Automated Software Size Estimation Methods And Techniques: A Review

2017 ◽  
Vol 6 (4) ◽  
pp. 38
Author(s):  
ATTRI V.K. ◽  
BAL J.S. ◽  
◽  
Keyword(s):  
Estimation Methods ◽  
Size Estimation ◽  
Methods And Techniques ◽  
Software Size Estimation ◽  
Automated Software

Automated software size estimation based on function points using UML models

2005 ◽  
Vol 47 (13) ◽  
pp. 881-890 ◽  
Author(s):  
Aleš Živkovič ◽  
Ivan Rozman ◽  
Marjan Heričko
Keyword(s):  
Size Estimation ◽  
Function Points ◽  
Software Size Estimation ◽  
Automated Software ◽  
Uml Models

scholarly journals Using Actors and Use Cases for Software Size Estimation

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 592
Author(s):  
Radek Silhavy ◽  
Petr Silhavy ◽  
Zdenka Prokopova
Keyword(s):  
Project Planning ◽  
Use Cases ◽  
New Method ◽  
Software Systems ◽  
Software Project ◽  
Use Case ◽  
Size Estimation ◽  
Software Size Estimation ◽  
Use Case Points

Software size estimation represents a complex task, which is based on data analysis or on an algorithmic estimation approach. Software size estimation is a nontrivial task, which is important for software project planning and management. In this paper, a new method called Actors and Use Cases Size Estimation is proposed. The new method is based on the number of actors and use cases only. The method is based on stepwise regression and led to a very significant reduction in errors when estimating the size of software systems compared to Use Case Points-based methods. The proposed method is independent of Use Case Points, which allows the elimination of the effect of the inaccurate determination of Use Case Points components, because such components are not used in the proposed method.

scholarly journals A Pilot Study on Home Range and Habitat Use of Chinese Goral (Naemorhedus Griseus): Exploring GPS Tracking Data in Cliff Landscape by Three Estimation Methods

2021 ◽  
Author(s):  
yang teng ◽  
Shupei TANG ◽  
lai heda meng ◽  
Liji Wu ◽  
Zhiqing HAN ◽  
...  
Keyword(s):  
Home Range ◽  
Habitat Use ◽  
Estimation Methods ◽  
Conservation Strategies ◽  
Gps Tracking ◽  
Tracking Data ◽  
Size Estimation ◽  
Range Estimation ◽  
Lower Altitude ◽  
Effective Conservation

Abstract Home range size estimation is a crucial basis for developing effective conservation strategies and provides important insights into animal behavior and ecology. This study aimed at analyzing the home range variations, the influence of altitude in habitat selection, and comparing three methods in home range estimation of Chinese gorals (Naemorhedus griseus) living at a cliff landscape. The results indicated that there were significant differences between the annual home range sizes of individual animals but there was no difference in their seasonal home range sizes based on GPS tracking data of five female Chinese gorals from February 2015 to September 2018. The monthly home ranges decreased dramatically in May, June and July due to birth-giving. Notable seasonal variations were found in the micro-habitats of the Chinese gorals, as reflected by the altitude they inhabit, with higher altitude habitats used in spring and lower altitude habitats used in winter. Additionally, the altitude of monthly habitats was lowest in January, which may indicate an adaptation to low air temperature. We also found differences between estimation methods, namely minimum convex polygon (MCP), kernel density estimation (KDE) and α-local convex hull (α-LoCoH), with seasonal home range sizes derived from α-LoCoH being substantially smaller than those derived from MCP and KDE. In conclusion, our findings filled the gaps in home range study for this endangered species and contributed to effective conservation strategies. Considerations shall have to be given to the variations in home range estimation caused by different methods when dealing with rugged habitats, so as to make sure that any interpretation concerning the habitat use of the targeted species made on basis of such results would be meaningful and valid.

