Browsing by Author "Kocyigit, Altan"

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A Case Study on the Utilization of Problem and Solution Domain Measures for Software Size Estimation
(2016) Ayyildiz, Tulin Erelebi; Kocyigit, Altan; 0000-0002-7372-0223; 0000-0001-5003-4127; AAE-1726-2021; S-6347-2016
Detailed requirements is the primary input of software size measurement and effort estimation methodologies and a significant amount of time and expertise is needed for size measurement. In order to streamline size measurement and effort estimation, this study exploits the correlations between the problem domain measures such as the number of distinct nouns and distinct verbs in the requirements artifacts and the solution domain measures such as the number of software classes and methods in the corresponding object oriented software. In this case study, 12 commercial software projects are analyzed and multiple regression analysis is carried out to develop an estimation model for the solution domain metrics in terms of problem domain metrics. The results suggest that, for the projects examined, it is possible to use problem domain measures to make plausible predictions for the solution domain metrics.
Correlations between problem and solution domain measures of open source software
(2017) Ayyidiz, Tulin Ercelebi; Kocyigit, Altan; 0000-0002-7372-0223; AAE-1726-2021
Software size measurement and effort estimation methodologies in use today usually take the detailed requirements of software to be developed as the primary input and a certain amount of time and expertise is needed for size measurement. This paper analyzes the open source projects' correlations between the problem domain measures (the number of nouns and verbs) and solution domain measures (the number of software classes and methods). In this paper, 27 open source software projects are analyzed. Linear regression and cross validation techniques are applied to investigate the relation between the sizes of problem domain (i.e., conceptual) and solution domain (i.e., design) measures. The results reveal a strong correlation between the problem domain measures and the solution domain measures constituting the corresponding software. The results suggest that it is possible to use problem domain descriptions in the early stages of software development projects to make plausible predictions for the size and effort of the software.
Correlations Between Problem Domain and Solution Domain Size Measures for Open Source Software
(2014) Ayyildiz, Tulin Ercelebi; Kocyigit, Altan; https://orcid.org/0000-0002-7372-0223; AAE-1726-2021
Predicting how much effort will be required to complete a software project as early as possible is a very important factor in the success of software development projects. Including function points and its variants, there are several size measures and corresponding measurement methods that can be used for effort estimation. However, in most of the projects, there is limited amount of information available in the early stages and significant effort is spent for size measurement and effort estimation with such methods. This paper analyzes the correlation between the size metrics of conceptual model of the problem domain and the resulting software. For this purpose, we consider open source project management and game software. We apply linear regression and cross validation techniques to investigate the relation between the sizes of problem domain (i.e., conceptual) and solution domain (i.e., design) models. The results reveal a high correlation between the number of conceptual classes in the problem domain model and the number of software classes constituting the corresponding software. The results suggest that it is possible to use problem domain descriptions in the early stages of software development projects to make plausible predictions for the size of the software.
Size and Effort Estimation Based on Problem Domain Measures for Object-Oriented Software
(2018) Ayyildiz, Tulin Ercelebi; Kocyigit, Altan; https://orcid.org/0000-0002-7372-0223; AAE-1726-2021
This paper analyzes the correlations between the problem domain measures such as the number of distinct nouns and distinct verbs in the requirements artifacts and the solution domain measures such as the number of software classes and methods in the corresponding object-oriented software. For this purpose, 14 completed software development projects of a CMMI Level-3 certified defense industry company have been analyzed. The observed strong correlation is taken as the indication of linear relationship between the measures and a size estimation model based on linear regression analysis is proposed. Prediction performance of the method is analyzed on the 14 software projects. Moreover, it has been observed that there is a high correlation between the problem domain measures and the development effort. Therefore, the linear regression analysis is also used to estimate the effort in terms of the problem domain measures. The effort estimations are also evaluated and compared with the efforts predicted using the size measured by the COSMIC Function Point (CFP) method. The results show that the proposed method provides more accurate effort estimates compared to the effort estimated by using CFP size measurement.
Towards a Model Based Process Assessment for Data Analytics: An Exploratory Case Study
(2020) Gokalp, Mert Onuralp; Kayabay, Kerem; Gokalp, Ebru; Kocyigit, Altan; Eren, P. Erhan; 0000-0002-4030-2447; S-5921-2016
The ability to leverage data analytics can enhance the decision-making process in organizations by generating valuable insights. However, there is a limited understanding of how organizations can adopt data analytics as part of their business processes due to a lack of comprehensive roadmap with a structural approach like a Process Capability Maturity Model (PCMM). In this study, the development of a PCMM based on the ISO/IEC 330xx standard for the data analytics domain is proposed to assist organizations in assessing their data analytics processes capability level and providing a roadmap for improving them continuously. Towards this goal, we conducted an exploratory case study for one data analytics process to evaluate the applicability and usability of the proposed approach.