Managing variability in configurable systems remains a challenging endeavor for multiple reasons. First, variability must be properly defined using domain knowledge and reusable software artifacts, often relying on ex...
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ISBN:
(纸本)9798400705939
Managing variability in configurable systems remains a challenging endeavor for multiple reasons. First, variability must be properly defined using domain knowledge and reusable software artifacts, often relying on extraction and refinement of legacy assets. Second, variability must be maintained during evolution in time (revisions) and space (variants). Recent research activities have focused on enabling the integrated management of evolution and variability. Existing approaches stem from multiple origins, notably software configuration management and product line engineering. the 1st. international Workshop on Reverse Variability engineering and Evolution of software-Intensive Systems joins the motivation originating from REVE and VariVolution. It shall bring together active researchers eliciting software variability and studying its evolution, and practitioners who encounter these phenomena in the real-world. Re:Volution offers a platform to exchange ideas, case studies, and tools, fostering research collaborations and synergies.
A wide range of transformer-based language models have been proposed for information retrieval tasks. However, including transformer-based models in retrieval pipelines is often complex and requires substantial engine...
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ISBN:
(纸本)9798400713293
A wide range of transformer-based language models have been proposed for information retrieval tasks. However, including transformer-based models in retrieval pipelines is often complex and requires substantial engineering effort. In this paper, we introduce Lightning IR, an easy-to-use PyTorch Lightning-based framework for applying transformer-based language models in retrieval scenarios. Lightning IR provides a modular and extensible architecture that supports all stages of a retrieval pipeline: from fine-tuning and indexing to searching and re-ranking. Designed to be scalable and reproducible, Lightning IR is available as open-source: https://***/webis-de/lightning-ir.
the space sector is currently undergoing a transformative phase marked by the emergence of CubeSat projects. Although many CubeSats are launched annually, only a few manage to accomplish their missions. this challenge...
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ISBN:
(纸本)9798350358810;9798350358803
the space sector is currently undergoing a transformative phase marked by the emergence of CubeSat projects. Although many CubeSats are launched annually, only a few manage to accomplish their missions. this challenge is partly attributed to the inherent complexity of CubeSats, which, despite their small size, remain intricate systems. Companies engaged in CubeSat development generally lack the resources and regulatory impetus to implement systematic engineering processes, as outlined in international standards. the absence of a straightforward and space-specific system engineering framework hinders teams in effectively managing their development processes, addressing system complexity, and consequently, limits the success rate of missions. the objective of this article is to delineate the methodology devised to formulate such a framework. Our approach is anchored in the utilization of the ISO/IEC TR 29110-1:2016 system engineering standard, which we propose to expand to align withthe specifications of the space sector defined in the ECSS-EST- 10C standard. the deployment of an initial version of the framework in a project undertaken by the Expleo Group, along with parallel initiatives within the European Space Agency, serves as a catalyst for further exploration in this direction.
Data flow coverage criteria are widely used in software testing, but there is almost no research on low-level data flow metrics as software defect predictors. Aims: We examine two such metrics in this context: dep-deg...
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ISBN:
(纸本)9789897586477
Data flow coverage criteria are widely used in software testing, but there is almost no research on low-level data flow metrics as software defect predictors. Aims: We examine two such metrics in this context: dep-degree (DD) proposed by Beyer and Fararooy and a new data flow metric called dep-degree density (DDD). Method: We investigate the importance of DD and DDD in SDP models. We perform a correlation analysis to check if DD and DDD measure different aspects of the code than the well-known size, complexity, and documentation metrics. Finally, we perform experiments with five different classifiers on nine projects from the Unified Bug Dataset to compare the performance of the SDP models trained with and without data flow metrics. Results: 1) DD is noticeably correlated with many other code metrics, but DDD is not correlated or is very weakly correlated with other metrics considered in this study;2) both DD and DDD are highly ranked in the feature importance analysis;3) SDP models that use DD and DDD perform better than models that do not use data flow metrics. Conclusions: Data-flow metrics: DD and DDD can be valuable predictors in SDP models.
Requirements engineering is a key skill in systems and softwareengineering. Educating students in the different forms and concepts of requirements engineering (e.g., traditional versus agile) is essential to prepare ...
