatge en el que es descriu), consistència antre la part estructural i el comportament (les seues restriccions d'integritat) i completitud (és a dir, tots els canvis possibles en l'estat del sistema es poden realitzar mitjançant l'execució de les operacions definides en el model executable). Per als models defectuosos, l'informe de CoSTest retorna una retroalimentació significativa que ajuda a localitzar i reparar els defectes dete / Granda Juca, MF. (2017). Testing-Based Conceptual Schema Validation in a Model-Driven Environment [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/89091 / TESIS

Software testing is a very important phase in software development as it minimize risks ina software system, however, it consumes time and can be very expensive. With automatictest case generation time consumption and cost can be reduced. Model-based testing isa method to test a software system with a model of the systems behaviour. Automatictest case generation is often considered a favorable support in model-based testing. In thiswork, the concept of model-based testing is explored along with testing the embedded partof a water-level measurement system (WLM) to investigate the efficiency of model-basedtesting on a software system. As a result of this, a model-based testing tool, MoMut::UMLis used to generate the test-cases on the UML model of WLM system that is built ina UML modeling environment, Eclipse-Papyrus. However, MoMut::UML implements aspecial type of model-based testing technique, model-based mutation testing; that injectsfaults in the UML model, and generates test-data on the fault-based model. By this, thebehaviour of system-under-test, only the UML model of water-level measurement system,is tested.

Unit testing plays a crucial role in ensuring the quality and reliability of software systems. However, manual testing can often be a slow and time-consuming process. With current advancements in artificial intelligence (AI), new tools have emerged for automated unit testing to address this issue. But how do these new AI tools compare to conventional automated unit test generation tools? To answer this question, we compared two state-of-the-art conventional unit test tools (EVOSUITE and RANDOOP) with the sole commercially available AI-based unit test tool (DIFFBLUE COVER) for Java. We tested them on 10 sample classes from 3 real-life projects provided by the Defects4J dataset to evaluate their performance regarding code coverage, mutation score, and fault detection. The results showed that EVOSUITE achieved the highest code coverage, averaging 89%, while RANDOOP and DIFFBLUE COVER achieved similar results, averaging 63%. In terms of mutation score, DIFFBLUE COVER had the lowest average score of 40%, while EVOSUITE and RANDOOP scored 67% and 50%, respectively. For fault detection, EVOSUITE and RANDOOP detected a higher number of bugs (7 out of 10 and 5 out of 10, respectively) compared to DIFFBLUE COVER, which found only 4 out of 10. Although the AI-based tool was outperformed in all three criteria, it still shows promise by being able to achieve adequate results, in some cases even surpassing the conventional tools while generating a significantly smaller number of total assertions and more comprehensive tests. Nonetheless, the study acknowledges its limitations in terms of the restricted number of AI-based tools used and the small number of projects utilized from Defects4J.

As the field of computer science continues to grow, the number of students enrolled in related programs will grow as well. Though one-on-one tutoring is one of the more effective means of teaching, computer science instructors will have less and less time to devote to individual students. To address this growing concern, many tools that automate parts of an instructor’s job have been proposed. These tools can assist instructors in presenting concepts and grading student work, and they can help students learn to program more effectively. A growing group of intelligent tutoring systems attempts to tie all of this functionality into a single tool that is meant to be used throughout an entire CS course or series of courses. To contribute to this emerging area, the Factoring Problem Generator (FPG) is presented in this work. The FPG creates and grades problems in C in which students search for and extract blocks of repeated code into individual functions, learning to utilize parameters and return values as they do so. The problems created by the FPG are highly configurable by instructors such that the difficulty can be finely tuned to suit students’ individual needs. Instructors can choose whether or not to include arrays, pointers, certain elemental data types, certain operators, or certain kinds of statements, among other things. The FPG is additionally capable of generating a set of test cases for each generated problem. These test cases fully exercise students’ solutions by covering all branches of execution, and they ensure that program functionality does not change as students factor code into functions. Initial experimentation with the system has suggested that the FPG can be integrated into a beginning CS curriculum and with further refinement could become a standard tool in the CS classroom.

Context: Testing is an important activity in software development and is typically estimated to account for nearly half of the efforts in the software development cycle. This puts a great demand on improving the artifacts involved in this task such as the test cases and test suites (a collection of test cases).  Objective: When executing test programs, it is typical to record runtime information associated with the test cases in the form of test execution logs or traces. The aim of this work is to explore how this information can be utilized to improve the software testing process. To this end, two main aspects are investigated which are (1) in the context of test case generation and (2) in the context of different optimizations regarding existing test suites. Furthermore, the role of the logs regarding fault localization in connection with improving the existing test suites is investigated. Method: A systematic literature review is conducted to investigate, identify and analyze the existing literature on test case generation and test suite optimization that utilizes the test execution logs. Results: After a rigorous search in six digital databases, 26 primary studies were identified. 5 of the selected papers propose approaches in the context of test data generation, 8 papers suggest test case prioritization (TCP) techniques, 4 papers discuss approaches in test case selection (TCS), and 5 papers propose approaches in test suite minimization (TSM). Furthermore, we identified, 3 papers that discuss fault localization, and one paper that discussed the decomposition of large test cases into smaller single purpose test cases using the logs from previous test executions. Conclusion: The test execution logs are a useful source of information for different testing activities. Regarding test case generation, the main theme observed is the use of genetic algorithms in attempting to generate appropriate test cases when the alternative might have been to use random test data generation methods. When it comes to improving existing test suites several approaches within TCP, TCS and TSM such as similarity-based, modification-based, cluster-based, and search-based were put forward by the authors of the selected primary studies. Furthermore, several fault localization techniques using the logs were suggested.

This study investigates the utilization of Large Language Models for Test Case Generation. The study uses the Large Language model and Embedding model provided by Llama, specifically Llama2 of size 7B, to generate test cases given a defined input. The study involves an implementation that uses customization techniques called Retrieval Augmented Generation (RAG) and Prompt Engineering. RAG is a method that in this study, stores organisation information locally, which is used to create test cases. This stored data is used as complementary data apart from the pre-trained data that the large language model has already trained on. By using this method, the implementation can gather specific organisation data and therefore have a greater understanding of the required domains. The objective of the study is to investigate how AI-driven test case generation impacts the overall software quality and development efficiency. This is evaluated by comparing the output of the AI-based system, to manually created test cases, as this is the company standard at the time of the study. The AI-driven test cases are analyzed mainly in the form of coverage and time, meaning that we compare to which degree the AI system can generate test cases compared to the manually created test case. Likewise, time is taken into consideration to understand how the development efficiency is affected. The results reveal that by using Retrieval Augmented Generationin combination with Prompt Engineering, the system is able to identify test cases to a certain degree. The results show that 66.67% of a specific project was identified using the AI, however, minor noise could appear and results might differ depending on the project’s complexity. Overall the results revealed how the system can positively impact the development efficiency and could also be argued to have a positive effect on the software quality. However, it is important to understand that the implementation as its current stage, is not sufficient enough to be used independently, but should rather be used as a tool to more efficiently create test cases.