Técnicas de prueba avanzadas para la generación de casos de prueba

Software testing is a crucial phase in software development, particularly in contexts such as critical systems, where even minor errors can have severe consequences. The advent of Industry 4.0 brings new challenges, with software present in almost all industrial systems. Overcoming technical limitations, as well as limited development times and budgets, is a major challenge that software testing faces nowadays. Such limitations can result in insufficient attention being paid to it. The Bay of Cadiz’s industrial sector is known for its world-leading technological projects, with facilities and staff fully committed to innovation. The close relationship between these companies and the University of Cadiz allows for a constant exchange between industry and academia. This PhD thesis aims to identify the most important elements of software testing in Industry 4.0, based on close industrial experience and the latest state-of-the-art work. This allows us to break down the software testing process in a context where large teams work on large-scale, changing projects with numerous dependencies. It also allows us to estimate the percentage benefit that a solution could provide to test engineers throughout the process. Our results indicate a need for non-commercial, flexible, and adaptable solutions for the automation of software testing, capable of meeting the constantly changing needs of industry projects. This work provides a comprehensive study on the industry’s needs and motivates the development of two new solutions using state-of-the-art technologies, which are rarely present in industrial work. These results include a tool, ASkeleTon, which implements a procedure for generating test harnesses based on the Abstract Syntax Tree (AST) and a study examining the ability of the Dynamic Symbolic Execution (DSE) testing technique to generate test data capable of detecting potential faults in software. This study leads to the creation of a novel family of testing techniques, called mutationinspired symbolic execution (MISE), which combines DSE with mutation testing (MT) to produce test data capable of detecting more potential faults than DSE alone. The findings of this work can serve as a reference for future research on software testing in Industry 4.0. The solutions developed in this PhD thesis are able to automate essential tasks in software testing, resulting in significant potential benefits. These benefits are not only for the industry, but the creation of the new family of testing techniques also represents a promising line of research for the scientific community, benefiting all software projects regardless of their field of application.La prueba del software es una de las etapas más importantes durante el desarrollo de software, especialmente en determinados tipos de contextos como el de los sistemas críticos, donde el más mínimo fallo puede conllevar la más grave de las consecuencias. Nuevos paradigmas tecnológicos como la Industria 4.0 conllevan desafíos que nunca antes se habían planteado, donde el software está presente en prácticamente todos los sistemas industriales. Uno de los desafíos más importantes a los que se enfrenta la prueba del software consiste en superar las limitaciones técnicas además de los tiempos de desarrollo y presupuestos limitados, que provocan que en ocasiones no se le preste la atención que merece. El tejido industrial de la Bahía de Cádiz es conocido por sacar adelante proyectos tecnológicos punteros a nivel mundial, con unas instalaciones y un personal totalmente implicado con la innovación. Las buenas relaciones de este conjunto de empresas con la Universidad de Cádiz, sumadas a la cercanía geográfica, permiten que haya una conversación constante entre la industria y la academia. Este trabajo de tesis persigue identificar los elementos más importantes del desarrollo de la prueba del software en la Industria 4.0 en base a una experiencia industrial cercana, además de a los últimos trabajos del estado del arte. Esto permite identificar cada etapa en la que se desglosa la prueba del software en un contexto donde trabajan equipos muy grandes con proyectos de gran envergadura, cambiantes y con multitud de dependencias. Esto permite, además, estimar el porcentaje de beneficio que podría suponer una solución que ayude a los ingenieros de prueba durante todo el proceso. Gracias a los resultados de esta experiencia descubrimos que existe la necesidad de soluciones para la automatización de la prueba del software que sean no comerciales, flexibles y adaptables a las constantes necesidades cambiantes entre los proyectos de la industria. Este trabajo aporta un estudio completo sobre las necesidades de la industria en relación a la prueba del software. Los resultados motivan el desarrollo de dos nuevas soluciones que utilizan tecnologías del estado del arte, ampliamente usadas en trabajos académicos, pero raramente presentes en trabajos industriales. En este sentido, se presentan dos resultados principales que incluyen una herramienta que implementa un procedimiento para la generación de arneses de prueba basada en el Árbol de Sintaxis Abstracta (AST) a la que llamamos ASkeleTon y un estudio donde se comprueba la capacidad de la técnica de pruebas Ejecución Simbólica Dinámica (DSE, por sus siglas en inglés) para generar datos de prueba capaces de detectar fallos potenciales en el software. Este estudio deriva en la creación de una novedosa familia de técnicas de prueba a la que llamamos mutation-inspired symbolic execution (MISE) que combina DSE con la prueba de mutaciones (MT, por sus siglas en inglés) para conseguir un conjunto de datos de prueba capaz de detectar más fallos potenciales que DSE por sí sola. Las soluciones desarrolladas en este trabajo de tesis son capaces de automatizar parte de la prueba del software, resultando en unos beneficios potenciales importantes. No solo se aportan beneficios a la industria, sino que la creación de la nueva familia de técnicas de prueba supone una línea de investigación prometedora para la comunidad científica, siendo beneficiados todos los proyectos software independientemente de su ámbito de aplicación

Clinical-pathological study on β-APP, IL-1β, GFAP, NFL, Spectrin II, 8OHdG, TUNEL, miR-21, miR-16, miR-92 expressions to verify DAI-diagnosis, grade and prognosis

Traumatic brain injury (TBI) is one of the most important death and disability cause, involving substantial costs, also in economic terms, when considering the young age of the involved subject. Aim of this paper is to report a series of patients treated at our institutions, to verify neurological results at six months or survival; in fatal cases we searched for βAPP, GFAP, IL-1β, NFL, Spectrin II, TUNEL and miR-21, miR-16, and miR-92 expressions in brain samples, to verify DAI diagnosis and grade as strong predictor of survival and inflammatory response. Concentrations of 8OHdG as measurement of oxidative stress was performed. Immunoreaction of β-APP, IL-1β, GFAP, NFL, Spectrin II and 8OHdG were significantly increased in the TBI group with respect to control group subjects. Cell apoptosis, measured by TUNEL assay, were significantly higher in the study group than control cases. Results indicated that miR-21, miR-92 and miR-16 have a high predictive power in discriminating trauma brain cases from controls and could represent promising biomarkers as strong predictor of survival, and for the diagnosis of postmortem traumatic brain injury

Acceptability-Oriented Computing

We discuss a new approach to the construction of software systems. Instead of attempting to build a system that is as free of errors as possible, the designer instead identifies key properties that the execution must satisfy to be acceptable to its users. Together, these properties define the acceptability envelope of the system: the region that it must stay within to remain acceptable. The developer then augments the system with a layered set of components, each of which enforces one of the acceptability properties. The potential advantages of this approach include more flexible, resilient systems that recover from errors and behave acceptably across a wide range of operating environments, an appropriately prioritized investment of engineering resources, and the ability to productively incorporate unreliable components into the final software system.Singapore-MIT Alliance (SMA

Parallel Architectures for Planetary Exploration Requirements (PAPER)

The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified

Feasibility of improving risk stratification in the inherited cardiac conditions

Fatal ventricular arrhythmias can occur in patients with Hypertrophic Cardiomyopathy, Brugada Syndrome and rarely in patients with normal cardiac investigations. Despite very different pathogeneses, we hypothesised that a common electrophysiological substrate precipitates these arrhythmias and could be used as a marker for risk stratification. In Chapter 3 of this thesis, we found that fewer than half the cardiac arrest survivors with Brugada Syndrome would have been offered prophylactic defibrillators based on current risk scoring, highlighting the need for better risk stratification. Our group previously used a commercially available 252-electrode vest which constructs ventricular electrograms onto a CT image of the heart to show exercise related differences in high-risk patients. In Chapter 4, we applied this method to Brugada patients, but could not reproduce prior results. Further investigation revealed periodic changes in activation patterns after exercise that could explain this discrepancy. An alternative matrix approach was developed to overcome this problem. Exercise induced conduction heterogeneity differentiated Brugada patients from unaffected controls, but not those surviving cardiac arrest. However, if considered alongside spontaneous type 1 ECG and syncope, inducible conduction heterogeneity markedly improved identification of Brugada cardiac arrest survivors. In Chapter 5 the method was shown to differentiate idiopathic ventricular fibrillation patients from those fully recovered from acute ischaemic cardiac arrest, implying a permanent electrophysiological abnormality. In Chapter 8, we showed prolonged mean local activation times and activation-recovery intervals in hypertrophic cardiomyopathy cardiac arrest survivors compared to those without previous ventricular arrhythmia. These metrics were combined into both logistic regression and support vector machine models to strongly differentiate the groups. We concluded that electrophysiological changes could identify cardiac arrest survivors in various cardiac conditions, but a single factor common pathway was not established. Prospective studies are required to determine if using these parameters could enhance current risk stratification for sudden death.Open Acces

Test-case reduction for C compiler bugs

ManuscriptTo report a compiler bug, one must often find a small test case that triggers the bug. The existing approach to automated test-case reduction, delta debugging, works by removing substrings of the original input; the result is a concatenation of substrings that delta cannot remove. We have found this approach less than ideal for reducing C programs because it typically yields test cases that are too large or even invalid (relying on undefined behavior). To obtain small and valid test cases consistently, we designed and implemented three new, domain-specific test-case reducers. The best of these is based on a novel framework in which a generic fixpoint computation invokes modular transformations that perform reduction operations. This reducer produces outputs that are, on average, more than 25 times smaller than those produced by our other reducers or by the existing reducer that is most commonly used by compiler developers. We conclude that effective program reduction requires more than straightforward delta debugging

Catala: A Programming Language for the Law

Law at large underpins modern society, codifying and governing many aspects of citizens' daily lives. Oftentimes, law is subject to interpretation, debate and challenges throughout various courts and jurisdictions. But in some other areas, law leaves little room for interpretation, and essentially aims to rigorously describe a computation, a decision procedure or, simply said, an algorithm. Unfortunately, prose remains a woefully inadequate tool for the job. The lack of formalism leaves room for ambiguities; the structure of legal statutes, with many paragraphs and sub-sections spread across multiple pages, makes it hard to compute the intended outcome of the algorithm underlying a given text; and, as with any other piece of poorly-specified critical software, the use of informal language leaves corner cases unaddressed. We introduce Catala, a new programming language that we specifically designed to allow a straightforward and systematic translation of statutory law into an executable implementation. Catala aims to bring together lawyers and programmers through a shared medium, which together they can understand, edit and evolve, bridging a gap that often results in dramatically incorrect implementations of the law. We have implemented a compiler for Catala, and have proven the correctness of its core compilation steps using the F* proof assistant. We evaluate Catala on several legal texts that are algorithms in disguise, notably section 121 of the US federal income tax and the byzantine French family benefits; in doing so, we uncover a bug in the official implementation. We observe as a consequence of the formalization process that using Catala enables rich interactions between lawyers and programmers, leading to a greater understanding of the original legislative intent, while producing a correct-by-construction executable specification reusable by the greater software ecosystem

Technology Development Standardization and Evaluation in Pulmonary Medicine

book chapterBiomedical Informatic