Pregled bibliografske jedinice broj: 1061566
Data Mining Approach to Effort Modeling On Agile Software Projects
Data Mining Approach to Effort Modeling On Agile Software Projects // Informatica (Ljubljana), 44 (2020), 2; 231-239 doi:10.31449/inf.v44i2.2759 (međunarodna recenzija, članak, znanstveni)
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Naslov
Data Mining Approach to Effort Modeling On Agile
Software Projects
Autori
Karna, Hrvoje ; Gotovac, Sven ; Vicković, Linda
Izvornik
Informatica (Ljubljana) (0350-5596) 44
(2020), 2;
231-239
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
agile scrum ; data mining ; effort estimation ; k-nearest neighbor ; software engineering ; project management
Sažetak
Software production is a complex process. Accurate estimation of the effort required to build the product, regardless of its type and applied methodology, is one of the key problems in the field of software engineering. This study presents the approach to effort estimation on agile software project using local data and data mining techniques, in particular k-nearest neighbor clustering algorithm. The applied process is iterative, meaning that in order to build predictive models, sets of data from previously executed project cycles are used. These models are then utilized to generate estimate for the next development cycle. Used data enrichment process, proved to be useful as results of effort prediction indicate decrease in estimation error compared to the estimates produced solely by the estimators. The proposed approach suggests that similar models can be built by other organizations as well, using the local data at hand and this way optimizing the management of the software product development.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)
- Scopus