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Çok Boyutlu Yazılım Geliştirme Verimlilik Değerlendirme Modeli Önerisi ve Uzaktan Çalışma Ortamlarında Kullanım Örnekleri

Yıl 2025, Cilt: 18 Sayı: 2, 163 - 173, 22.12.2025
https://doi.org/10.54525/bbmd.1719996

Öz

Geleneksel yazılım geliştirme projelerinde verimlilik, yalnızca girdi-çıktı oranı üzerinden değerlendirilen, çoğu zaman tek boyutlu bir yaklaşımla ele alınmaktadır. Bu bakış açısı, kod kalitesi, bakım yükü ve müşteri memnuniyeti gibi kritik unsurları göz ardı ederek, verimliliğin çok boyutlu doğasını tam olarak yansıtamamaktadır. Bu çalışmada, yazılım geliştirme süreçlerindeki verimliliği somut verilerle ölçülebilir hale getirmeyi amaçlayan, dokuz temel boyuttan oluşan kapsamlı bir model önerilmiştir.
Modelin uygulanabilirliğini ve geçerliliğini test etmek amacıyla, üç farklı kurumda üçer yıllık döngüleri kapsayan bir örnek olay çalışması gerçekleştirilmiştir. Elde edilen bulgular, önerilen modelin gerçek hayattaki yazılım geliştirme süreçleriyle uyumlu olduğunu ve kurumlardaki gözlemlerle tutarlı sonuçlar üretebildiğini göstermektedir. Bu yönüyle, önerilen model, literatürdeki tek boyutlu verimlilik yaklaşımlarından önemli ölçüde ayrışmaktadır.
Verimlilik sonuçlarının, kurum kültürü, takım yapısı, kullanılan teknolojiler ve teknik borç gibi bağlamsal faktörlerden etkilendiği görülmüştür. Bu nedenle, modelin sağladığı değerlerin her kuruma özgü olduğu ve doğrudan kurumlar arası karşılaştırma yerine, kurumlardaki zaman içindeki değişimin incelenmesinin daha anlamlı sonuçlar vereceği vurgulanmıştır. Önerilen model, yapay zekanın yazılım geliştirmeye entegrasyonu ve farklı iş modellerinin verimliliğe olan etkileri gibi güncel konuların incelenmesi için bir temel sunmaktadır. Bu çalışma, gelecekteki araştırmalar için verimlilik analizlerinde bir zemin hazırlamakta ve yazılım verimliliği alanında çok boyutlu ve bağlama duyarlı yaklaşımların önemini ortaya koymaktadır.

