Automatically Discovering, Reporting and Reproducing Android Application Crashes

Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we introduce a novel, automated approach called CRASHSCOPE. This tool explores a given Android app using systematic input generation, according to several strategies informed by static and dynamic analyses, with the intrinsic goal of triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented crash report containing screenshots, detailed crash reproduction steps, the captured exception stack trace, and a fully replayable script that automatically reproduces the crash on a target device(s). We evaluated CRASHSCOPE's effectiveness in discovering crashes as compared to five state-of-the-art Android input generation tools on 61 applications. The results demonstrate that CRASHSCOPE performs about as well as current tools for detecting crashes and provides more detailed fault information. Additionally, in a study analyzing eight real-world Android app crashes, we found that CRASHSCOPE's reports are easily readable and allow for reliable reproduction of crashes by presenting more explicit information than human written reports.Comment: 12 pages, in Proceedings of 9th IEEE International Conference on Software Testing, Verification and Validation (ICST'16), Chicago, IL, April 10-15, 2016, pp. 33-4

Implementación de placas de corte para la optimización de costos de producción en el proceso de acondicionado de fresa congelada en una empresa agroexportadora

Publicación a texto completo no autorizada por el autorRealiza un estudio exploratorio y experimental de la reducción de costos de producción mediante la implementación de placas en la operación de corte/deshojado de fresas para congelado en una empresa agroexportadora. Se elabora prototipos de las placas de corte que son adaptados a una de las líneas productivas para la observación y recopilación de datos, tomando un grupo de 32 operarios como muestra de control con el uso de las placas durante un mes de proceso.Tesi

An exploratory study of bug-introducing changes: what happens when bugs are introduced in open source software?

Context: Many studies consider the relation between individual aspects and bug-introduction, e.g., software testing and code review. Due to the design of the studies the results are usually only about correlations as interactions or interventions are not considered. Objective: Within this study, we want to narrow this gap and provide a broad empirical view on aspects of software development and their relation to bug-introducing changes. Method: We consider the bugs, the type of work when the bug was introduced, aspects of the build process, code review, software tests, and any other discussion related to the bug that we can identify. We use a qualitative approach that first describes variables of the development process and then groups the variables based on their relations. From these groups, we can induce how their (pair-wise) interactions affect bug-introducing changes.Comment: Registered Report with Continuity Acceptance (CA) for submission to Empirical Software Engineering granted by RR-Committee of the MSR'2

On Using Information Retrieval to Recommend Machine Learning Good Practices for Software Engineers

Machine learning (ML) is nowadays widely used for different purposes and in several disciplines. From self-driving cars to automated medical diagnosis, machine learning models extensively support users' daily activities, and software engineering tasks are no exception. Not embracing good ML practices may lead to pitfalls that hinder the performance of an ML system and potentially lead to unexpected results. Despite the existence of documentation and literature about ML best practices, many non-ML experts turn towards gray literature like blogs and Q&A systems when looking for help and guidance when implementing ML systems. To better aid users in distilling relevant knowledge from such sources, we propose a recommender system that recommends ML practices based on the user's context. As a first step in creating a recommender system for machine learning practices, we implemented Idaka. A tool that provides two different approaches for retrieving/generating ML best practices: i) an information retrieval (IR) engine and ii) a large language model. The IR-engine uses BM25 as the algorithm for retrieving the practices, and a large language model, in our case Alpaca. The platform has been designed to allow comparative studies of best practices retrieval tools. Idaka is publicly available at GitHub: https://bit.ly/idaka. Video: https://youtu.be/cEb-AhIPxnM.Comment: Accepted for Publication at ESEC/FSE demonstrations trac

Exploring the Security Awareness of the Python and JavaScript Open Source Communities

Software security is undoubtedly a major concern in today's software engineering. Although the level of awareness of security issues is often high, practical experiences show that neither preventive actions nor reactions to possible issues are always addressed properly in reality. By analyzing large quantities of commits in the open-source communities, we can categorize the vulnerabilities mitigated by the developers and study their distribution, resolution time, etc. to learn and improve security management processes and practices. With the help of the Software Heritage Graph Dataset, we investigated the commits of two of the most popular script languages -- Python and JavaScript -- projects collected from public repositories and identified those that mitigate a certain vulnerability in the code (i.e. vulnerability resolution commits). On the one hand, we identified the types of vulnerabilities (in terms of CWE groups) referred to in commit messages and compared their numbers within the two communities. On the other hand, we examined the average time elapsing between the publish date of a vulnerability and the first reference to it in a commit. We found that there is a large intersection in the vulnerability types mitigated by the two communities, but most prevalent vulnerabilities are specific to language. Moreover, neither the JavaScript nor the Python community reacts very fast to appearing security vulnerabilities in general with only a couple of exceptions for certain CWE groups.Comment: 17th International Conference on Mining Software Repositorie

