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El treball consisteix en el desenvolupament d’un sistema de monitoratge de la càrrega exercida sobre cadascuna de les extremitats inferiors per a pacients en activitats de rehabilitació. El sistema ha d’incloure uns sensors de pressió estratègicament distribuïts a la planta dels peus, un sistema d’adquisició de dades i un microcontrolador que processi les dades i informi en temps real del percentatge de pressió exercida per cada extremitat sobre el terra., The project involves the development of a monitoring system for the load exerted on each of the lower extremities for patients undergoing rehabilitation activities. The system must include pressure sensors strategically distributed on the soles, a data acquisition system, and a microcontroller that processes the data and provides real-time information on the percentage of pressure exerted by each feet on the ground.

Task-based programming models are a promising approach to exploiting complex distributed and heterogeneous systems. However, integrating different communication, offloading, and storage APIs within tasks poses performance and deadlock risks. Several Task-Aware libraries, such as TAMPI, TASIO, and TACUDA, have been developed to integrate blocking and non-blocking APIs within task-based programming models efficiently. In this paper, we introduce the Asynchronous Low-level Programming Interface (ALPI) to enable the interoperability and portability of Task-Aware libraries across various programming models and runtime systems. We have implemented ALPI in the Nanos6 and nOS-V runtimes, enhancing the integration of Task-Aware libraries with the OmpSs-2 and OpenMP programming models. This work is a step towards improving the composability of parallel programming models by supporting Task-Aware libraries across different runtime systems., This work was supported by the Spanish Ministry of Science and Innovation (grant PID2019-107255GB) and the Severo Ochoa Program (grant CEX2021-001148-S), both funded by MCIN/AEI/10.13039/501100011033. The Generalitat de Catalunya also supported this work via grant 2021-SGR-01007., Peer Reviewed, Postprint (author's final draft)

ML pipelines, as key components of ML systems, shall be developed following quality assurance techniques. Unfortunately, it is often the case in which they present maintainability issues, due to the experimentatal nature of data collection and ML model construction. To address this problem, this work in progress proposes initial metrics to measure the presence of code smells in ML pipelines. These metrics reflect good software engineering practices for code quality of ML pipelines., This work was supported by the “Spanish Ministerio de Ciencia e Innovación” under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033., Peer Reviewed, Postprint (author's final draft)

Computing the differences between two versions of the same program is an essential task for software development and software evolution research. AST differencing is the most advanced way of doing so, and an active research area. Yet, AST differencing algorithms rely on configuration parameters that may have a strong impact on their effectiveness. In this paper, we present a novel approach named DAT (D iff Auto Tuning ) for hyperparameter optimization of AST differencing. We thoroughly state the problem of hyper-configuration for AST differencing. We evaluate our data-driven approach DAT to optimize the edit-scripts generated by the state-of-the-art AST differencing algorithm named GumTree in different scenarios. DAT is able to find a new configuration for GumTree that improves the edit-scripts in 21.8% of the evaluated cases., This work was supported in part by the Spanish Ministry of Science and Innovation under Grant RYC2021-031523-I, in part by the GAISSA Spanish research project under Grant TED2021-130923B-I00, in part by the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) funded by Knut and Alice Wallenberg Foundation, and in part by the Swedish Foundation for Strategic Research (SSF). Some experiments were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC)., Peer Reviewed, Postprint (author's final draft)

