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检索条件"主题词=Data-Driven Development"

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Towards a Digital Business Operating System 12th

Towards a Digital Business Operating System

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12th International Joint Conference on Software Technologies (ICSOFT)

作者： Bosch, Jan Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9783319936413;9783319936406

With the increasingly important role of software in industry and society overall, the traditional ways of organizing are becoming increasingly outdated. To remain competitive, companies need to adopt a new, digital business operating mechanism. In this paper, we present such a system consisting of four dimensions, i.e. speed, data, ecosystems and empowerment, and three scopes of work, i.e. operations, development and innovation.

关键词： Agile practices data-driven development Software ecosystems Empowerment

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Towards a data Engineering Process in data-driven Systems Engineering 8

Towards a Data Engineering Process in Data-Driven Systems En...

引用

International Symposium on Systems Engineering (ISSE)

作者： Petersen, Patrick Stage, Hanno Langner, Jacob Ries, Lennart Rigoll, Philipp Hohl, Carl Philipp Sax, Eric FZI Res Ctr Informat Technol Karlsruhe Germany

ISBN: (纸本)9781665481823

Highly Automated Driving (HAD) has become one of the leading trends in the automotive industry. Mandatory tasks like environment perception and scene understanding challenge existing rule-based methods. Thus, data-driven technologies and Artificial Intelligence (AI) have been introduced to automotive software development. Utilizing data in the development process has become essential as these systems are no longer developed with classical systems engineering methods, but rather by deriving requirements from and training the algorithms with recorded real-world data. This entails the introduction of data-driven workflows and data-management as new aspects of Automotive Systems Engineering (ASE). Tasks related to the development of Artificial Intelligence (AI) software differ from their classical engineering and programming counterparts. Thus, engineers require new tools and methods for developing safe and accurate AI-based software and handling data efficiently during ASE. Another important aspect of data-driven development is ensuring data quality throughout the systems engineering process. Hence, this paper aims to take a step towards the introduction of a data engineering process in data-driven automotive systems engineering. Putting a spotlight on developing well-designed data sets as the central element for training and validating AI-based software. Besides determining the quality of data sets, we present steps towards improving data and data set quality.

关键词： automotive systems engineering data-driven development ai-engineering

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Skuld: A self-learning tool for impact-driven technical debt management 3

Skuld: A self-learning tool for impact-driven technical debt...

引用

3rd IEEE/ACM International Conference on Technical Debt (TechDebt)

作者： Burgaya Pujols, Josep Bas, Pieter Martinez-Fernandez, Silverio Martini, Antonio Trendowicz, Adam Skuld Technol Barcelona Barcelona Spain Fraunhofer IESE Kaiserslautern Germany UPC Kaiserslautern Germany Skuld & Univ Oslo Oslo Norway

ISBN: (纸本)9781450379601

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 ***, 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.

关键词： Technical Debt Project Management Tool data-driven development

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Time Series Segmentation for Driving Scenario Detection with Fully Convolutional Networks 7

Time Series Segmentation for Driving Scenario Detection with...

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7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)

作者： Elspas, Philip Klose, Yannick Isele, Simon Bach, Johannes Sax, Eric Dr Ing Hc F Porsche AG Weissach Germany FZI Res Ctr Informat Technol Karlsruhe Germany

ISBN: (纸本)9789897585135

Leveraging measurement data for Advanced Driver Assistant Systems and Automated Driving Systems requires reliable meta information about covered driving scenarios. With domain expertise, rule-based detectors can be a scalable way to detect scenarios in large amounts of recorded data. However, rules might struggle with noisy data, large number of variations or corner cases and might miss valuable scenarios of interest. Finding missing scenarios manually is challenging and hardly scalable. Therefore we suggest to complement rule-based scenario detection with a data-driven approach. In this work rule-based detections are used as labels to train Fully Convolutional Networks (RCN) in a weakly supervised setup. Experiments show, that FCNs generalize well and identify additional scenarios of interest. The main contribution of this paper is twofold: First, the scenario detection is formulated as a time series segmentation problem and the capability to learn a meaningful scenario detection is demonstrated. Secondly. we show how the disagreement between the rule-based method and the learned detection method can be analyzed to find wrong or missing detections. We conclude, that the FCNs provide a scalable way to assess the quality of a rule based scenario detection without the need of large amounts of ground truth infromation.

关键词： Scenario Detection data-driven development Time Series Segmentation Fully Convolutional Networks Driving Scenarios

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A Highly Configurable Flexible Analytic Model for MCI/Frailty Risk Detection in Age-friendly Cities 26

A Highly Configurable Flexible Analytic Model for MCI/Frailt...

引用

26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM)

作者： Urosevic, Vladimir Andric, Marina Vukidcvic, Milan Tatsiopoulos, Christos Belit Ltd Belgrade Serbia AMIS Belgrade Serbia Univ Belgrade Fac Org Sci Belgrade Serbia

ISBN: (纸本)9781538667705;9789532900873

The global human population is aging rapidly, however, living longer does not necessarily mean living healthy, active and independent life. The emerging disruptive technologies like the Internet of Things (IoT) are proving instrumental in addressing this prominent societal challenge. Urban IoT infrastructures, designed to support the Smart City vision, enable capturing of personal data for analyzing behaviour of elderly people. Activities within the Horizon 2020 City4Age project are aimed at showing that behavioral analysis can help detect and mitigate risks of Mild Cognitive Impairment (MCI) and frailty problems of elderly. This paper presents the latest developments in extending the configurability and flexibility of the comprehensive City4Age computational model for risk detection. The proposed model extensions have demonstrated seamless adaptation to specific characteristics of various urban contexts, as well as seamless "pluggable" integration of various combined evolving and extendable parameterized algorithm implementations and methods for behaviour variation and risk recognition, based on relevant statistical and machine learning techniques.

关键词： geriatric model data-driven development flexible modelling configurability temporal analysis

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Challenges and Strategies for Undertaking Continuous Experimentation to Embedded Systems: Industry and Research Perspectives 19th

Challenges and Strategies for Undertaking Continuous Experim...

引用

19th International Conference on Agile Software development (XP)

作者： Mattos, David Issa Bosch, Jan Olsson, Helena Holmstrom Chalmers Univ Technol Dept Comp Sci & Engn Horselgangen 11 S-41296 Gothenburg Sweden Malmo Univ Dept Comp Sci & Media Technol S-21119 Malmo Sweden

ISBN: (纸本)9783319916026;9783319916019

Context: Continuous experimentation is frequently used in web-facing companies and it is starting to gain the attention of embedded systems companies. However, embedded systems companies have different challenges and requirements to run experiments in their systems. Objective: This paper explores the challenges during the adoption of continuous experimentation in embedded systems from both industry practice and academic research. It presents strategies, guidelines, and solutions to overcome each of the identified challenges. Method: This research was conducted in two parts. The first part is a literature review with the aim to analyze the challenges in adopting continuous experimentation from the research perspective. The second part is a multiple case study based on interviews and workshop sessions with five companies to understand the challenges from the industry perspective and how they are working to overcome them. Results: This study found a set of twelve challenges divided into three areas;technical, business, and organizational challenges and strategies grouped into three categories, architecture, data handling and development processes. Conclusions: The set of identified challenges are presented with a set of strategies, guidelines, and solutions. To the knowledge of the authors, this paper is the first to provide an extensive list of challenges and strategies for continuous experimentation in embedded systems. Moreover, this research points out open challenges and the need for new tools and novel solutions for the further development of experimentation in embedded systems.

关键词： Continuous experimentation data-driven development Controlled experiments Embedded systems

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Towards a Scenario database from Recorded Driving data with Regular Expressions for Scenario Detection 8

Towards a Scenario Database from Recorded Driving Data with ...

引用

8th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)

作者： Elspas, Philip Lindner, Jonas Brosowsky, Mathis Bach, Johannes Sax, Eric Dr Ing hcF Porsche AG Weissach Germany Karlsruhe Inst Technol Karlsruhe Germany

ISBN: (纸本)9789897585739

With increasing capabilities of Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) established automotive development processes are challenged. The specification phase faces an open world problem, with an exploding space of different driving situations and various corner cases. Scenario-based development provides a systematic approach to describe the operational design domain of ADAS and ADS with scenarios, that can be used along the development process until system qualification. However, deriving all relevant scenarios, that need to be considered remains an open challenge. Recorded driving data provides a valuable source of real-world scenarios with highest validity. A database with such scenarios can be used to validate requirements early in the specification phase. For system qualification, detected scenarios can be extended with test conditions or can be (re-)simulated. Furthermore, function development can leverage a scenario database for data-driven and machine learning methods. While a scenario database is a common concept most approaches remain abstract and vague in the description. In this work we analyze requirements and expectations on a scenarios database and propose a detailed design and concept. For the necessary scenario detection, we suggest a new method to identify complex pattern in multivariate time series based on regular expressions.