Nivel de estrés académico en estudiantes de enfermería durante la pandemia de COVID-19

Introduction. The COVID-19 pandemic has had a negative impact on the emotional health of the population, with different and inappropriate responses depending on the affected group. The research aimed to estimate the level of academic stress in nursing students from the National Autonomous University of Chota, Peru, during the COVID-19 pandemic. Methods. Observational, cross-sectional study, carried out in 122 nursing students from I to X cycle, they responded to the SISCO SV Academic Stress Inventory. Results. The level of academic stress in the stressors dimension was severe in women (64.4%) and men (77.2%), in the symptom dimension it was severe in women (42.5%) and mild in men (48.6 %) and in the dimension of coping strategies, it was severe in women (62.1%) and men (60.0%). The most frequent stressors were: task and work overload (66.4%), limited time for work (64.8%), level of demand from teachers (58.2%), exams or practices (58.2%) , teacher evaluation forms (54.1%), type of jobs requested (54.1%) and highly theoretical teachers (53.3%); the most frequent symptom was headaches (45.1%); the most used coping strategies were: listening to music or watching television (54.9%), surfing the internet (53.3%), assertive ability (51.6%), concentrating on solving the situation (49.2%) and entrust themselves to God (48.4%). The level of global academic stress was severe in women (51.7%) and men (48.6%). Conclusion. Nursing students of both sexes presented a level of severe academic stress in the dimensions and in the global assessment.Introducción. La pandemia de COVID-19 ha calado negativamente en la salud emocional de la población, con respuestas diferentes e inapropiadas según el grupo afectado. La investigación tuvo como objetivo estimar el nivel de estrés académico en estudiantes de enfermería de la Universidad Nacional Autónoma de Chota, Perú, durante la pandemia de COVID-19. Métodos. Estudio observacional, transversal, realizado en 122 estudiantes de enfermería de I a X ciclo, respondieron al Inventario de Estrés Académico SISCO SV. Resultados. El nivel de estrés académico en la dimensión estresores fue severo en mujeres (64,4%) y varones (77,2%), en la dimensión síntomas fue severo en mujeres (42,5%) y leve en varones (48,6%) y en la dimensión estrategias de afrontamiento fue severo en mujeres (62,1%) y varones (60,0%). Los estresores más frecuentes fueron: sobrecarga de tareas y trabajos (66,4%), tiempo limitado para trabajos (64,8%), nivel de exigencia de profesores (58,2%), exámenes o prácticas (58,2%), formas de evaluación de profesores (54,1%), tipo de trabajos solicitados (54,1%) y profesores muy teóricos (53,3%); el síntoma más frecuente fue los dolores de cabeza (45,1%); las estrategias de afrontamiento más utilizadas fueron: escuchar música o ver televisión (54,9%), navegar en internet (53,3%), habilidad asertiva (51,6%), concentrarse en resolver la situación (49,2%) y encomendarse a Dios (48,4%). El nivel de estrés académico global fue severo en mujeres (51,7%) y varones (48,6%). Conclusión. Los estudiantes de enfermería de ambos sexos presentaron un nivel de estrés académico severo en las dimensiones y en la valoración global

Contravention of regulatory provisions in public procurement to the common rules of the Administrative General Procedure Law Single Ordered Text

El Texto Único Ordenado de la Ley del Procedimiento Administrativo General (TUO de la LPAG) es calificado, en la actualidad, como una norma común. Esto implica que los procedimientos administrativos especiales, regulados por ley o reglamento, no pueden apartarse de las reglas y principios establecidos en el mismo TUO de la LPAG. Es así que, a partir de la premisa mencionada, el presente artículo tiene por objetivo poner en evidencia que existen disposiciones del régimen del procedimiento administrativo sancionador en la normativa de contrataciones del Estado que contravienen manifiestamente el referido régimen común