A TAXONOMY OF FORKS IN THE CONTEXT OF DECENTRALIZED AUTONOMOUS ORGANIZATIONS

Decentralized autonomous organizations (DAOs) are blockchain-based organizations that manage resources through self-executing rules defined in smart contracts and rely on decentralized governance approaches. Many DAOs were affected by forking, a phenomenon in which a new DAO–the fork–is created by copying another DAO’s–the parent’s–protocols, source code, and/or data. Current research unveiled various far-reaching implications of DAO forking but comparing and generalizing these is inhibited by a missing fine-grained understanding of the different types of DAO forks. This motivates us to develop a taxonomy of DAO forks. We developed our taxonomy based on research on forking of DAOs and software development projects and the examination of 21 real-world cases of DAO forking. Our taxonomy contributes a framework to researchers of DAOs and software forking as well as practitioners, who are now able to define and distinguish different types of DAO forks and their individual implications

Seamless Variability Management With the Virtual Platform

Customization is a general trend in software engineering, demanding systems that support variable stakeholder requirements. Two opposing strategies are commonly used to create variants: software clone & own and software configuration with an integrated platform. Organizations often start with the former, which is cheap, agile, and supports quick innovation, but does not scale. The latter scales by establishing an integrated platform that shares software assets between variants, but requires high up-front investments or risky migration processes. So, could we have a method that allows an easy transition or even combine the benefits of both strategies? We propose a method and tool that supports a truly incremental development of variant-rich systems, exploiting a spectrum between both opposing strategies. We design, formalize, and prototype the variability-management framework virtual platform. It bridges clone & own and platform-oriented development. Relying on programming-language-independent conceptual structures representing software assets, it offers operators for engineering and evolving a system, comprising: traditional, asset-oriented operators and novel, feature-oriented operators for incrementally adopting concepts of an integrated platform. The operators record meta-data that is exploited by other operators to support the transition. Among others, they eliminate expensive feature-location effort or the need to trace clones. Our evaluation simulates the evolution of a real-world, clone-based system, measuring its costs and benefits.Comment: 13 pages, 10 figures; accepted for publication at the 43rd International Conference on Software Engineering (ICSE 2021), main technical trac

Understanding Variability-Aware Analysis in Low-Maturity Variant-Rich Systems

Context: Software systems often exist in many variants to support varying stakeholder requirements, such as specific market segments or hardware constraints. Systems with many variants (a.k.a. variant-rich systems) are highly complex due to the variability introduced to support customization. As such, assuring the quality of these systems is also challenging since traditional single-system analysis techniques do not scale when applied. To tackle this complexity, several variability-aware analysis techniques have been conceived in the last two decades to assure the quality of a branch of variant-rich systems called software product lines. Unfortunately, these techniques find little application in practice since many organizations do use product-line engineering techniques, but instead rely on low-maturity \clo~strategies to manage their software variants. For instance, to perform an analysis that checks that all possible variants that can be configured by customers (or vendors) in a car personalization system conform to specified performance requirements, an organization needs to explicitly model system variability. However, in low-maturity variant-rich systems, this and similar kinds of analyses are challenging to perform due to (i) immature architectures that do not systematically account for variability, (ii) redundancy that is not exploited to reduce analysis effort, and (iii) missing essential meta-information, such as relationships between features and their implementation in source code.Objective: The overarching goal of the PhD is to facilitate quality assurance in low-maturity variant-rich systems. Consequently, in the first part of the PhD (comprising this thesis) we focus on gaining a better understanding of quality assurance needs in such systems and of their properties.Method: Our objectives are met by means of (i) knowledge-seeking research through case studies of open-source systems as well as surveys and interviews with practitioners; and (ii) solution-seeking research through the implementation and systematic evaluation of a recommender system that supports recording the information necessary for quality assurance in low-maturity variant-rich systems. With the former, we investigate, among other things, industrial needs and practices for analyzing variant-rich systems; and with the latter, we seek to understand how to obtain information necessary to leverage variability-aware analyses.Results: Four main results emerge from this thesis: first, we present the state-of-practice in assuring the quality of variant-rich systems, second, we present our empirical understanding of features and their characteristics, including information sources for locating them; third, we present our understanding of how best developers\u27 proactive feature location activities can be supported during development; and lastly, we present our understanding of how features are used in the code of non-modular variant-rich systems, taking the case of feature scattering in the Linux kernel.Future work: In the second part of the PhD, we will focus on processes for adapting variability-aware analyses to low-maturity variant-rich systems.Keywords:\ua0Variant-rich Systems, Quality Assurance, Low Maturity Software Systems, Recommender Syste

