180 research outputs found

    Self-organising Roles in Agile Globally Distributed Teams

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    The ability to self-organise is posited to be a fundamental requirement for successful agile teams. In particular, self-organising teams are said to be crucial in agile globally distributed software development (AGSD) settings, where distance exacerbates team issues. We used contextual analysis to study the specific interaction behaviours and enacted roles of practitioners working in multiple AGSD teams. Our results show that the teams studied were extremely task focussed, and those who occupied team lead or programmer roles were central to their teams’ self-organisation. These findings have implications for AGSD teams, and particularly for instances when programmers – or those occupying similar non-leadership positions – may not be willing to accept such responsibilities. We discuss the implications of our findings for information system development (ISD) practice

    Data gathering for actor analyses: A research note on the collection and aggregation of individual respondent data for MACTOR

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    The augmentation of future studies with data on actors and their interactions is suggested as a means to reduce uncertainty and to account for extreme or unexpected future outcomes due to the involvement of multiple actors and their competing perspectives and options. In the context of New Zealand’s health workforce forecasting environment, this research note presents a systematic method to gather and aggregate actor data developed for a recent foresight study. The method identifies the issues encountered and solutions developed when gathering data from time poor respondents representing diverse and sometimes oppositional actors, and for the coding and aggregation of these data for use in LIPSOR’s actor analysis tool, MACTOR. Worked examples are provided to demonstrate the method’s application with the software

    Towards a standardised strategy to collect and distribute application software artifacts

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    Reference sets contain known content that are used to identify relevant or filter irrelevant content. Application profiles are a type of reference set that contain digital artifacts associated with application software. An application profile can be compared against a target data set to identify relevant evidence of application usage in a variety of investigation scenarios. The research objective is to design and implement a standardised strategy to collect and distribute application software artifacts using application profiles. An advanced technique for creating application profiles was designed using a formalised differential analysis strategy. The design was implemented in a live differential forensic analysis tool, LiveDiff, to automate and simplify data collection. A storage mechanism was designed based on a previously standardised forensic data abstraction. The design was implemented in a new data abstraction, Application Profile XML (APXML), to provide storage, distribution and automated processing of collected artifacts
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