Uporaba programskih metrik za vrednotenje kakovosti projektov Python

magistrsko delo

Robert Malačič (Author), Marjan Heričko (Mentor)

Abstract

Programske metrike so ključne za doseganje želene kakovosti programskih in informacijskih sistemov ter identifikacijo komponent, ki jih je potrebno preoblikovati in izboljšati. V magistrskem delu smo raziskali, ali lahko uveljavljene objektno orientirane programske metrike uporabimo tudi v projektih Python. S pomočjo pregleda literature in analize orodij za zbiranje metričnih vrednosti smo identificirali metrike, primerne za vrednotenje kakovosti programskih rešitev, razvitih v jeziku Python. V empiričnem delu raziskave smo izbrane metrike uporabili pri analizi programske kode enainštiridesetih projektov Python. Ugotovili smo, da lahko na osnovi objektno orientiranih metrik kot so npr. WMC, DIT, RFC, NOC, kot tudi nekaterih klasičnih metrik, kot je ciklomatična kompleksnost vrednotimo in primerjamo kakovost posameznih projektov, kot tudi identificiramo slabo oblikovane razrede. Dodatno smo ugotovili, da lahko koncept tehničnega dolga uporabimo tudi za projekte Python.

Keywords

informacijski sistemi;programska oprema;Phyton;kakovost projektov;magistrske naloge;

Data

Language:	Slovenian
Year of publishing:	2016
Typology:	2.09 - Master's Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	R. Malačič
UDC:	004.43(043)
COBISS:	20139030
Views:	1012
Downloads:	159
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Use of software metrics to evaluate the quality of Python projects
Secondary abstract:	Software metrics are the key to achieving the desired quality of software and information systems, and for identification of components that need to be transformed and improved. In this thesis, we investigated whether the established object oriented software metrics can be also used in Python projects. Through literature review and analysis of tools which collect the metric values we identified metrics appropriate for evaluation of quality of software solutions developed in the Python program language. Within the empirical part of the research, we used metrics in the analysis of the program code of forty-one Python projects. We found that on the basis of the object-oriented metrics like WMC, DIT, RFC, NOC as well as on the basis of some classic metrics such as cyclomatic complexity, we can evaluate and compare the quality of individual projects as well as identify the badly designed classes. Furthermore, we found that the concept of technical debt could also be used for Python projects.
Secondary keywords:	information systems;software;Phyton;quality metrics;
URN:	URN:SI:UM:
Type (COBISS):	Master's thesis
Thesis comment:	Univ. v Mariboru, Fak. za elekrotehniko, računalništvo in informatiko
Pages:	VIII, 135 str.
ID:	9144668