关键词： Scenario database Scenario Detection Automated Driving data-driven development

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Architecting to Ensure Requirement Relevance Keynote TwinPeaks Workshop 5

Architecting to Ensure Requirement Relevance Keynote TwinPea...

引用

Fifth International Workshop on the Twin Peaks of Requirements and Architecture TwinPeaks

作者： Bosch, Jan Chalmers Dept Comp Sci & Engn Gothenburg Sweden

ISBN: (纸本)9781467371001

Research has shown that up to two thirds of features in software systems are hardly ever used or not even used at all. This represents a colossal waste of R&D resources and occurs across the industry. On the other hand, product management and many others work hard at interacting with customers, building business cases and prioritizing requirements. A fundamentally different approach to deciding what to build is required: requirements should be treated as hypothesis throughout the development process and constant feedback from users and systems in the field should be collected to dynamically reprioritize and change requirements. This requires architectural support beyond the current state of practice as continuous deployment, split testing and data collection need to be an integral part of the architecture. In this paper, we present a brief overview of our research and industry collaboration to address this challenge.

关键词： requirements engineering software architecture data-driven development

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How To Get Good At data: 5 Steps 7

How To Get Good At Data: 5 Steps

引用

7th International Workshop on Software-Intensive Business (IWSiB)

作者： Olsson, Helena Holmstrom Bosch, Jan Malmo Univ Malmo Sweden Chalmers Univ Technol Gothenburg Sweden

ISBN: (纸本)9798400705717

data allows companies to transition towards data-driven organizations and this is, in mar experience, one of the highest-priority goals that many companies have. However, despite the prominence of data and the many opportunities associated with collection, analysis and use of data, the adoption of data-driven practices is slow. In our experience, companies fail to transition from their current state to a fully data-driven approach as the transformation is perceived as so large, complex and multi-dimensional that it becomes overwhelming and therefore, impossible to achieve in one step. We address this challenge by presenting a step-by-step process for how to transition towards fully data-driven practices. Consequently, the contribution of this paper is a model in which we outline five maturity steps for evolving towards fully data-driven practices.

关键词： data-driven development data practices software instrumentation value modeling data maturity model

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An Activity and Metric Model for Online Controlled Experiments 19th

An Activity and Metric Model for Online Controlled Experimen...

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19th International Conference on Product-Focused Software Process Improvement (PROFES)

作者： Mattos, David Issa Dmitriev, Pavel Fabijan, Aleksander Bosch, Jan Olsson, Helena Holmstrom Chalmers Univ Technol Dept Comp Sci & Engn Horselgangen 11 S-41296 Gothenburg Sweden Outreach 1441 North 34th St Seattle WA 98103 USA Malmo Univ Dept Comp Sci & Media Technol S-21119 Malmo Sweden

ISBN: (纸本)9783030036737;9783030036720

YAccurate prioritization of efforts in product and services development is critical to the success of every company. Online controlled experiments, also known as A/B tests, enable software companies to establish causal relationships between changes in their systems and the movements in the metrics. By experimenting, product development can be directed towards identifying and delivering value. Previous research stresses the need for data-driven development and experimentation. However, the level of granularity in which existing models explain the experimentation process is neither sufficient, in terms of details, nor scalable, in terms of how to increase number and run different types of experiments, in an online setting. Based on a case study of multiple products running online controlled experiments at Microsoft, we provide an experimentation framework composed of two detailed experimentation models focused on two main aspects;the experimentation activities and the experimentation metrics. This work intends to provide guidelines to companies and practitioners on how to set and organize experimentation activities for running trustworthy online controlled experiments.

关键词： data-driven development A/B tests Online controlled experiments

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