Requirements specifcation is a core activity in the requirements engineering phase of a software development project. Researchers have contributed extensively to the feld of requirements specifcation, but the extent to which their proposals have been adopted in practice remains unclear. We gathered evidence about the state of practice in requirements specifcation by focussing on the artefacts used in this activity, the application of templates or guidelines, how requirements are structured in the specifcation document, what tools practitioners use to specify requirements, and what challenges they face. We conducted an interview-based survey study involving 24 practitioners from 12 diferent Swedish IT companies. We recorded the interviews and analysed these recordings, primarily by using qualitative methods. Natural language constitutes the main specifcation artefact but is usually accompanied by some other type of instrument. Most requirements specifcations use templates or guidelines, although they seldom follow any fxed standard. Requirements are always structured in the document according to the main functionalities of the system or to project areas or system parts. Diferent types of tools, including MS Ofce tools, are used, either individually or combined, in the compilation of requirements specifcations. We also note that challenges related to the use of natural language (dealing with ambiguity, inconsistency, and incompleteness) are the most frequent challenges that practitioners face in the compilation of requirements specifcations. These fndings are contextualized in terms of demographic factors related to the individual interviewees, the organization they are afliated with, and the project they selected to discuss during our interviews. A number of our fndings have been previously reported in related studies. These fndings show that, in spite of the large number of notations, models and tools proposed from academia for improving requirements specifcation, p, This paper has been funded by the Spanish Ministerio de Ciencia e Innovación under project/funding scheme PID2020-117191RB-I00/AEI/., Peer Reviewed, Postprint (published version)

Scientific applications face the challenge of efficiently exploiting increasingly complex parallel and distributed systems. Developing hand-tuned codes is a time-consuming, tedious and hardly reusable task. Reaching high performance appears detrimental to productivity and portability and unreasonable to expect from scientists. Domain-Specific Languages (DSLs) are collaborative environments aiming to overcome such difficulties by decoupling the problem description from the algorithmic implementation. However, developing a competitive tool in High-Performance Computing (HPC) is challenging: DSLs for HPC environments have two additional critical requirements, performance and scalability. Moreover, documented and successful cases are few, making it difficult to popularise DSLs as problem-solving environments for scientific HPC code development. In this context, Saiph is a task-based DSL easing the simulation of physical phenomena from Computational Fluid Dynamics (CFD), developed to meet HPC productivity and performance requirements. This work reports the tuning and evaluation of Saiph using the Taylor–Green Vortex (TGV) problem as a case study. We assess Saiph’s productivity, numerical methods, and high-performance strategies to illustrate its use and demonstrate its competitiveness, viability and benefits for CFD software developments in HPC environments. Hence, we contribute to the popularisation of HPC DSLs as suitable problem-solving environments able to unify modern computational and scientific knowledge., This work has been supported by the Generalitat de Catalunya (contract 2021-SGR-01007), the Spanish Ministry of Science and Technology (contract PID2019-107255 GB), and Severo Ochoa (CEX2021- 001148-S/MCIN/AEI/10.13039/ 501100011033)., Peer Reviewed, Postprint (author's final draft)

Vitamin-V is a project funded under the Horizon Europe program for the period 2023-2025. The project aims to create a complete open-source software stack for RISC-V that can be used for cloud services. This software stack is intended to have the same level of performance as the x86 architecture, which is currently dominant in the cloud computing industry. In addition, the project aims to create a powerful virtual execution environment that can be used for software development, validation, verification, and testing. The virtual environment will consider the relevant RISC-V ISA extensions required for cloud deployment. Commercial cloud systems use hardware features currently unavailable in RISC-V virtual environments, including virtualization, cryptography, and vectorization. To address this, Vitamin-V will support these features in three virtual environments: QEMU, gem5, and cloud-FPGA prototype platforms. The project will focus on providing support for EPI-based RISC-V designs for both the main CPUs and cloud-important accelerators, such as memory compression. The project will add the compiler (LLVM-based) and toolchain support for the ISA extensions. Moreover, Vitamin-V will develop novel approaches for validating, verifying, and testing software trustworthiness. This paper focuses on the plans and visions that the Vitamin-V project has to support validation, verification, and testing for cloud applications, particularly emphasizing the hardware support that will be provided., Funded by the European Union. Project number: 101093062., Peer Reviewed, Postprint (author's final draft)

