Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Subject: search.filters.subject.Size Measurement

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  • Article
    An Alternative Software Benchmarking Dataset: Effort Estimation With Machine Learning
    (Elsevier Science Inc, 2026) Yurum, Ozan Rasit; Unlu, Huseyin; Demirors, Onur
    Effort estimation plays a vital role in software project planning, as accurate estimates of required human resources are essential for success. Traditional estimation models often depend on historical size and effort data, yet organizations frequently struggle to access reliable effort records. Public benchmarking datasets like ISBSG offer useful data but may lack coverage or involve licensing fees. To address this issue, we previously introduced a free, extendable benchmarking dataset that integrates functional size and effort data extracted from 18 studies. In this study, we examine the effectiveness of our dataset for predictive effort estimation and compare it with the widely used ISBSG dataset. Our analysis includes 337 records from our dataset and 732 ISBSG projects, focusing on those with COSMIC size data. We first developed and compared models using linear regression and nine machine learning algorithms - Bayesian Ridge, Ridge Regression, Decision Tree, Random Forest, XGBoost, LightGBM, k-Nearest Neighbors, Multi-Layer Perceptron, and Support Vector Regression. Then, we selected the best-performing models and applied them to an unseen evaluation dataset to assess their generalization performance. The results show that machine learning performance varies based on evaluation method and dataset characteristics. Despite having fewer records, our dataset enabled more accurate predictions than ISBSG in most cases, highlighting its potential for effort estimation. This study demonstrates the viability of our dataset for building predictive models and supports the use of machine learning in improving estimation accuracy. Expanding this dataset could offer a valuable, open-access resource for organizations seeking effective and lowcost estimation solutions.
  • Conference Object
    Software Change Size Measurement: an Exploratory Systematic Mapping Study
    (CEUR-WS, 2024) Hacaloglu, T.; Demirörs, Onur; Küçükateş Ömüral, N.; Kılınç Soylu, G.; Demirörs, O.
    Change in software projects can occur through various channels. Customers may request modifications or new features; appraisal activities such as reviews or testing may uncover issues that necessitate adjustments, or products may need to adapt to changes in their operating environment. Therefore, it is essential to assess these changes explicitly and objectively within the scope of software engineering activities. Specifically, quantifying change by measuring its size is crucial for successful management, as without a meaningful metric, it is impossible to accurately assess its impact on the project's effort, schedule, and cost. This study aims to explore the concept of change in software engineering literature, with a particular emphasis on the methods used to measure its size. The study reveals that the current literature on this topic is still in its early stages and the measurement and estimation of changes remain challenging throughout both development and maintenance phases. According to the reviewed articles, size is primarily used for effort estimation. Various software artifacts from different stages of the Software Development Life Cycle (SDLC) serve as input for change measurement, highlighting the need for a versatile size measurement applicable across all SDLC phases. Most of the reviewed articles interpret change in the context of maintenance activities. This research sets a benchmark for the status of software size measures for software change and highlights related problems to suggest further research topics. © 2024 Copyright for this paper by its authors.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 13
    Microservice-Based Projects in Agile World: a Structured Interview
    (Elsevier, 2024) Unlu, Huseyin; Kennouche, Dhia Eddine; Soylu, Gorkem Kiling; Demirors, Onur
    Context: During the last decade, Microservice-based software architecture (MSSA) has been a preferred design paradigm for a growing number of companies. MSSA, specifically in the form of reactive systems, has substantial differences from the more conventional design paradigms, such as object-oriented analysis and design. Therefore, adaptation demands software organizations to transform their culture. However, there is a lack of research studies that explore common practices utilized by software companies that implement MSSAs.Objective: In this study, our goal is to get an insight into how practices such as an agile methodology, software analysis, design, test, size measurement, and effort estimation are performed in software projects which embrace the Microservice-based software architecture paradigm. Together with the identification of practices utilized for the MSSA paradigm, we aim to determine the challenges organizations face to adopt microservice-based software architectures.Method: We performed a structured interview with participants coming from 20 different organizations over different roles, domains, and countries to collect information on their views, experience, and the challenges faced.Results: Our results reveal that organizations find agile development compatible with microservices. In general, they continue to use traditional object-oriented modeling notations for analysis and design in an abstract way. They continue to use the same subjective size measurement and effort estimation approaches that they were using previously in traditional architectures. However, they face unique challenges in developing microservices.Conclusion: Although organizations face challenges, practitioners continue to use familiar techniques that they have been using for traditional architectures. The results provide a snapshot of the software industry that utilizes microservices.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 2
    Effort Prediction With Limited Data: a Case Study for Data Warehouse Projects
    (IEEE, 2022) Unlu, Huseyin; Yildiz, Ali; Demirors, Onur
    Organizations may create a sustainable competitive advantage against competitors by using data warehouse systems with which they can assess the current status of their operations at any moment. They can analyze trends and connections using up-to-date data. However, data warehouse projects tend to fail more often than other projects as it can be tough to estimate the effort required to build a data warehouse system. Functional size measurement is one of the methods used as an input for estimating the amount of work in a software project. In this study, we formed a measurement basis for DWH projects in an organization based on the COSMIC Functional Size Measurement Method. We mapped COSMIC rules on two different architectures used for DWH projects in the organization and measured the size of the projects. We calculated the productivity of the projects and compared them with the organization's previous projects and DWH projects in the ISBSG repository. We could not create an organization-wide effort estimation model as we had a limited number of projects. As an alternative, we evaluated the success of effort estimation using DWH projects in the ISBSG repository. We also reported the challenges we faced during the size measurement process.
  • Conference Object
    Citation - WoS: 7
    Citation - Scopus: 12
    Utilization of Three Software Size Measures for Effort Estimation in Agile World: a Case Study
    (IEEE, 2022) Unlu, Huseyin; Hacaloglu, Tuna; Buber, Fatma; Berrak, Kivilcim; Leblebici, Onur; Demirors, Onur
    Functional size measurement (FSM) methods, by being systematic and repeatable, are beneficial in the early phases of the software life cycle for core project management activities such as effort, cost, and schedule estimation. However, in agile projects, requirements are kept minimal in the early phases and are detailed over time as the project progresses. This situation makes it challenging to identify measurement components of FSM methods from requirements in the early phases, hence complicates applying FSM in agile projects. In addition, the existing FSM methods are not fully compatible with today's architectural styles, which are evolving into event-driven decentralized structures. In this study, we present the results of a case study to compare the effectiveness of different size measures: functional -COSMIC Function Points (CFP)-, event-based - Event Points-, and code length-based - Line of Code (LOC)- on projects that were developed with agile methods and utilized a microservice- based architecture. For this purpose, we measured the size of the project and created effort estimation models based on three methods. It is found that the event-based method estimated effort with better accuracy than the CFP and LOC-based methods.