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Article Citation - WoS: 11Citation - Scopus: 13Assessing Team Work in Engineering Projects(Tempus Publications, 2015) Mishra, Deepti; Ostrovska, Sofiya; Hacaloglu, Tuna; Mathematics; Computer Engineering; Information Systems EngineeringTeam work is considered a valuable teaching technique in higher education. However, the assessment of an individual's work in teams has proved to be a challenging task. Consequently, self-and peer-evaluations are becoming increasingly popular for the assessment of individuals in a team work, though it is essential to determine whether students can judge their own as well as their peer's performance effectively. Self-and peer-evaluations have been applied in different disciplines and their authenticity with regard to teacher's assessment has been evaluated in the literature but this issue has not been investigated in the field of engineering education so far. In this study, a peer-and self-assessment procedure is applied to the evaluation of a project work conducted in teams of 3 or 4 students. The participants were engineering students taking two similar courses related with database design and development. It is found that a majority of the students were unable to assess themselves as objectively as their instructor. Further, it is observed that successful students tend to under-estimate, whereas unsuccessful students tend to over-estimate, their own performance. The paper also establishes that the results of self-assessments are independent from the gender factor.Article Citation - WoS: 3Citation - Scopus: 6An Exploratory Case Study Using Events as a Software Size Measure(Springer, 2023) Hacaloglu, Tuna; Demirors, OnurSoftware Size Measurement is a critical task in Software Development Life Cycle (SDLC). It is the primary input for effort estimation models and an important measure for project control and process improvement. There exist various size measurement methods whose successes have already been proven for traditional software architectures and application domains. Being one of them, functional size measurement (FSM) attracts specific attention due to its applicability at the early phases of SDLC. Although FSM methods were successful on the data-base centric, transaction oriented stand-alone applications, in contemporary software development projects, Agile methods are highly used, and a centralized database and a relational approach are not used as before while the requirements suffer from a lack of detail. Today's software is frequently service based, highly distributed, message-driven, scalable and has unprecedented levels of availability. In the new era, event-driven architectures are appearing as one of the emerging approaches where the 'event' concept largely replaces the 'data' concept. Considering the important place of events in contemporary architectures, we focused on approaching the software size measurement problem from the event-driven perspective. This situation guided us to explore how useful event as a size measure in comparison to data-movement based methods. The findings of our study indicates that events can be promising for measurement and should be investigated further in detail to be formalized for creating a measurement model thereby providing a replicable approach.Article Citation - WoS: 16What We Know About Software Test Maturity and Test Process Improvement(Ieee Computer Soc, 2018) Garousi, Vahid; Felderer, Michael; Hacaloglu, Tuna[No Abstract Available]Conference Object Citation - WoS: 1Citation - Scopus: 3A Software Development Process Model for Cloud by Combining Traditional Approaches(Springer international Publishing Ag, 2015) Hacaloglu, Tuna; Eren, P. Erhan; Mishra, Deepti; Mishra, AlokEven though cloud computing is a technological paradigm that has been adopted more and more in various domains, there are few studies investigating the software development lifecycle in cloud computing applications and there is still not a comprehensive software development process model developed for cloud computing yet. Due to the nature of cloud computing that is completely different from the traditional software development, there is a need of suggesting process models to perform the software development systematically to create high quality software. In this study, we propose a new conceptual Software Development Life Cycle Model for Cloud Software Development that incorporates characteristics of different process models for traditional software development. The proposed model takes traditional model's specific characteristics into account and also considers cloud's specific nature i.e. advantages and challenges as well.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.Review Citation - WoS: 65Citation - Scopus: 80Software Test Maturity Assessment and Test Process Improvement: a Multivocal Literature Review(Elsevier, 2017) Garousi, Vahid; Felderer, Michael; Hacaloglu, TunaContext: Software testing practices and processes in many companies are far from being mature and are usually conducted in ad-hoc fashions. Such immature practices lead to various negative outcomes, e.g., ineffectiveness of testing practices in detecting all the defects, and cost and schedule overruns of testing activities. To conduct test maturity assessment (TMA) and test process improvement (TPI) in a systematic manner, various TMA/TPI models and approaches have been proposed. Objective: It is important to identify the state-of-the-art and the-practice in this area to consolidate the list of all various test maturity models proposed by practitioners and researchers, the drivers of TMA/TPI, the associated challenges and the benefits and results of TMA/TPI. Our article aims to benefit the readers (both practitioners and researchers) by providing the most comprehensive survey of the area, to this date, in assessing and improving the maturity of test processes. Method: To achieve the above objective, we have performed a Multivocal Literature Review (MLR) study to find out what we know about TMA/TPI. A MLR is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). We searched the academic literature using the Google Scholar and the grey literature using the regular Google search engine. Results: Our MLR and its results are based on 181 sources, 51 (29%) of which were grey literature and 130 (71%) were formally published sources. By summarizing what we know about TMA/TPI, our review identified 58 different test maturity models and a large number of sources with varying degrees of empirical evidence on this topic. We also conducted qualitative analysis (coding) to synthesize the drivers, challenges and benefits of TMA/TPI from the primary sources. Conclusion: We show that current maturity models and techniques in TMA/TPI provides reasonable advice for industry and the research community. We suggest directions for follow-up work, e.g., using the findings of this MLR in industry-academia collaborative projects and empirical evaluation of models and techniques in the area of TMA/TPI as reported in this article. (C) 2017 Elsevier B.V. All rights reserved.Article Citation - WoS: 6Citation - Scopus: 7Teaching Software Verification and Validation Course: a Case Study(Tempus Publications, 2014) Mishra, Deepti; Hacaloglu, Tuna; Mishra, Alok; Computer Engineering; Software Engineering; Information Systems EngineeringSoftware verification and validation (V & V) is one of the significant areas of software engineering for developing high quality software. It is also becoming part of the curriculum of a universities' software and computer engineering departments. This paper reports the experience of teaching undergraduate software engineering students and discusses the main problems encountered during the course, along with suggestions to overcome these problems. This study covers all the different topics generally covered in the software verification and validation course, including static verification and validation. It is found that prior knowledge about software quality concepts and good programming skills can help students to achieve success in this course. Further, team work can be chosen as a strategy, since it facilitates students' understanding and motivates them to study. It is observed that students were more successful in white box testing than in black box testing.Article Citation - WoS: 2Citation - Scopus: 4Online Collaborative Tool Usage for Review Meetings in Software Engineering Courses(Routledge Journals, Taylor & Francis Ltd, 2022) Turhan, Cigdem; Akman, Ibrahim; Hacaloglu, TunaThe instructors generally utilize conventional methods in teaching software engineering courses, where the students are provided theoretical knowledge based on text books or lecture notes. Usage of collaborative tools may be a solution to the problems of not practicing the depth of the components of the subject. This study proposes the usage of a collaborative tool, namely, Google Docs in a software engineering course based on predefined scenarios. The review meeting subject was selected for this purpose and students' reactions were assessed with a survey after the completion of the experiments. The survey data were analysed using least square regression method. The results have shown that efficiency, certainty, satisfaction, advantage, complexity, learnability, and intention are indicators of the adoption of the online collaborative tool.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.
