Picking the right problem frame - an empirical study

This source preferred by Keith Phalp

Authors: Phalp, K.T. and Cox, K.

http://www.springerlink.com/content/g034346w784u3540/?p=f4d5eca7a4eb4bee8ae55b8aea249ca4&pi=4

Journal: Empirical Software Engineering

Volume: 5

Pages: 215-228

ISSN: 1382-3256

DOI: 10.1023/A:1026538531893

Problemframes are a relatively new approach to requirements engineering,promising benefits not only in elicitation but also in subsequentdesign, by allowing their users to select methods and techniquesappropriate to their given problem domain. In order to be effectivethis approach relies upon the correct identification of relevantproblem frames for a given problem or scenario. Hence, we examinewhether people are able to identify the correct (relevant) framesfor a given set of problem descriptions, and whether they cancorrectly gauge the relative contribution of each identifiedframe to the given problem. We note the Euclidean distance of(individual and group) answers from an expert solution, consideringeach problem frame as a separate dimension. Examination of thisdistance (or magnitude of error) allows us to gauge the accuracywith which people can assign problem frames. We compare the performanceof individuals within groups, and the performance where groupswork together to provide a collective solution, comparing bothof these with a fair-distribution strategy. We found that peoplecan choose the relevant frames with a reasonable degree of accuracy,but that this is improved where they work to provide a collectivesolution. We also note differences among groups, for example,that experience appears to improve the accuracy with which groupscan collectively choose relevant frames.

This data was imported from DBLP:

Authors: Phalp, K. and Cox, K.

Journal: Empirical Software Engineering

Volume: 5

Pages: 215-228

This data was imported from Scopus:

Authors: Phalp, K. and Cox, K.

Journal: Empirical Software Engineering

Volume: 5

Issue: 3

Pages: 215-228

ISSN: 1382-3256

DOI: 10.1023/A:1026538531893

Problem frames are a relatively new approach to requirements engineering, promising benefits not only in elicitation but also in subsequent design, by allowing their users to select methods and techniques appropriate to their given problem domain. In order to be effective this approach relies upon the correct identification of relevant problem frames for a given problem or scenario. Hence, we examine whether people are able to identify the correct (relevant) frames for a given set of problem descriptions, and whether they can correctly gauge the relative contribution of each identified frame to the given problem. We not the Euclidean distance of (individual and group) answers from an expert solution, considering each problem frame as a separate dimension. Examination of this distance (or magnitude of error) allows us to gauge the accuracy with which people can assign problem frames. We compare the performance of individuals within groups, and the performance where groups work together to provide a collective solution, comparing both of these with a fair-distribution strategy. We found that people can choose the relevant frames with a reasonable degree of accuracy, but that this is improved where they work to provide a collective solution. We also note differences among groups, for example, that experience appears to improve the accuracy with which groups can collectively choose relevant frames.

The data on this page was last updated at 04:56 on September 25, 2018.