DocumentCode :
3152953
Title :
Incremental delivery using abstract data types and requirements clustering
Author :
Hsia, Pei ; Gupta, Arun
Author_Institution :
Comput. Sci. Eng. Dept, Texas Univ., Arlington, TX, USA
fYear :
1992
fDate :
15-18 Jun 1992
Firstpage :
137
Lastpage :
150
Abstract :
It has been recognized that abstract data types (ADTs) are important in software development. Developers use ADTs to implement systems. Customers are usually not able to understand ADTs due to lack of technical knowledge. Thus, they may not easily envision (or rather, may not be concerned with) how the use of ADTs meet their requirements. This paper uses the concepts of ADTs to accomplish incremental delivery and develops a methodology to deliver data-dominant systems incrementally. An important outcome of this methodology is an algorithm to cluster requirements based on ADTs obtained from the Onion methodology. A case study demonstrating the methodology is presented
Keywords :
abstract data types; systems analysis; abstract data types; data-dominant systems; incremental delivery; requirements clustering; software development; Clustering algorithms; Computer science; Educational institutions; Feedback; Programming; Software development management; Software engineering; Software systems; Usability; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems Integration, 1992. ICSI '92., Proceedings of the Second International Conference on
Conference_Location :
Morristown, NJ
Print_ISBN :
0-8186-2697-6
Type :
conf
DOI :
10.1109/ICSI.1992.217275
Filename :
217275
Link To Document :
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