Issue trackers, such as Jira, have become the prevalent collaborative tools in software engineering for managing issues, such as requirements, development tasks, and software bugs. However, issue trackers inherently focus on the lifecycle of single issues, although issues have and express dependencies on other issues that constitute issue dependency networks in large complex collaborative projects. The objective of this study is to develop supportive solutions for the improved management of dependent issues in an issue tracker. This study follows the Design Science methodology, consisting of eliciting drawbacks and constructing and evaluating a solution and system. The study was carried out in the context of The Qt Company's Jira, which exemplifies an actively used, almost two-decade-old issue tracker with over 100,000 issues. The drawbacks capture how users operate with issue trackers to handle issue information in large, collaborative, and long-lived projects. The basis of the solution is to keep issues and dependencies as separate objects and automatically construct an issue graph. Dependency detections complement the issue graph by proposing missing dependencies, while consistency checks and diagnoses identify conflicting issue priorities and release assignments. Jira's plugin and service-based system architecture realize the functional and quality concerns of the system implementation. We show how to adopt the intelligent supporting techniques of an issue tracker in a complex use context and a large data-set. The solution considers an integrated and holistic system view, practical applicability and utility, and the practical characteristics of issue data, such as inherent incompleteness., The work presented in this paper has been conducted within the scope of the Horizon 2020 project OpenReq, which is supported by the European Union under Grant Nr. 732463. We are grateful for the provision of the Finnish computing infrastructure to carry out the tests (persistent identifier urn:nbn:fi:research-infras-2016072533). This paper has been funded by the Spanish Ministerio de Ciencia e Innovacionúnder project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033., Peer Reviewed, Postprint (published version)

Software analytic tools consume big amounts of data coming from either (or both) the software development process or the system usage and aggregate them into indicators which are rendered to different types of stakeholders, also offering them a portfolio of techniques and capabilities such as what-if analysis, prediction and alerts. Precisely, the variety of stakeholders and the different goals they pursue justifies the convenience of performing an intentional analysis of the use of software analytics tools. With this aim, we first enumerate the different stakeholders and identify their intentional relationships with software analytics tools in the form of dependencies. Then, we focus on one particular stakeholder, namely the requirements engineer, and identify further intentional elements represented in a strategic rationale model. The resulting model provides an abstract view of the domain which may help stakeholders when deciding on the adoption of software analytic tools in their particular context., This paper has been funded by the Spanish Ministerio de Ciencia e Innovación under project / funding scheme PID2020-117191RB-I00 / AEI/10.13039/501100011033., Peer Reviewed, Postprint (published version)

Context: In despite of agile and rapid software development (ARSD) being researched and applied extensively, managing quality requirements (QRs) are still challenging. As ARSD processes produce a large amount of data, measurement has become a strategy to facilitate QR management. Objective: This study aims to survey the literature related to QR management through metrics in ARSD, focusing on: bibliometrics, QR metrics, and quality-related indicators used in quality management. Method: The study design includes the definition of research questions, selection criteria, and snowballing as search strategy. Results: We selected 61 primary studies (2001-2019). Despite a large body of knowledge and standards, there is no consensus regarding QR measurement. Terminology is varying as are the measuring models. However, seemingly different measurement models do contain similarities. Conclusion: The industrial relevance of the primary studies shows that practitioners have a need to improve quality measurement. Our collection of measures and data sources can serve as a starting point for practitioners to include quality measurement into their decision-making processes. Researchers could benefit from the identified similarities to start building a common framework for quality measurement. In addition, this could help researchers identify what quality aspects need more focus, e.g., security and usability with few metrics reported., This work has been funded by the European Union’s Horizon 2020 research and innovation program through the Q-Rapids project (grant no. 732253). This research was also partially supported by the Spanish Ministerio de Economía, Industria y Competitividad through the DOGO4ML project (grant PID2020-117191RB-I00). Silverio Martínez-Fernández worked in Fraunhofer IESE before January 2020., Peer Reviewed, Postprint (published version)

