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Conference Object Citation - WoS: 3Citation - Scopus: 4Effort Prediction for Microservices: a Case Study(Ieee, 2021) Unlu, Huseyin; Hacaloglu, Tuna; Leblebici, Onur; Demirors, OnurSoftware size measurement is critical as an input to perform important project management processes such as effort, cost and schedule estimation. Functional size measurement (FSM) methods are beneficial in terms of being applicable in the early phases of the software life cycle over functional requirements and providing a systematic and repeatable method. However, in agile organizations, it can be challenging to seperate measurement components of FSM methods from requirements in the early phases as the documentation is kept to a minimum compared to traditional methods such as the Waterfall Model and is detailed as the project steps. In addition, the existing FSM methods are not fully compatible with today's architectural structures, which are from being data-driven and to evolve into a behaviour-oriented structure. In this study, we performed a case study which includes a project developed with agile methods and using microservice-based architecture to compare the effectiveness of COSMIC FSM and event-based software size measurement. For this purpose, we measured the size of the project and created effort estimation models based on two methods. The measurers had difficulty in applying both methods due to the limited detail level of the requirements in the project. However, the event-based method was found to estimate effort with less error than the COSMIC FSM method.Conference Object Citation - WoS: 7Citation - Scopus: 12Utilization 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, OnurFunctional 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.Article Citation - WoS: 6Citation - Scopus: 8Software Size Measurement: Bridging Research and Practice(Ieee Computer Soc, 2024) Hacaloglu, Tuna; Unlu, Huseyin; Yildiz, Ali; Demirors, OnurThis study investigates the limited adoption of functional size measurement methods in the software development industry. Using insights from firms experienced in size measurement, it aims to uncover industry expectations and facilitate the translation of theoretical methodologies into practical applications.Conference Object Citation - WoS: 3Citation - Scopus: 5Predicting Software Functional Size Using Natural Language Processing: an Exploratory Case Study(IEEE, 2024) Unlu, Huseyin; Tenekeci, Samet; Ciftci, Can; Oral, Ibrahim Baran; Atalay, Tunahan; Hacaloglu, Tuna; Demirors, OnurSoftware Size Measurement (SSM) plays an essential role in software project management as it enables the acquisition of software size, which is the primary input for development effort and schedule estimation. However, many small and medium-sized companies cannot perform objective SSM and Software Effort Estimation (SEE) due to the lack of resources and an expert workforce. This results in inadequate estimates and projects exceeding the planned time and budget. Therefore, organizations need to perform objective SSM and SEE using minimal resources without an expert workforce. In this research, we conducted an exploratory case study to predict the functional size of software project requirements using state-of-the-art large language models (LLMs). For this aim, we fine-tuned BERT and BERT_SE with a set of user stories and their respective functional size in COSMIC Function Points (CFP). We gathered the user stories included in different project requirement documents. In total size prediction, we achieved 72.8% accuracy with BERT and 74.4% accuracy with BERT_SE. In data movement-based size prediction, we achieved 87.5% average accuracy with BERT and 88.1% average accuracy with BERT_SE. Although we use relatively small datasets in model training, these results are promising and hold significant value as they demonstrate the practical utility of language models in SSM.