Kaynakça

  • W. Fan, P. Moen, “Working more, less or the same during COVID-19? A mixed method, intersectional analysis of remote workers”, Work and Occupations, Vol. 49, No. 2, (pp. 143-186), 2022
  • W. A. Chapetta, G. H. Travassos, "Towards an evidence-based theoretical framework on factors influencing the software development productivity", Empirical Software Engineering, 25, 3501–3543, 2020.
  • A. Trigo, J. Varajão, M. Almeida, "Low-Code Versus Code-Based Software Development: Which Wins the Productivity Game?," IT Professional, 24(5), 61-68, 2022.
  • S. A. Butt, S. Misra, G. Piñeres-Espitia, P. Ariza-Colpas, M. M. Sharma, "A Cost Estimating Method for Agile Software Development," in Computational Science and Its Applications – ICCSA 2021, 12955, 2021.
  • M. Z. Ahmad, N. Ahmad, "Parametric Software Reliability Growth Model with Testing Effort: A Review," 2021 International Conference on Computational Performance Evaluation (ComPE), 899-904, 2021.
  • Z. Liao, Y. Zhao, S. Liu, Y. Zhang, L. Liu, J. Long, "The Measurement of the Software Ecosystem’s Productivity with GitHub," Computer Systems Science and Engineering, 36(1), 239-258, 2021.
  • Z. Liao, X. Qi, Y. Zhang, X. Fan, Y. Zhou, "How to Evaluate the Productivity of Software Ecosystem: A Case Study in GitHub," 2020.
  • J. S. Mota, H. A. Tives, E. D. Canedo, "Tool for Measuring Productivity in Software Development Teams", Information, 12(10), 396, 2021.
  • A. Hussain, M. Raja, P. Vellaisamy, S. Krishnan, L. Rajendran, "Enhanced framework for ensemble effort estimation by using recursive-based classification," IET Software, 2021.
  • A. A. M. Alsunki, M. A. M. Ali, A. A. Jaharadak, N. Md Tahir, "Framework of Software Developers Engagement Antecedents and Productivity - A Review," 2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA), 302-307, 2020.
  • J. B. Michael, "Placing Trust in Automated Software Development Processes," Computer, 55(7), 78-81, 2022.
  • P. Jalote, D. Kamma, "Studying Task Processes for Improving Programmer Productivity," IEEE Transactions on Software Engineering, 47(4), 801-817, 2021.
  • A. A. M. Nordin, R. Latih, N. M. Ali, "Software Development Productivity Model: Validation through Expert Review," 2021 International Conference on Electrical Engineering and Informatics (ICEEI), 1-6, 2021.
  • V. L. Martino, C. Gravino, "Using COSMIC to measure functional size of software: a Systematic Literature Review," 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 225-228, 2022.
  • U. A. Alrubaee, D. Cetinkaya, G. Liebchen, H. Dogan, "A process model for component-based model-driven software development," Information, 11(6), 302, 2020.
  • L. Castillo-Salinas, S. Sanchez-Gordon, J. Villarroel-Ramos, M. Sánchez-Gordón, "Evaluation of the implementation of a subset of ISO/IEC 29110 Software Implementation process in four teams of undergraduate students of Ecuador. An empirical software engineering experiment," Computer Standards & Interfaces, 70, 103430, 2020.
  • Khan, S. U., Khan, A. W., Khan, F., Khan, J., & Lee, Y. (2023). Factors influencing vendor organizations in the selection of DevOps for global software development: an exploratory study using a systematic literature review. Cognition, Technology & Work, 25(4), 411-426.
  • Ebert, C., Arockiasamy, J. P., Hettich, L., & Weyrich, M. (2024). Hints for generative AI software development. IEEE Software, 41(5), 24-33.
  • Z. Ying, D. Towey, Y. Zhang, "Evaluation of the Code Generated By Large Language Models: The State of the Art," 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), 440-449, 2025.
  • I. Hardill, A. Green, “Remote working—altering the spatial contours of work and home in the new economy”, New Technology Work and Employment, 18(3), 212-222, 2003.
  • D. Hislop, C. Axtell, K. Daniels, “The challenge of remote working”, 2008.
  • H. Sharp, L. Barroca, A. Deshpande, P. Gregory, K. Taylor, “Remote working in an Agile team”, Agile Research Network, 1-15, 2016.
  • A. H. Zulfany, R. S. Dewi, S. G. Partiwi, “Analyzing mental workload of remote worker by using SWAT methodology (case study: Remote software engineer)”, IOP Conference Series: Materials Science and Engineering, Cilt 598, Sayı 1, Ağustos 2019.
  • G. Sudhakar, A. Farooq, S. Patnaik, “Measuring productivity of software development teams”, Serbian Journal of Management, 7(1), 65-75, 2012.
  • S. Delaney, D. Schmidt, “A productivity framework for software development literature review”, Proceedings of the 2nd International Conference on Software Engineering and Information Management, (pp. 69-74), Ocak 2019.
  • J. Iqbal, M. Omar, A. Yasin, “An empirical analysis of the effect of agile teams on software productivity”, 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), (pp. 1-8), Ocak 2019.
  • A. A. M. Nordin, R. Latih, N. M. Ali, “Software Development Productivity Model: Validation through Expert Review”, 2021 International Conference on Electrical Engineering and Informatics (ICEEI), (pp. 1-6), Ekim 2021.
  • A. Rot, M. Sobinska, P. Busch, “Programming Teams in Remote Working Environments: an Analysis of Performance and Productivity”, 2023 13th International Conference on Advanced Computer Information Technologies (ACIT), (pp. 376-381), Eylül 2023.
  • D. Smite, N. B. Moe, E. Klotins, J. Gonzalez-Huerta, “From forced Working-From-Home to voluntary working-from-anywhere: Two revolutions in telework”, Journal of Systems and Software, 195, 111509, 2023.
  • J. K. Nwankpa, Y. F. Roumani, “Remote work, employee productivity and innovation: the moderating roles of knowledge sharing and digital business intensity”, Journal of Knowledge Management, 28(6), 1793-1818, 2024.
  • A. Nguyen‐Duc, D. Khanna, G. H. Le, D. Greer, X. Wang, L. M. Zaina, P. Abrahamsson, “Work‐from‐home impacts on software project: A global study on software development practices and stakeholder perceptions”, Software: Practice and Experience, 54(5), 896-926, 2024.
  • S. Somanathan, “Optimizing Agile Project Management for Virtual Teams: Strategies for Collaboration, Communication, and Productivity in Remote Settings”, International Journal of Applied Engineering & Technology, 5, 2023.
  • F. Jansen, R. De Souza Santos, “Remote Communication Trends Among Developers and Testers in Post-Pandemic Work Environments”, 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME), Flagstaff, AZ, A.B.D., (pp. 672-677), 2024, doi: 10.1109/ICSME58944.2024.00071.
  • S. L. Pfleeger, F. Wu, R. Lewis, Software cost estimation and sizing methods: issues, and guidelines, Cilt 269, Rand Corporation, 2005.
  • Common Software Measurement International Consortium (COSMIC), “COSMIC Software Sizing - open standard for software size measurement”, https://cosmic-sizing.org/, 2025.
  • D. Bogdanović, S. Sladojević, M. Arsenović, A. Anderla, “Multi-Criteria Analysis of Characteristics of Remote Employee Monitoring Systems”, 21st International Symposium INFOTEH-JAHORINA (INFOTEH), (pp. 1-6), 2022.
  • B. Wilkes, A. M. P. Milani, M. A. Storey, “A framework for automating the measurement of devops research and assessment (DORA) metrics”, 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME), (pp. 62-72), Ekim 2023.
  • H. Altunel, B. Say, “Software product system model: a customer-value oriented, adaptable, devops-based product model”, SN Computer Science, 3(1), 38, 2022.
  • OWASP Foundation, “OWASP Top Ten”, https://owasp.org/www-project-top-ten/, 2025.
  • N. Dayyala, K. A. Walstrom, K. K. Bagchi, G. Udo, “Factors impacting defect density in software development projects”, International Journal of Information Technologies and Systems Approach (IJITSA), 15(1), 1-23, 2022.
  • S. A. Butt, A. C. Melisa, S. Misra, “Software product maintenance: A case study”, International Conference on Computer Information Systems and Industrial Management, (pp. 81-92), Cham: Springer International Publishing, Temmuz 2022.
  • P. Giro Manzano, Customer Satisfaction Measurement: strategies, methodologies and factors influencing customer satisfaction measures, 2021.
  • K. Cleaver, Teamwork Quality and Success in Remote, Hybrid, and Proximal Agile Software Development (ASD) Teams, Doktora Tezi, The Chicago School of Professional Psychology, 2024.
  • G. Hernández, Á. Martínez, R. Jiménez, F. Jiménez, “Productivity metrics for an agile software development team: A systematic review”, TecnoLógicas, 22(SPE), 63-81, 2019.
  • H. Altunel, “Product life cycle based project management model”, The Journal of Modern Project Management, Vol. 4, No. 3, 2017.

Multi-Dimensional Software Development Efficiency Assessment Model Proposal and Its Evaluation in Remote Work Environments

Yıl 2025, Cilt: 18 Sayı: 2, 163 - 173, 22.12.2025
https://doi.org/10.54525/bbmd.1719996

Öz

In traditional software development, efficiency is often evaluated through a one-dimensional approach that focuses solely on the input-output ratio. This perspective overlooks critical factors such as code quality, maintenance burden, and customer satisfaction, failing to capture the multidimensional nature of efficiency. This study proposes a comprehensive, nine-dimensional model designed to make software development efficiency and productivity measurable using concrete data.
To test the model's applicability and validity, a case study was conducted across three different organizations, covering three-year periods within each. The findings demonstrate that the proposed model is consistent with real-world software development processes and produces results that align with observations within these organizations. In this regard, the model significantly departs from the one-dimensional efficiency approaches prevalent in existing literature.
The results indicate that efficiency is influenced by contextual factors such as company culture, team structure, technologies used, and technical debt. Therefore, it is emphasized that the values provided by the model are specific to each organization. Instead of direct comparison, analyzing changes over time within a single organization yields more meaningful results. The proposed model provides a foundation for examining current topics, such as the integration of artificial intelligence into software development and the impact of different business models on efficiency. This work establishes a basis for future research and highlights the importance of adopting a multidimensional, context-aware approach to software efficiency.