El presente proyecto final de máster se focaliza en el estudio y diseño de un sistema de monitorización para un sistema fotovoltaico y qué metodología de proyectos es la más adecuada para realizarlo. Dicho estudio se centra en cubrir el consumo de dos hornos eléctricos para un particular. Para conseguir dicho propósito, primero se realiza el dimensionamiento del sistema fotovoltaico para cubrir las necesidades del consumo y posteriormente el estudio y diseño del sistema de monitorización. Durante el desarrollo de la parte técnica previamente mencionada se va analizando que metodología de proyectos es la más adecuada, si tradicional o ágil, para finalmente desarrollar el protocolo del proyecto utilizando la metodología de proyectos escogida que aporte más beneficios a este

Context: Exploiting software development related data from software-development intensive organizations to support tactical and strategic decision making is a challenge. Combining data-driven approaches with expert knowledge has been highlighted as a sensible approach for leading software-development intensive organizations to rightful decision-making improvements. However, most of the existing proposals lack of important aspects that hinders their industrial uptake such as: customization guidelines to fit the proposals to other contexts and/or automatic or semi-automatic data collection support for putting them forward in a real organization. As a result, existing proposals are rarely used in the industrial context. Objective: Support software-development intensive organizations with guidance and tools for exploiting software development related data and expert knowledge to improve their decision making. Method: We have developed a novel method called SESSI (Specification and Estimation of Software Strategic Indicators) that was articulated from industrial experiences with Nokia, Bittium, Softeam and iTTi in the context of Q-Rapids European project following a design science approach. As part of the industrial summative evaluation, we performed the first case study focused on the application of the method. Results: We detail the phases and steps of the SESSI method and illustrate its application in the development of ModelioNG, a software product of Modeliosoft development firm. Conclusion: The application of the SESSI method in the context of ModelioNG case study has provided us with useful feedback to improve the method and has evidenced that applying the method was feasible in this context., Peer Reviewed, Postprint (author's final draft)

Introducing advanced functionalities in safety-critical systems requires using more powerful architectures such as GPUs. However software in safety-critical industries is subject to functional certification, which cannot be achieved using standard GPU programming languages such as CUDA and OpenCL. Fortunately, GPUs are already used in certified critical systems for display tasks, using safety-certified solutions such as OpenGL SC 2.0. In this paper, we compare two state-of-the art graphics-based methodologies, OpenGL SC 2.0 and Brook Auto/BRASIL for the implementation of a prototype avionics case study. We evaluate both methods on a realistic industrial setup, composed by an avionics-grade GPU and a safety-certified GPU driver in terms of development metrics and performance, showing their feasibility., This work was funded by the Airbus TANIA-GPU Project ADS (E/200). It was also partially supported by the Spanish Ministry of Economy and Competitiveness under grants PID2019-107255GB and FJCI-2017-34095 and HiPEAC., Peer Reviewed, Postprint (author's final draft)

En aquest treball s'especifica, dissenya i implementa una extensió software pel dashboard estratègic de Q-Rapids (Quality-Aware Rapid Software Development) per tal de poder crear, validar, modificar, i, en general, gestionar els indicadors estratègics (SI) que es poden definir per sistemes software. L'objectiu principal és donar solució a una sèrie de limitacions en la implementació original de les funcionalitats del dashboard per tal de que ofereixi una solució completa., This project specifies, designs and implements a software extension for the strategic dashboard of the Q-Rapids tool (Quality-Aware Rapid Software Development) in order to create, validate, modify, and, in general, manage the strategic indicators (SI) that can be defined in software systems. The main goal is to address a number of limitations in the original implementation of dashboard functionalities in order to offer a complete solution.

