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A Statistical Evaluation of The Depth of Inheritance Tree Metric for Open-Source Applications Developed in Java

Prykhodko Sergiy, Prykhodko Natalіa, Smykodub Tetyana

Foundations of Computing and Decision Sciences

2021

Vol. 46, No. 2

159--172

The Depth of Inheritance Tree (DIT) metric, along with other ones, is used for estimating some quality indicators of software systems, including open-source applications (apps). In cases involving multiple inheritances, at a class level, the DIT metric is the maximum length from the node to the root of the tree. At an application (app) level, this metric defines the corresponding average length per class. It is known, at a class level, a DIT value between 2 and 5 is good. At an app level, similar recommended values for the DIT metric are not known. To find the recommended values for the DIT mean of an app we have proposed to use the confidence and prediction intervals. A DIT mean value of an app from the confidence interval is good since this interval indicates how reliable the estimate is for the DIT mean values of all apps used for estimating the interval. A DIT mean value higher than an upper bound of prediction interval may indicate that some classes have a large number of the inheritance levels from the object hierarchy top. What constitutes greater app design complexity as more classes are involved. We have estimated the confidence and prediction intervals of the DIT mean using normalizing transformations for the data sample from 101 open-source apps developed in Java hosted on GitHub for the 0.05 significance level.

Updating, Integration and Making Available Spatial Data with the Use of the State-of-the-Art Technologies

Michałowska K., Głowienka-Mikrut E., Mikrut S., Bochenek M.

Geomatics and Environmental Engineering

2013

Vol. 7, no. 3

57--67

This paper presents possibilities for the utilization of spatial information derived from various sources (GPS field measurements, map scanning, data resources in centres for land survey and cartography documentation, orthophotomaps, WMS and WFS data, map Websites). It also draws attention to potential problems encountered in the process of data integration with the use of state-of-the-art processing technologies and making available geographical information. The authors also introduce the issue of the quality of processed data in the aspect of their accuracy and reliability, and the possibility of their incorporating into Spatial Data Infrastructure (SDI) resources.

W artykule przedstawiono możliwośd wykorzystania informacji przestrzennych pochodzących z różnych źródeł (pomiary terenowe GPS, skany map, zasoby danych w ośrodkach dokumentacji geodezyjnej i kartograficznej, ortofotomapy, dane WMS i WFS, serwisy mapowe). Opisano także potencjalne utrudnienia napotykane w procesie integracji danych z zastosowaniem najnowszych technologii przetwarzania i udostępniania informacji geograficznej. Autorzy poruszają także temat jakości przetworzonych danych w aspekcie ich dokładności i wiarygodności oraz możliwości włączenia do zasobów infrastruktury informacji przestrzennej (IIP).