Kaynakça

  • W. Fan, P. Moen, “Working more, less or the same during COVID-19? A mixed method, intersectional analysis of remote workers”, Work and Occupations, Vol. 49, No. 2, (pp. 143-186), 2022
  • W. A. Chapetta, G. H. Travassos, "Towards an evidence-based theoretical framework on factors influencing the software development productivity", Empirical Software Engineering, 25, 3501–3543, 2020.
  • A. Trigo, J. Varajão, M. Almeida, "Low-Code Versus Code-Based Software Development: Which Wins the Productivity Game?," IT Professional, 24(5), 61-68, 2022.
  • S. A. Butt, S. Misra, G. Piñeres-Espitia, P. Ariza-Colpas, M. M. Sharma, "A Cost Estimating Method for Agile Software Development," in Computational Science and Its Applications – ICCSA 2021, 12955, 2021.
  • M. Z. Ahmad, N. Ahmad, "Parametric Software Reliability Growth Model with Testing Effort: A Review," 2021 International Conference on Computational Performance Evaluation (ComPE), 899-904, 2021.
  • Z. Liao, Y. Zhao, S. Liu, Y. Zhang, L. Liu, J. Long, "The Measurement of the Software Ecosystem’s Productivity with GitHub," Computer Systems Science and Engineering, 36(1), 239-258, 2021.
  • Z. Liao, X. Qi, Y. Zhang, X. Fan, Y. Zhou, "How to Evaluate the Productivity of Software Ecosystem: A Case Study in GitHub," 2020.
  • J. S. Mota, H. A. Tives, E. D. Canedo, "Tool for Measuring Productivity in Software Development Teams", Information, 12(10), 396, 2021.
  • A. Hussain, M. Raja, P. Vellaisamy, S. Krishnan, L. Rajendran, "Enhanced framework for ensemble effort estimation by using recursive-based classification," IET Software, 2021.
  • A. A. M. Alsunki, M. A. M. Ali, A. A. Jaharadak, N. Md Tahir, "Framework of Software Developers Engagement Antecedents and Productivity - A Review," 2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA), 302-307, 2020.
  • J. B. Michael, "Placing Trust in Automated Software Development Processes," Computer, 55(7), 78-81, 2022.
  • P. Jalote, D. Kamma, "Studying Task Processes for Improving Programmer Productivity," IEEE Transactions on Software Engineering, 47(4), 801-817, 2021.
  • A. A. M. Nordin, R. Latih, N. M. Ali, "Software Development Productivity Model: Validation through Expert Review," 2021 International Conference on Electrical Engineering and Informatics (ICEEI), 1-6, 2021.
  • V. L. Martino, C. Gravino, "Using COSMIC to measure functional size of software: a Systematic Literature Review," 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 225-228, 2022.
  • U. A. Alrubaee, D. Cetinkaya, G. Liebchen, H. Dogan, "A process model for component-based model-driven software development," Information, 11(6), 302, 2020.
  • L. Castillo-Salinas, S. Sanchez-Gordon, J. Villarroel-Ramos, M. Sánchez-Gordón, "Evaluation of the implementation of a subset of ISO/IEC 29110 Software Implementation process in four teams of undergraduate students of Ecuador. An empirical software engineering experiment," Computer Standards & Interfaces, 70, 103430, 2020.
  • Khan, S. U., Khan, A. W., Khan, F., Khan, J., & Lee, Y. (2023). Factors influencing vendor organizations in the selection of DevOps for global software development: an exploratory study using a systematic literature review. Cognition, Technology & Work, 25(4), 411-426.
  • Ebert, C., Arockiasamy, J. P., Hettich, L., & Weyrich, M. (2024). Hints for generative AI software development. IEEE Software, 41(5), 24-33.
  • Z. Ying, D. Towey, Y. Zhang, "Evaluation of the Code Generated By Large Language Models: The State of the Art," 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC), 440-449, 2025.
  • I. Hardill, A. Green, “Remote working—altering the spatial contours of work and home in the new economy”, New Technology Work and Employment, 18(3), 212-222, 2003.
  • D. Hislop, C. Axtell, K. Daniels, “The challenge of remote working”, 2008.
  • H. Sharp, L. Barroca, A. Deshpande, P. Gregory, K. Taylor, “Remote working in an Agile team”, Agile Research Network, 1-15, 2016.
  • A. H. Zulfany, R. S. Dewi, S. G. Partiwi, “Analyzing mental workload of remote worker by using SWAT methodology (case study: Remote software engineer)”, IOP Conference Series: Materials Science and Engineering, Cilt 598, Sayı 1, Ağustos 2019.
  • G. Sudhakar, A. Farooq, S. Patnaik, “Measuring productivity of software development teams”, Serbian Journal of Management, 7(1), 65-75, 2012.