Aplicativo móvil para el sistema de inventario en la Botica Nuevo Perú E.I.R.L

La investigación difunde el desarrollo e implementación de un Aplicativo móvil para el sistema de inventario en la Botica Nuevo Perú E.I.R.L, puesto que la empresa presento como deficiencia el índice de rotación de stock y el nivel de cumplimiento en despachos. El objetivo propuesto de la investigación fue determinar el efecto de una Aplicación móvil para el sistema de inventario en la Botica Nuevo Perú E.I.R.L, en el año 2021. La tesis está conformada por capítulos, divididos en: Introducción, Marco teórico, Metodología de la investigación, Resultados, Discusión, Conclusión y Recomendaciones. De tal forma se describe los aspectos teóricos del sistema de inventario, también las metodologías que son base teórica para el desarrollo del aplicativo móvil. La herramienta tecnológica aplicada con la metodología Scrum, por ser la que se adapta a las funcionalidades y requerimientos del proyecto de investigación, la característica funcional es la cooperación de la parte del aliado estratégico, lo cual permitió aterrizar las bases teóricas y prácticas para un producto útil. La implementación del aplicativo móvil permitió incrementar el índice de rotación de stock de 40.76% al 85.64%, de igual forma, se incrementó el nivel de cumplimiento en despachos del 41.62% al 85.11%. Como se manifiesta los resultados indicados previamente, admitieron llegar a la conclusión que la aplicación móvil incremento de forma significativa esto conlleva a la mejora en todo lo propuesto en el proyecto de investigación

A Framework for Seamless Variant Management and Incremental Migration to a Software Product-Line

Context: Software systems often need to exist in many variants in order to satisfy varying customer requirements and operate under varying software and hardware environments. These variant-rich systems are most commonly realized using cloning, a convenient approach to create new variants by reusing existing ones. Cloning is readily available, however, the non-systematic reuse leads to difficult maintenance. An alternative strategy is adopting platform-oriented development approaches, such as Software Product-Line Engineering (SPLE). SPLE offers systematic reuse, and provides centralized control, and thus, easier maintenance. However, adopting SPLE is a risky and expensive endeavor, often relying on significant developer intervention. Researchers have attempted to devise strategies to synchronize variants (change propagation) and migrate from clone&own to an SPL, however, they are limited in accuracy and applicability. Additionally, the process models for SPLE in literature, as we will discuss, are obsolete, and only partially reflect how adoption is approached in industry. Despite many agile practices prescribing feature-oriented software development, features are still rarely documented and incorporated during actual development, making SPL-migration risky and error-prone.Objective: The overarching goal of this PhD is to bridge the gap between clone&own and software product-line engineering in a risk-free, smooth, and accurate manner. Consequently, in the first part of the PhD, we focus on the conceptualization, formalization, and implementation of a framework for migrating from a lean architecture to a platform-based one.Method: Our objectives are met by means of (i) understanding the literature relevant to variant-management and product-line migration and determining the research gaps (ii) surveying the dominant process models for SPLE and comparing them against the contemporary industrial practices, (iii) devising a framework for incremental SPL adoption, and (iv) investigating the benefit of using features beyond PL migration; facilitating model comprehension.Results: Four main results emerge from this thesis. First, we present a qualitative analysis of the state-of-the-art frameworks for change propagation and product-line migration. Second, we compare the contemporary industrial practices with the ones prescribed in the process models for SPL adoption, and provide an updated process model that unifies the two to accurately reflect the real practices and guide future practitioners. Third, we devise a framework for incremental migration of variants into a fully integrated platform by exploiting explicitly recorded metadata pertaining to clone and feature-to-asset traceability. Last, we investigate the impact of using different variability mechanisms on the comprehensibility of various model-related tasks.Future work: As ongoing and future work, we aim to integrate our framework with existing IDEs and conduct a developer study to determine the efficiency and effectiveness of using our framework. We also aim to incorporate safe-evolution in our operators

Clone-based variability management in the android ecosystem

Mobile app developers often need to create variants to account for different customer segments, payment models or functionalities. A common strategy is to clone (or fork) an existing app and then adapt it to new requirements. This form of reuse has been enhanced with the advent of social-coding platforms such as Github, cultivating a more systematic reuse. Different facilities, such as forks, pull requests, and cross-project traceability support clone-based development. Unfortunately, even though, many apps are known to be maintained in many variants, little is known about how practitioners manage variants of mobile apps. We present a study that explores clone-based reuse practices for open-source Android apps. We identified and analyzed families of apps that are maintained together and that exist both on the official app store (Google Play) as well as on Github, allowing us to analyze reuse practices in depth. We mined both repositories to identify app families and to study their characteristics, including their variabilities as well as code-propagation practices and maintainer relationships. We found that, indeed, app families exist and that forked app variants fall into the following categories: (i) re-branding and simple customizations, (ii) feature extension, (iii) supporting of the mainline app, and (iv) implementation of different, but related features. Other notable characteristic of the app families we discovered include: (i) 72.7% of the app families did not perform any form of code propagation, and (ii) 74% of the app families we studied do not have common maintainers