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  • 1.
    Bjarnason, Elizabeth
    et al.
    Lund University, Sweden.
    Borg, Markus
    RISE, Swedish ICT, SICS, Security Lab.
    Aligning Requirements and Testing - Working Together Toward the Same Goal2017In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 34, no 1, p. 20-23, article id 7819382Article in journal (Other academic)
    Abstract [en]

    The proper alignment of requirements engineering and testing (RET) can be key to software's success. Three practices can provide effective RET alignment: using test cases as requirements, harvesting trace links, and reducing distances between requirements engineers and testers. The Web extra https://youtu.be/M65ZKxfxqME is an audio podcast of author Elizabeth Bjarnason reading the the Requirements column she cowrote with Markus Borg.

    Download full text (pdf)
    fulltext
  • 2.
    Gregory, Sarah
    et al.
    Intel Internet of Things Group, USA.
    Borg, Markus
    RISE Research Institutes of Sweden. Lund University, Sweden.
    Looking Back, Moving Forward: A Handover2022In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 39, no 5, p. 17-20Article in journal (Refereed)
    Abstract [en]

    A coworker teased me a few months ago, describing requirements engineering (RE) as "plumbing,"something he absolutely considered functional, even necessary, but otherwise best not discussed in polite conversation. I responded with a graphically descriptive suggestion of what one might experience with a plumbing failure. I then drew parallels to a situation where a team's excellent execution of their standard requirements practice proved insufficient for the complex circumstances of their newest program. Although they'd laid the pipes as intended with the tools and practices with which they were proficient, this "new construction" had different needs.

  • 3.
    Linåker, Johan
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Robles, Gregorio
    Universidad Rey Juan Carlos, Spain.
    Bryant, Deborah
    Open Source Initiative, USA.
    Sashiko, Muto
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Open Source Software in the Public Sector: 25 Years and Still in Its Infancy2023In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 40, no 4, p. 39-44Article, review/survey (Refereed)
    Abstract [en]

    The proliferation of Open Source Software (OSS) adoption and collaboration has surged within industry, resulting in its ubiquitous presence in commercial offerings and shared digital infrastructure. However, in the public sector, both awareness and adoption of OSS is still in its infancy due to a number of obstacles including regulatory, cultural, and capacity-related challenges. This special issue is a call for action, highlighting the necessity for both research and practice to narrow the gap, selectively transfer and adapt existing knowledge, as well as generate new knowledge to enable the public sector to fully harness the potential benefits OSS has to offer. 

  • 4.
    Linåker, Johan
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Runeson, Per
    Lund University, Sweden.
    Zuiderwijk, Anneke
    Delft University of Technology, Netherlands.
    Brock, Aamanda
    OpenUK, UK.
    Collaborative Aspects of Open Data in Software Engineering2022In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 39, no 1, p. 31-35Article in journal (Refereed)
    Abstract [en]

    Engineers require high-quality data for the design and implementation of today's software, especially in the context of machine learning (ML). This puts an emphasis on the need for the publication and sharing of data from and between organizations, public as well as private. Following the paradigm of open innovation, open data provide a mechanism to increase the availability of information, offering utility and improving innovation and user choice through the inevitable interoperability this enables. 

  • 5.
    Martini, Antonio
    et al.
    University of Oslo, Norway.
    Besker, Terese
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Posch, Torsten
    Siemens AG, Germany.
    Bosch, Jan
    Chalmers University of Technology, Sweden.
    TD Pulse: Assessing the Systematic Management of Technical Debt2023In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 40, no 3, p. 54-62Article in journal (Refereed)
    Abstract [en]

    Technical Debt requires the management of several technical and non-technical aspects: process, organization, tools, etc. Software companies must identify where TD is not well managed and where to improve. Based on ten years of research and practice, we have created an effective approach, TD Pulse, to assess Technical Debt Management in large software companies and find critical improvement areas. The approach was used by 232 and evaluated by more than 200 practitioners in three large companies, including Siemens and Zenseact. The results show that our approach is valuable and lightweight. We also share lessons learned from the whole assessment experience. 