Graphs play an important role in many areas of Computer Science. In particular, our work is motivated by model-driven software development and by graph databases. For this reason, it is very important to have the means to express and to reason about the properties that a given graph may satisfy. With this aim, in this paper we present a visual logic that allows us to describe graph properties, including navigational properties, i.e., properties about the paths in a graph. The logic is equipped with a deductive tableau method that we have proved to be sound and complete., This work was supported by the Spanish Ministry of Economy and Competitiveness and the European Union (FEDER funds) under grant GRAMM (ref. TIN2017-86727-C2-1-R, TIN2017-86727-C2-2-R) and by the Basque Project GIU15/30, and grant UFI11/45., Peer Reviewed, Postprint (author's final draft)

Context: Managing Non-Functional Requirements (NFRs) in software projects is challenging, and projects that adopt Model-Driven Development (MDD) are no exception. Although several methods and techniques have been proposed to face this challenge, there is still little evidence on how NFRs are handled in MDD by practitioners. Knowing more about the state of the practice may help researchers to steer their research and practitioners to improve their daily work. Objective: In this paper, we present our findings from an interview-based survey conducted with practitioners working in 18 different companies from 6 European countries. From a practitioner's point of view, the paper shows what barriers and benefits the management of NFRs as part of the MDD process can bring to companies, how NFRs are supported by MDD approaches, and which strategies are followed when (some) types of NFRs are not supported by MDD approaches. Results: Our study shows that practitioners perceive MDD adoption as a complex process with little to no tool support for NFRs, reporting productivity and maintainability as the types of NFRs expected to be supported when MDD is adopted. But in general, companies adapt MDD to deal with NFRs. When NFRs are not supported, the generated code is sometimes changed manually, thus compromising the maintainability of the software developed. However, the interviewed practitioners claim that the benefits of using MDD outweight the extra effort required by these manual adaptations. Conclusion: Overall, the results indicate that it is important for practitioners to handle NFRs in MDD, but further research is necessary in order to lower the barrier for supporting a broad spectrum of NFRs with MDD. Still, much conceptual and tool implementation work seems to be necessary to lower the barrier of integrating the broad spectrum of NFRs in practice., Peer Reviewed, Postprint (author's final draft)

The UP2DATE H2020 project focuses on highperformance heterogeneous embedded platforms for critical systems. We will develop observability and controllability solutions to support online updates while ensuring safety and security for mixed-criticality tasks. In this paper, we describe the rationale behind the selection of the baseline research platforms which will be used to develop and demonstrate the project concepts, including a performance comparison to identify the most efficient one., This work is funded by the European Commission’s Horizon 2020 programme under the UP2DATE project (grant agreement 871465). It is also partially supported by the Spanish Ministry of Economy and Competitiveness under grants PID2019-107255GB and FJCI-2017-34095 and HiPEAC., Peer Reviewed, Postprint (author's final draft)

Space missions need software in order to be aware of the occurrence of geometric events in different phases of their project lifecycle. However, current software packages that provide capabilities to search for geometric events might lack desirable software qualities such as extensibility and reusability, and some conflate the definition of events with the search for the same. In order to improve the state of the art, we propose a framework named Tychonis that, via metamodeling techniques and conscious use of object-oriented design best practices, (i) can integrate with current and future mission software, (ii) enables end-users to extend opportunities and search algorithms without modifying the tools that use the framework, and (iii) promotes the cross-mission reusability of the framework and its extensions. These attributes make it less costly for projects to develop software to search for geometric events. Tychonis is provided as a software library that allows missions to add their own data structures and constructs to the framework, including geometric event types and search algorithms. This is accomplished with Tychonis’ use of the Eclipse Modeling Framework (EMF) to capture its metamodel, which enables the generation of Java classes that represent built-in or user-developed Tychonis constructs. In the present paper, we elaborate on the impetus for the development of Tychonis, present its proposed design and use, and discuss growth opportunities for future consideration., Peer Reviewed, Postprint (author's final draft)

