%0 Conference Paper %1 laskey00 %A Laskey, Kathryn B. %A Barry, Philip %A Brouse, Peggy %B 2th Intl Conf. on Software Engineering and Knowledge Engineering %C Chicago, IL %D 2000 %K uncertainty requirements uml bayes litmap %T Breaking the Knowledge Bottleneck for Bayesian Networks Using Language (UML) Artifacts %U http://citeseer.ist.psu.edu/458714.html %X Effective requirements management has been recognized as a key element in the creation of systems. This exercise involves a significant amount of uncertainty, as the requirements analyst is often unsure if the system requirements specified actually provide the functionality the user wants. Previous work demonstrated how system functionality within a given domain could be modeled as a library of Bayesian network fragments. These fragments can be combined into larger networks to model...

@inproceedings{laskey00, abstract = {Effective requirements management has been recognized as a key element in the creation of systems. This exercise involves a significant amount of uncertainty, as the requirements analyst is often unsure if the system requirements specified actually provide the functionality the user wants. Previous work demonstrated how system functionality within a given domain could be modeled as a library of Bayesian network fragments. These fragments can be combined into larger networks to model...}, added-at = {2006-03-24T16:34:33.000+0100}, address = {Chicago, IL}, author = {Laskey, Kathryn B. and Barry, Philip and Brouse, Peggy}, biburl = {https://www.bibsonomy.org/bibtex/2a8c7852f81a5c63377615714bc4b109e/neilernst}, booktitle = {2th Intl Conf. on Software Engineering and Knowledge Engineering}, citeulike-article-id = {295606}, comment = {- consider applying this to i* - this uses UML use case and analysis models (analysis models sounds like i*) - distinguishes between user and system requirements (what is this distinction) - the DBN can only give results on what is known (based on incoming information -- Winograd) - used to compare use case diagrams with sequence diagrams, e.g. what is the probability that a user requirement (as specified in use case) is filled? Which assumes that sequence diagrams map 1-1 to system performance, which is nonsense. Problem in validating these predictions given that you never have accurate data on the system.}, description = {sdasda}, interhash = {e9415ee0dd491102cecf7301e09bab0f}, intrahash = {a8c7852f81a5c63377615714bc4b109e}, keywords = {uncertainty requirements uml bayes litmap}, month = {July}, priority = {0}, timestamp = {2006-03-24T16:34:33.000+0100}, title = {Breaking the Knowledge Bottleneck for Bayesian Networks Using Language (UML) Artifacts}, url = {http://citeseer.ist.psu.edu/458714.html}, year = 2000 }