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ISBN:
(纸本)9798400704987
Requirements engineering is a key skill in systems and softwareengineering. Educating students in the different forms and concepts of requirements engineering (e.g., traditional versus agile) is essential to prepare them for any technical job. However, requirements engineering education can be challenging, particularly if it is not structured around a real-world project, and thus taught only conceptually. Unfortunately, when designing lectures, educators face pedagogical, technological, and content-related challenges, such as practice-orientation, student motivation, prior knowledge of students, or even emergency situations like the COVID-19 pandemic. In this paper, we report our experiences of integrating a novel pedagogical idea into a typical requirements-engineering course that builds on the increased use of multimedia communication in all parts of society: we asked students to create videos to document and communicate requirements of diverse products. Overall, we report (i) the general design of the course;(ii) why, how, and in what form we introduced video-creation tasks;as well as (iii) the students' feedback and our experiences. Due to mostly positive feedback and the rising demand for multimedia competences in industry, we perceive the introduction of the video-creation tasks as a success for developing key skills and improving students' motivation to learn about requirements engineering. We provide an overview of our lessons learned and discuss their implications to enable other educators to integrate similar tasks in their courses, while avoiding the pitfalls we faced.
this special issue contains nine extended and rigorously peer-reviewed papers selected from those originally presented at ECBS 2023, the 8thinternationalconference on engineering of Computer-Based Systems, held at M...
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this special issue contains nine extended and rigorously peer-reviewed papers selected from those originally presented at ECBS 2023, the 8thinternationalconference on engineering of Computer-Based Systems, held at M & auml;lardalen University, Sweden, October 16-18, 2023, under the theme "engineering for Responsible AI". the included papers represent innovative contributions addressing critical aspects of responsible artificial intelligence and integrated engineering practices. these contributions span from formal verification and security analyses of IoT protocols and federated learning frameworks to machine learning-based simulations and predictions in hardware and software systems. the selection also includes work on automata learning techniques for protocol compliance, continuous integration approaches for neural network-based autonomous systems, assertion usage in software testing, language-driven engineering for code generation, and the integration of IoT backends in digital twin infrastructures. Together, these papers showcase recent advances, offering valuable insights into the rigorous integration of modern technologies within complex, computer-based systems.
Colorectal polyps can evolve into colon cancer over time. Early screening or detection of colon polyps using computer-aided detection (CAD) techniques along with removal of the polyps can lower the risk of colon cance...
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Given the importance of mechanical and plant engineering for European competitiveness, it is necessary to think beyond the current status quo. Mechanical and plant engineering is characterized by the development of la...
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ISBN:
(纸本)9798350358810;9798350358803
Given the importance of mechanical and plant engineering for European competitiveness, it is necessary to think beyond the current status quo. Mechanical and plant engineering is characterized by the development of large-scale customer-specific products. the development of such complex systems is a challenge for all disciplines, e.g. mechanics, electronics, computer science and control engineering, as they have to interact with each other. During the offer phase, an initial system concept is created. the offer phase is crucial for the company, as it is during this phase that the customer decides whether to buy the system. At the same time, since it is unclear whether the customer will accept the offer, it is a question of cost-benefit for the company. this paper examines the urgency of interdisciplinary approaches in mechanical and plant engineering, particularly in light of the increasing trend towards product customization and the global competitive landscape. the idea of a model-based approach for the offer phase in special machine construction is explicitly discussed. this approach can contribute to an efficient offer phase. the advantages of a model-based approach for the offer phase of mechanical and plant engineering are also presented in this paper. Withthe help of industry experts, different types of models are analyzed for their suitability for this phase.
Hybrid driving vehicles are a combination of AVs and non-AVs (Autonomous and non-Autonomous Vehicles). their co-existence is the inevitable future of mobility in smart cities. thus, it is very important to understand ...
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Code smells in software systems create maintenance and extension challenges for developers. While many tools detect code smells, few provide refactoring suggestions. Some of the tools support live detection in an inte...
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ISBN:
(纸本)9789897586477
Code smells in software systems create maintenance and extension challenges for developers. While many tools detect code smells, few provide refactoring suggestions. Some of the tools support live detection in an integrated development environment. We present a tool for the live detection of data clumps in Java with generated suggestions and semi-automatic refactoring. To achieve this, our research examines projects and their associated abstract syntax trees and analyzes types of variables. thereby, we aim to detect data clumps, a type of code smells, and generate suggestions to counteract them. We implemented our approach to live data clumps detection as an IntelliJ integrated development environment application plugin. the live detection achieved a median of less than 0.5 s for the ArgoUML software project, which we analyzed as an example. From over 1500 investigated files, our approach detected 125 files with data clumps and that of CBSD (Code Bad Smell Detector) detected 97 files with data clumps. For both approaches, 92 of the files found were the same. We combined the manual steps for refactoring, resulting in a semi-automatic elimination of data clumps.
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