Aquest treball té com a objectiu principal desenvolupar una aplicació informàtica per tal de monitorar i visualitzar les dades de generació tant elèctrica com tèrmica d'un generador Dish Stirling situat al terrat de l’edifici de l’ETSEIB. Aquest generador disposa d’un sistema d’adquisició de dades que utilitza un software comercial anomenat “Scada”, i d’una pàgina web que requereix tenir instal·lada una versió de Java que ja no és segura, i com a tal ja no és compatible amb els navegadors d’internet actuals. Degut a que el sistema d’adquisició de dades requereix una llicència de pagament i a que la pàgina web no es accessible amb els navegadors actuals, aquest projecte ha desenvolupat dues aplicacions que substitueixin les aplicacions anteriors: - Una aplicació que es connecta periòdicament a el servidor del generador per recollir les dades del generador i guardar-les en una base de dades en format SQL - Una pàgina web que permet mostrar les dades guardades a la base de dades en forma de gràfic o de taula i que permet descarregar-les en format CSV. Aquestes aplicacions han estat desenvolupades en Python, un llenguatge de programació interpretat, multiplataforma i open-source (de codi públic). Com a editor de codi s’ha utilitzat “Pycharm”, un IDE per Python que permet configurar fàcilment diferents entorns de programació, i com a software de gestió de base de dades s’ha utilitzat “MariaDB”. Per la pàgina web, s’ha utilitzat un framework per fer pàgines web amb Python anomenat “Django”, el treball explica com s’ha utilitzat l’estructura i metodologies d’aquest framework. Un framework es un programa amb funcionalitats ja dissenyades que permet escriure programes que utilitzin aquestes funcionalitats. També s’ha utilitzat tecnologies de disseny web com són el Bootstrap, CSS, Javascript i Jquery,que permeten escriure pàgines web dinàmiques a partir del llenguatge HTML, el llenguatge amb el que s’escriu el cos de les pàgines web en documents de format html. Per poder acce

Context: Agile software development has become commonplace in software development companies due to the numerous benefits it provides. However, conducting Agile projects is demanding in Small and Medium Enterprises (SMEs), because projects start and end quickly, but still have to fulfil customers' quality requirements. Objective: This paper aims at reporting a practical experience on the use of metrics related to the software development process as a means supporting SMEs in the development of software following an Agile methodology. Method: We followed Action-Research principles in a Polish small-size software development company. We developed and executed a study protocol suited to the needs of the company, using a pilot case. Results: A catalogue of Agile development process metrics practically validated in the context of a small-size software development company, adopted by the company in their Agile projects. Conclusions: Practitioners may adopt these metrics in their Agile projects, especially if working in an SME, and customise them to their own needs and tools. Academics may use the findings as a baseline for new research work, including new empirical studies., The authors would like to thank all the members of the QRapids H2020 project consortium., Peer Reviewed, Postprint (published version)

Aquest treball de fi de grau correspon a un projecte informàtic. El projecte consisteix en implementar una eina software amb l’objectiu principal de que empreses i organitzacions puguin tenir un control sobre l’estat dels diferents paràmetres dels seus servidors. Aquesta eina, pensada per treballar en servidors Linux, instal·la automàticament un client als servidors, que envia periòdicament el valor dels paràmetres configurats a una pàgina web. Per altra banda, aquest projecte també utilitza un sistema de predicció que permet descobrir quina és la funció principal de cada servidor, les funcions que pot predir aquest sistema són: servidor web, servidor de base de dades, servidor de correu, servidor de fitxers i servidor de salt. Gràcies a aquesta informació, l’eina de monitorització, permet tenir controlats els paràmetres més rellevants pera cada tipus de servidor. El que comporta que es puguin detectar incidents que una eina demonitorització convencional no podria detectar per defecte, sinó que s’haurien de configurar els paràmetres manualment. Quan es detecta un incident, el sistema avisa a l’equip de TIC per tal de solucionar ràpidament el conflicte. Aquest estudi s’ha dut a terme per mitjà de l’empresa SmartAoS i forma part d’un projecte més gran per tal d’aportar-hi la funcionalitat esmentada anteriorment., The project consists in the implementation of a software tool with the main goal of allowing the companies and organizations to have control over the status parameters of their servers.This tool, designed to work on Linux servers, automatically installs the client to the servers, which sends the configured parameters value periodically to a webpage. On the other hand, this project also uses a prediction system which allows to discover the main functionality ofevery server. The type of servers that can predict are: web server, database server, email server and jump server. Thanks to this information, the monitoirng tool allow us to control the most relevant values in each server type. This system provides us the possiblity to detect more errors in an automated way and warnt the IT team consequently. This study it’s a collaboration with the SmartAoS company and it’s part of a bigger project with the aim of providing the mentioned functionality

