128 research outputs found

    Requirements engineering and continuous deployment

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    This article summarizes the RE in the Age of Continuous Deployment panel at the 25th IEEE International Requirements Engineering Conference. It highlights two synergistic points (user stories and linguistic tooling) and one challenge (nonfunctional requirements) in fast-paced, agile-like projects, and recommends how to carry on the dialogue.Peer ReviewedPostprint (author's final draft

    Titanium complexes of phosphinimide ligands with pendant hemilabile donars.

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    Originally published in Optics Express on 23 March 2015 (oe-23-6-7879

    The Effects of GQM+Strategies on Organizational Alignment

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    The increasing role of software for developing products and services requires that organizations align their software-related activities with high-level business goals. In practice, this alignment is very difficult and only little systematic support is available. GQM+Strategies is a method that aims at aligning organizational goals, strategies, and measurements at all levels of an organization in a seamless way. This article describes a case study of applying GQM+Strategies in a globally op- erating industrial R&D organization developing special-purpose device products for B2B customers. The study analyzes how GQM+Strategies has helped clarify and harmonize the goal set of the organization. Results of the study indicate im- proved alignment and integration of different goals. In addition, the method helped to make the initially informal goal-setting more transparent and consequently en- abled revising it while new, more important goals were discovered and compre- hended. Moreover, several elements affecting the achievement of goals as well as impediments were identified.Peer reviewe

    Data-driven elicitation, assessment and documentation of quality requirements in agile software development

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    Quality Requirements (QRs) are difficult to manage in agile software development. Given the pressure to deploy fast, quality concerns are often sacrificed for the sake of richer functionality. Besides, artefacts as user stories are not particularly well-suited for representing QRs. In this exploratory paper, we envisage a data-driven method, called Q-Rapids, to QR elicitation, assessment and documentation in agile software development. Q-Rapids proposes: 1) The collection and analysis of design and runtime data in order to raise quality alerts; 2) The suggestion of candidate QRs to address these alerts; 3) A strategic analysis of the impact of such requirements by visualizing their effect on a set of indicators rendered in a dashboard; 4) The documentation of the requirements (if finally accepted) in the backlog. The approach is illustrated with scenarios evaluated through a questionnaire by experts from a telecom company.Peer ReviewedPostprint (author's final draft

    Experiences and Insights from Applying GQM+Strategies in a Systems Product Development Organization

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    Aligning software-related activities with corporate strategies and goals is increasingly important for several reasons such as increasing the business hit rate of software-based solutions. Several approaches have been proposed to create such an alignment. GQM+Strategies is an approach that applies measurement principles to link goals and strategies on different levels of an organisation. In this paper, we describe experiences from applying GQM+Strategies to elicit, link and align the goals of an integrated systems product development organisation across multiple organisational levels. We provide detailed insights into how GQM+Strategies was applied during a five-month period. The paper presents the application process and main lessons learnt. In addition, related approaches are described and an outlook on future work is given.Peer reviewe

    Strategies to manage quality requirements in agile software development: a multiple case study

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    Agile methods can deliver software that fulfills customer needs rapidly and continuously. Quality requirements (QRs) are important in this regard; however, detailed studies on how companies applying agile methods to manage QRs are limited, as are studies on the rationale for choosing specific QR management practices and related challenges. The aim of this study was to address why practitioners manage QRs as they do and what challenges they face. We also analyzed how existing practices mitigate some of the found challenges. Lastly, we connect the contextual elements of the companies with their practices and challenges. We conducted 36 interviews with practitioners from four companies of varying sizes. Since each company operates in different domains, comparing QR management strategies and related challenges in different contexts was possible. We found that the companies apply proactive, reactive, and interactive strategies to manage QRs. Additionally, our study revealed 40 challenges in six categories that companies applying agile methods may face in QR management. We also identified nine contextual elements that affect QR management practice choices and which, importantly, can explain many related challenges. Based on these findings, we constructed a theoretical model about the connection between context, QR management practices, and challenges. Practitioners in similar contexts can learn from the practices identified in this study. Our preliminary theoretical model can help other practitioners identify what challenges they can expect to face in QR management in different developmental contexts as well as which practices to apply to mitigate these challenges.This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 732253.Peer ReviewedPostprint (published version

    Continuously assessing and improving software quality with software analytics tools: a case study

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    In the last decade, modern data analytics technologies have enabled the creation of software analytics tools offering real-time visualization of various aspects related to software development and usage. These tools seem to be particularly attractive for companies doing agile software development. However, the information provided by the available tools is neither aggregated nor connected to higher quality goals. At the same time, assessing and improving software quality has also been a key target for the software engineering community, yielding several proposals for standards and software quality models. Integrating such quality models into software analytics tools could close the gap by providing the connection to higher quality goals. This study aims at understanding whether the integration of quality models into software analytics tools provides understandable, reliable, useful, and relevant information at the right level of detail about the quality of a process or product, and whether practitioners intend to use it. Over the course of more than one year, the four companies involved in this case study deployed such a tool to assess and improve software quality in several projects. We used standardized measurement instruments to elicit the perception of 22 practitioners regarding their use of the tool. We complemented the findings with debriefing sessions held at the companies. In addition, we discussed challenges and lessons learned with four practitioners leading the use of the tool. Quantitative and qualitative analyses provided positive results; i.e., the practitioners’ perception with regard to the tool’s understandability, reliability, usefulness, and relevance was positive. Individual statements support the statistical findings and constructive feedback can be used for future improvements. We conclude that potential for future adoption of quality models within software analytics tools definitely exists and encourage other practitioners to use the presented seven challenges and seven lessons learned and adopt them in their companies.Peer ReviewedPostprint (published version

    Data-driven requirements engineering in agile projects: The Q-Rapids approach

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    Requirements identification, specification and management are key activities in the software development process. In the last years, many approaches to these activities have emerged, based on the exploitation of huge amounts of data gathered from software repositories and system usage. The Q-Rapids project proposes the collection and analysis of such data and its consolidation into a set of strategic indicators as product quality, time to market and team productivity. These indicators are visualized through a dashboard designed to support decision-makers. In this paper, we present the ongoing research undertaken in this project. We use the concept of blocking situation to exemplify the Q-Rapids approach.Peer ReviewedPostprint (author's final draft
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