  • 6.
    Mellegård, Niklas
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, Viktoria.
    Burden, Håkan
    RISE - Research Institutes of Sweden (2017-2019), ICT, Viktoria.
    Levin, Daniel
    Volvo Car Corporation, Sweden.
    Lind, Kenneth
    HiMinds Göteborg AB, Sweden.
    Magazinius, Ana
    RISE - Research Institutes of Sweden (2017-2019), ICT, Viktoria.
    Contrasting Big Bang with Continuous Integration Through Defect Reports2020In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 37, no 3, p. 14-20Article in journal (Refereed)
    Abstract [en]

    Continuous integration promises earlier defect detection, quality improvements and more customer value delivered faster. But what evidence is there? In this longitudinal case study we examined the development of software for the advanced safety and driver support component of a Swedish vehicle manufacturer in two consecutive projects, where the first was developed in a big bang fashion, typical to a traditional waterfall process, while the second project utilized continuous integration. By contrasting the two projects, we evaluated the introduction of continuous integration and supplement earlier claims based on interview studies with a quantitative analysis of defect reports.

  • 7.
    Rudmark, Daniel
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Andersson, Magnus
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Feedback Loops in Open Data Ecosystems2022In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 39, no 1Article in journal (Refereed)
    Abstract [en]

    Public agencies are increasingly publishing open data to increase transparency and fuel data-driven innovation. For these organizations, maintaining sufficient data quality is key to continuous re-use but also heavily dependent on feedback loops being initiated between data publishers and users. This paper reports from a longitudinal engagement with Scandinavian transportation agencies, where such feedback loops have been successfully established. Based on these experiences, we propose four distinct types of data feedback loops in which both data publishers and re-users play critical roles.

    Download full text (pdf)
    fulltext
  • 8.
    Rudmark, Daniel
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems. University of Gothenburg, Sweden.
    Lindman, Juho
    University of Gothenburg, Sweden.
    Tryti, Andreas
    Entur AS, Norway.
    Dammen, Brede
    Entur AS, Norway.
    Beyond Procurement: How Entur Navigated the Open Source Journey to Advance Public Transport2023In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 40, no 4, p. 62-70Article in journal (Refereed)
    Abstract [en]

    This report describes how software professionals at the Norwegian public transport organization Entur use open source processes and tools to leverage digital transformation. Moving software acquisition from procurement to open source and in-house development can deliver value but also entails challenges. 

  • 9.
    Scharinger, Boris
    et al.
    Siemens Digital Industries, Germnay.
    Borg, Markus
    RISE Research Institutes of Sweden. Lund University, Sweden.
    Vogelsang, Andreas
    University of Cologne, Germany.
    Olsson, Thomas
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.
    Can RE Help Better Prepare Industrial AI for Commercial Scale?2022In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 39, no 6, p. 8-12Article in journal (Refereed)
    Abstract [en]

    This issue marks the start of my term as department editor for the “Requirements” column. I very much look forward to exploring contemporary aspects of requirements and requirements engineering (RE) in the coming years! As an institute researcher with RISE, I primarily work in strictly regulated domains, in which requirements are cornerstones in the development activities. Please check my introduction in the September/October 2022 issue of IEEE Software for more about my background. In this issue—featuring a theme that perfectly matches my current research interests—we discuss RE4AI from the perspective of Siemens Digital Industries. Referring to this as industrial artifical intelligence (AI), we share insights from our numerous chats about this topic in the last two years, including formal interviews with key stakeholders. In this column, we argue that the business side of AI has been underexplored—and that RE can help us forward.

  • 10.
    Trubiani, Catia
    et al.
    Gran Sasso Science Institute, Italy.
    Jamshidi, Pooyan
    University of South Carolina, USA.
    Cito, Jurgen
    Massachusetts Institute Technology, USA.
    Shang, Weiyi
    Concordia University, Canada.
    Jiang, Zhen Ming
    York University, Canada.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Performance Issues?: Hey DevOps, Mind the Uncertainty!2019In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 36, no 2, p. 110-117, article id 8501933Article in journal (Refereed)
    Abstract [en]

    DevOps is a novel trend that aims to bridge the gap between software development and operation teams. When applied to the performance evaluation process, it brings new challenges since developers need to be aware of the deployment settings and application runtime characteristics. At the operational stage, several uncertainties, e.g., workload fluctuations and resource availability, may affect the performance analysis. The goal of this paper is to identify the uncertain parameters and quantify their propagation to performance analysis results, in order to bring upfront the main system criticisms. To this end, we make use of a popular big data system showing that the sources of uncertainty may span on different characteristics and the performance analysis results can be heavily affected by these uncertainties. The paper contributes as an experience report aiming to better identify performance uncertainties through a case study. It provides a step-by-step guide to practitioners for controlling system uncertainties.

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