Currently, there is a growing interest in finding a comprehensive method in ETL process technology that can deal with healthcare data formats. Healthcare centers are very concerned about their sensitive information which mostly has patients' data inside. they avoid using the market-driven ETL tools because they need higher performance and adaption for complex security treatment. On the grounds of this, they are in great need of a stable ETL tool that does their transformation for them privately. One of the common data formats used by various healthcare providers for the exchange of clinical and administrative data among software applications is Health Level Seven (HL7). HL7 refers to a series of international standards that are used to move clinical and administrative data between applications by different healthcare providers. Typically, hospitals and other healthcare providers have several different data structures that are used for everything from billing reports to monitoring clinical data for patients. Standardized HL7 format is one of the widely used cases, with information about the patient identification and results of patient tests. Data analysts in the bioinformatics department typically need to analyze and review these kinds of information carefully. HL7 has a standard format for describing each of this information but it is a time-consuming process to understand and prepare them for analysis. In this thesis, a powerful ETL tool named ETL_for_HL7 is proposed to deal with this type of data. Usually, HL7 data is made available in the XML format file by the laboratory. The main objective of this thesis is to understand the HL7 data format, design a proper data model, create a valid conceptual schema and convert it to a physical data warehouse, implement an ETL tool in the way that the laboratory saves it and sends it to the data management department, transform it into analysis-ready formats (e.g., DW schema) and finally load it into the data warehouse. The

As the development progresses, software projects tend to accumulate Technical Debt and become harder to maintain. Multiple tools exist with the mission to help practitioners to better manage Technical Debt. Despite this progress, there is a lack of tools providing actionable and self-learned suggestions to practitioners aimed at mitigating the impact of Technical Debt in real projects. We aim to create a data-driven, lightweight, and self-learning tool positioning highly impactful refactoring proposals on a Jira backlog. Bearing this goal in mind, the first two authors have founded a startup, called Skuld.ai, with the vision of becoming the go-to software renovation company. In this tool paper, we present the software architecture and demonstrate the main functionalities of our tool. It has been showcased to practitioners, receiving positive feedback. Currently, its release to the market is underway thanks to an industry-research institute collaboration with Fraunhofer IESE to incorporate self-learning technical debt capabilities., Peer Reviewed, Postprint (author's final draft)

Managing software projects gets more and more complicated with an increasing project and product size. To cope with this complexity, many organizations use issue tracking systems, where tasks, bugs, and requirements are stored as issues. Unfortunately, managing software projects might remain chaotic even when using issue trackers. Particularly for long lasting projects with a large number of issues and links between them, it is often hard to maintain an overview of the dependencies, especially when dozens of new issues get reported every day. We present a Jira plug-in that supports developers, project managers, and product owners in managing and overviewing issues and their dependencies. Our tool visualizes the issue links, helps to find missing or unknown links between issues, and detects inconsistencies., The work presented in this paper has been conducted within the scope of the Horizon 2020 project OpenReq, which is supported by the European Union under the Grant Nr. 732463., Peer Reviewed, Postprint (author's final draft)

