| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Show document

Title:Primerjava samodejne in manualne ocene količine tehničnega dolga : magistrsko delo
Authors:Hliš, Tilen (Author)
Pavlič, Luka (Mentor) More about this mentor... New window
Stropnik, Ambrož (Co-mentor)
Files:.pdf MAG_Hlis_Tilen_2020.pdf (2,60 MB)
MD5: 35B8C0444E9139553333A5DA9C502E84
Work type:Master's thesis/paper (mb22)
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu smo raziskali področje metod za ocenjevanje količine tehničnega dolga. Izvedli smo sistematičen pregled literature, s katerim smo raziskali metode, ki se uporabljajo v orodjih za samodejno ocenjevanje količine tehničnega dolga. Analizirali in zbrali smo orodja, ki te metode implementirajo. Na petih izbranih projektih razvoja informacijskih rešitev smo izvedli popis tehničnega dolga. Pri tem smo najprej izvedli manualno identifikacijo in ocenjevanje količine tehničnega dolga. Sledila je samodejna identifikacija in ocenjevanje količine tehničnega dolga s pomočjo orodij. V zaključnem delu popisovanja smo dobljene manualne in samodejne ocene med seboj primerjali in analizirali. Empirični podatki, pridobljeni v popisu nakazujejo na velik razkorak med manualno in samodejno oceno.
Keywords:tehničen dolg, metode ocenjevanja, orodja, merjenje
Year of publishing:2020
Place of performance:Maribor
Publisher:[T. Hliš]
Number of pages:XI, 80 str.
COBISS_ID:27330819 New window
Categories:KTFMB - FERI
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
AddThis uses cookies that require your consent. Edit consent...

Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.


License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:14.06.2020

Secondary language

Title:Comparing the automatic and the manual estimates of the technical debt amount
Abstract:In this master thesis, we report a researched in the field of the methods of the technical debt amount estimation. We conducted a systematic literature review to investigate the methods used in a tools for automatically estimating the amount of technical debt. We analysed and collected the tools that implement these methods. We collected technical debt items on a five selected software projects, in which we firstly performed manual identification and estimation of the amount of technical debt. We followed by automatic identification and assessment. In the final part, the obtained manual and automatic estimates were compared and analysed. The empirical data obtained indicate a gap between manual and automatic estimation.
Keywords:technical debt, methods for estimating, tools, measurement


Leave comment

You have to log in to leave a comment.

Comments (0)
0 - 0 / 0
There are no comments!

Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica