Today, software teams can deploy new software versions to users at an increasing speed - even continuously. Although this has enabled faster responding to changing customer needs than ever before, the speed of automat...
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ISBN:
(纸本)9783319576336;9783319576329
Today, software teams can deploy new software versions to users at an increasing speed - even continuously. Although this has enabled faster responding to changing customer needs than ever before, the speed of automated customer feedback gathering has not yet blossomed out at the same level. For these purposes, the automated collecting of quantitative data about how users interact with systems can provide software teams with an interesting alternative. When starting such a process, however, teams are faced immediately with difficult decision making: What kind of technique should be used for collecting user-interaction data? In this paper, we describe the reasons for choosing specific collecting techniques in three cases and refine a previously designed selection framework based on their data. the study is a part of on-going design science research and was conducted using case study methods. A few distinct criteria which practitioners valued the most arose from the results.
It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startup...
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ISBN:
(纸本)9783319576336;9783319576329
It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups can learn depends on how fast they can prototype. Despite of the importance, there is a lack of research about prototyping in software startups. In this study, we aimed at understanding what are factors influencing different types of prototyping activities. We conducted a multiple case study on twenty European software startups. the results are two folds;firstly we propose a prototype-centric learning model in early stage software startups. Secondly, we identify factors occur as barriers but also facilitators for prototyping in early stage software startups. the factors are grouped into (1) artifacts, (2) team competence, (3) collaboration, (4) customer and (5) process dimensions. To speed up a startup's progress at the early stage, it is important to incorporate the learning objective into a well-defined collaborative approach of prototyping.
there has been a significant impact on software development lifecycle by the non-plan driven softwareprocesses such as agile derived models i.e. Scrum, extremeprogramming (XP) and recently introduced DevOps practice...
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softwareengineering (SE) practitioners must follow mature and quality processes, so that they can compete in an industry that demands quality products. In order to address this need, SEI proposed a personal methodolo...
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In agile, fast and continuous development lifecycles, software performance analysis is fundamental to confidently release continuously improved software versions. Researchers and industry practitioners have identified...
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ISBN:
(纸本)9781450348997
In agile, fast and continuous development lifecycles, software performance analysis is fundamental to confidently release continuously improved software versions. Researchers and industry practitioners have identified the importance of integrating performance testing in agile development processes in a timely and efficient way. However, existing techniques are fragmented and not integrated taking into account the heterogeneous skills of the users developing polyglot distributed software, and their need to automate performance practices as they are integrated in the whole lifecycle without breaking its intrinsic velocity. In this paper we present our vision for holistic continuous software performance assessment, which is being implemented in the BenchFlow tool. BenchFlow enables performance testing and analysis practices to be pervasively integrated in continuous development lifecycle activities. Users can specify performance activities (e.g., standard performance tests) by relying on an expressive Domain Specific Language for objective-driven performance analysis. Collected performance knowledge can be thus reused to speed up performance activities throughout the entire process.
this paper continues telling the story begun in "It has been a long journey, and it is not over yet" (published in agile Process in softwareengineering and extremeprogramming XP2015, Helsinki – 2015). thi...
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What do you do when you have endured an agile experience where things didn’t go so well? You can abandon agile altogether or you can take those lessons learned and apply them to future agile projects. this paper disc...
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Kainos is a software company based in Belfast, Northern Ireland. As well as bespoke development, its work includes service contracts for the maintenance of software created elsewhere. this type of work is challenging ...
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In the last two decades, agile and Lean approaches have gained wide acceptance in the software industry. In this realm, Kanban emerged in 2004 with a strong practitioner-driven support movement and today, Kanban is in...
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