Data science is mandatory in today's business to capitalize on achievements and assets. This specifically holds for modern software development, where data science facilitates analyzing product, process, and usage and thus managing evolution and performance. With the convergence of embedded and IT domains, such as the Internet of Things (IoT) and automotive systems, software systems are becoming more complex. Complexity has two faces. On one hand it means more functionality and fluid delivery models, thus offering markets more value, such as the ability to deliver a single-customer focus. Complexity, however, also means the growth of technical debt, which slows productivity and lowers quality. As software engineering generates ever larger and more varied data sets, such as feature usage, code analysis, test coverage, error logs, and maintenance data, companies face the challenge of unlocking the value of that data., Peer Reviewed, Postprint (author's final draft)

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This master thesis discusses the development of a tool for the supply management team in Hilti AG for a specific product line: cartridges. The tool comprises of an algorithm developed in Microsoft Excel, in the coding language Visual Basic. The purpose of the algorithm is to support the supply management team in optimizing decision-making when allocating production volumes between main suppliers. The master thesis starts with background research to state the current situation of the specific product line, from a supply management point of view. This research includes the description of the product, a description of the supply structure of Hilti, a description of the current suppliers, a market analysis and lastly, a description of how in the past volume allocations have been done. The master thesis follows with a SWOT analysis and target setting, from which the design concept of the algorithm starts. The design concept includes the following steps: system description, parameter definition, optimization strategy description and finally the explanation of the design concept. Subsequently, the design concept is implemented and the code is explained. The last step includes the solution evaluation from the point of view of the company, Outgoing

The use of software analytics in software development companies has grown in the last years. Still, there is little support for such companies to obtain integrated insightful and actionable information at the right time. This research aims at exploring the integration of runtime and development data to analyze to what extent external quality is related to internal quality based on real project data. Over the course of more than three months, we collected and analyzed data of a software product following the CRISP-DM process. We studied the integration possibilities between runtime and development data, and implemented two integrations. The number of bugs found in code has a weak positive correlation with code quality measures and a moderate negative correlation with the number of rule violations found. Other types of correlations require more data cleaning and higher quality data for their exploration. During our study, several challenges to exploit data gathered both at runtime and during development were encountered. Lessons learned from integrating external and internal data in software projects may be useful for practitioners and researchers alike., Peer Reviewed, Postprint (author's final draft)

Context: Quality requirements (QRs) describe the desired quality of software, and they play an important role in the success of software projects. In agile software development (ASD), QRs are often ill-defined and not well addressed due to the focus on quickly delivering functionality. Rapid software development (RSD) approaches (e.g., continuous delivery and continuous deployment), which shorten delivery times, are more prone to neglect QRs. Despite the significance of QRs in both ASD and RSD, there is limited synthesized knowledge on their management in those approaches. Objective: This study aims to synthesize state-of-the-art knowledge about QR management in ASD and RSD, focusing on three aspects: bibliometric, strategies, and challenges. Research method: Using a systematic mapping study with a snowballing search strategy, we identified and structured the literature on QR management in ASD and RSD. Results: We found 156 primary studies: 106 are empirical studies, 16 are experience reports, and 34 are theoretical studies. Security and performance were the most commonly reported QR types. We identified various QR management strategies: 74 practices, 43 methods, 13 models, 12 frameworks, 11 advices, 10 tools, and 7 guidelines. Additionally, we identified 18 categories and 4 non-recurring challenges of managing QRs. The limited ability of ASD to handle QRs, time constraints due to short iteration cycles, limitations regarding the testing of QRs and neglect of QRs were the top categories of challenges. Conclusion: Management of QRs is significant in ASD and is becoming important in RSD. This study identified research gaps, such as the need for more tools and guidelines, lightweight QR management strategies that fit short iteration cycles, investigations of the link between QRs challenges and technical debt, and extension of empirical validation of existing strategies to a wider context. It also synthesizes QR management strategies and challenges, which may be useful, Peer Reviewed, Postprint (author's final draft)