Supporting Scope Tracking and Visualization for Very Large-Scale Requirements Engineering-Utilizing FSC+, Decision Patterns, and Atomic Decision Visualizations
| Autor: | Tony Gorschek, Krzysztof Wnuk, Even-André Karlsson, Eskil Ahlin, Björn Regnell, David Callele |
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| Rok vydání: | 2016 |
| Předmět: |
Flexibility (engineering)
Scope (project management) Requirements engineering Computer science business.industry Process (engineering) 020207 software engineering 02 engineering and technology Data science Visualization Software 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software engineering business Management process Decision analysis |
| Zdroj: | IEEE Transactions on Software Engineering. 42:47-74 |
| ISSN: | 1939-3520 0098-5589 |
| DOI: | 10.1109/tse.2015.2445347 |
| Popis: | Deciding the optimal project scope that fulfills the needs of the most important stakeholders is challenging due to a plethora of aspects that may impact decisions. Large companies that operate in rapidly changing environments experience frequently changing customer needs which force decision makers to continuously adjust the scope of their projects. Change intensity is further fueled by fierce market competition and hard time-to-market deadlines. Staying in control of the changes in thousands of features becomes a major issue as information overload hinders decision makers from rapidly extracting relevant information. This paper presents a visual technique, called Feature Survival Charts+ (FSC+), designed to give a quick and effective overview of the requirements scoping process for Very Large-Scale Requirements Engineering (VLSRE). FSC+ were applied at a large company with thousands of features in the database and supported the transition from plan-driven to a more dynamic and change-tolerant release scope management process. FSC+ provides multiple views, filtering, zooming, state-change intensity views, and support for variable time spans. Moreover, this paper introduces five decision archetypes deduced from the dataset and subsequently analyzed and the atomic decision visualization that shows the frequency of various decisions in the process. The capabilities and usefulness of FSC+, decision patterns (state changes that features undergo) and atomic decision visualizations are evaluated through interviews with practitioners who found utility in all techniques and indicated that their inherent flexibility was necessary to meet the varying needs of the stakeholders. |
| Databáze: | OpenAIRE |
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