scholarly journals A Pilot Study on Home Range and Habitat Use of Chinese Goral (Naemorhedus Griseus): Exploring GPS Tracking Data in Cliff Landscape by Three Estimation Methods

2021 ◽  
Author(s):  
Yang Teng ◽  
Shupei TANG ◽  
Dalai Menghe ◽  
Liji Wu ◽  
Zhiqing HAN ◽  
...  
Keyword(s):  
Home Range ◽  
Habitat Use ◽  
Estimation Methods ◽  
Conservation Strategies ◽  
Gps Tracking ◽  
Tracking Data ◽  
Size Estimation ◽  
Range Estimation ◽  
Lower Altitude ◽  
Effective Conservation

Abstract Home range size estimation is a crucial basis for developing effective conservation strategies and provides important insights into animal behavior and ecology. This study aimed at analyzing the home range variations, the influence of altitude in habitat selection, and comparing three methods in home range estimation of Chinese gorals (Naemorhedus griseus) living at a cliff landscape. The results indicated that there were significant differences between the annual home range sizes of individual animals but there was no difference in their seasonal home range sizes based on GPS tracking data of five female Chinese gorals from February 2015 to September 2018. The monthly home ranges decreased dramatically in May, June and July due to birth-giving. Notable seasonal variations were found in the micro-habitats of the Chinese gorals, as reflected by the altitude they inhabit, with higher altitude habitats used in spring and lower altitude habitats used in winter. Additionally, the altitude of monthly habitats was lowest in January, which may indicate an adaptation to low air temperature. We also found differences between estimation methods, namely minimum convex polygon (MCP), kernel density estimation (KDE) and α-local convex hull (α-LoCoH), with seasonal home range sizes derived from α-LoCoH being substantially smaller than those derived from MCP and KDE. In conclusion, our findings filled the gaps in home range study for this endangered species and contributed to effective conservation strategies. Considerations shall have to be given to the variations in home range estimation caused by different methods when dealing with rugged habitats, so as to make sure that any interpretation concerning the habitat use of the targeted species made on basis of such results would be meaningful and valid.

On the Application of Automated Software Testing Techniques to the Development and Maintenance of Speech Recognition Systems

2012 ◽  
pp. 30-48
Author(s):  
Daniel Bolanos
Keyword(s):  
Speech Recognition ◽  
Software Testing ◽  
Automatic Speech Recognition ◽  
Automated Testing ◽  
Automated Software Testing ◽  
Testing Framework ◽  
Methods And Techniques ◽  
Testing Techniques ◽  
Recognition Systems ◽  
Automated Software

This chapter provides practitioners in the field with a set of guidelines to help them through the process of elaborating an adequate automated testing framework to competently test automatic speech recognition systems. Through this chapter the testing process of such a system is analyzed from different angles, and different methods and techniques are proposed that are well suited for this task.

Multimedia Quality of Experience

2016 ◽  
pp. 250-284
Author(s):  
Jeevan Pokhrel ◽  
Natalia Kushik ◽  
Bachar Wehbi ◽  
Nina Yevtushenko ◽  
Ana Rosa Cavalli
Keyword(s):  
User Satisfaction ◽  
Quality Of Experience ◽  
Learning Algorithms ◽  
Estimation Methods ◽  
The Internet ◽  
Successful Transmission ◽  
Methods And Techniques ◽  
Future Challenges ◽  
The Media

This chapter introduces the overall concept of multimedia Quality of Experience (QoE) over the Internet. It presents all the elements of multimedia QoE ecosystem and emphasizes their roles in determining the user satisfaction. The chapter also presents different multimedia transmission components and how these components contribute to successful transmission of the media content. In addition, some key performance indicators relevant to the multimedia QoE are presented with more emphasis on network and application level indicators. Furthermore, different QoE estimation methods and techniques along with QoS/QoE learning algorithms are presented. Finally, the chapter includes some of the future challenges and issues related to multimedia QoE.

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