  • S. Delaney, D. Schmidt, “A productivity framework for software development literature review”, Proceedings of the 2nd International Conference on Software Engineering and Information Management, (pp. 69-74), Ocak 2019.
  • J. Iqbal, M. Omar, A. Yasin, “An empirical analysis of the effect of agile teams on software productivity”, 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), (pp. 1-8), Ocak 2019.
  • A. A. M. Nordin, R. Latih, N. M. Ali, “Software Development Productivity Model: Validation through Expert Review”, 2021 International Conference on Electrical Engineering and Informatics (ICEEI), (pp. 1-6), Ekim 2021.
  • A. Rot, M. Sobinska, P. Busch, “Programming Teams in Remote Working Environments: an Analysis of Performance and Productivity”, 2023 13th International Conference on Advanced Computer Information Technologies (ACIT), (pp. 376-381), Eylül 2023.
  • D. Smite, N. B. Moe, E. Klotins, J. Gonzalez-Huerta, “From forced Working-From-Home to voluntary working-from-anywhere: Two revolutions in telework”, Journal of Systems and Software, 195, 111509, 2023.
  • J. K. Nwankpa, Y. F. Roumani, “Remote work, employee productivity and innovation: the moderating roles of knowledge sharing and digital business intensity”, Journal of Knowledge Management, 28(6), 1793-1818, 2024.
  • A. Nguyen‐Duc, D. Khanna, G. H. Le, D. Greer, X. Wang, L. M. Zaina, P. Abrahamsson, “Work‐from‐home impacts on software project: A global study on software development practices and stakeholder perceptions”, Software: Practice and Experience, 54(5), 896-926, 2024.
  • S. Somanathan, “Optimizing Agile Project Management for Virtual Teams: Strategies for Collaboration, Communication, and Productivity in Remote Settings”, International Journal of Applied Engineering & Technology, 5, 2023.
  • F. Jansen, R. De Souza Santos, “Remote Communication Trends Among Developers and Testers in Post-Pandemic Work Environments”, 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME), Flagstaff, AZ, A.B.D., (pp. 672-677), 2024, doi: 10.1109/ICSME58944.2024.00071.
  • S. L. Pfleeger, F. Wu, R. Lewis, Software cost estimation and sizing methods: issues, and guidelines, Cilt 269, Rand Corporation, 2005.
  • Common Software Measurement International Consortium (COSMIC), “COSMIC Software Sizing - open standard for software size measurement”, https://cosmic-sizing.org/, 2025.
  • D. Bogdanović, S. Sladojević, M. Arsenović, A. Anderla, “Multi-Criteria Analysis of Characteristics of Remote Employee Monitoring Systems”, 21st International Symposium INFOTEH-JAHORINA (INFOTEH), (pp. 1-6), 2022.
  • B. Wilkes, A. M. P. Milani, M. A. Storey, “A framework for automating the measurement of devops research and assessment (DORA) metrics”, 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME), (pp. 62-72), Ekim 2023.
  • H. Altunel, B. Say, “Software product system model: a customer-value oriented, adaptable, devops-based product model”, SN Computer Science, 3(1), 38, 2022.
  • OWASP Foundation, “OWASP Top Ten”, https://owasp.org/www-project-top-ten/, 2025.
  • N. Dayyala, K. A. Walstrom, K. K. Bagchi, G. Udo, “Factors impacting defect density in software development projects”, International Journal of Information Technologies and Systems Approach (IJITSA), 15(1), 1-23, 2022.
  • S. A. Butt, A. C. Melisa, S. Misra, “Software product maintenance: A case study”, International Conference on Computer Information Systems and Industrial Management, (pp. 81-92), Cham: Springer International Publishing, Temmuz 2022.
  • P. Giro Manzano, Customer Satisfaction Measurement: strategies, methodologies and factors influencing customer satisfaction measures, 2021.
  • K. Cleaver, Teamwork Quality and Success in Remote, Hybrid, and Proximal Agile Software Development (ASD) Teams, Doktora Tezi, The Chicago School of Professional Psychology, 2024.
  • G. Hernández, Á. Martínez, R. Jiménez, F. Jiménez, “Productivity metrics for an agile software development team: A systematic review”, TecnoLógicas, 22(SPE), 63-81, 2019.
  • H. Altunel, “Product life cycle based project management model”, The Journal of Modern Project Management, Vol. 4, No. 3, 2017.
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Yönetim Bilişim Sistemleri
Bölüm Araştırma Makalesi
Yazarlar

Haluk Altunel 0000-0003-1103-3644

Gönderilme Tarihi 15 Haziran 2025
Kabul Tarihi 30 Ekim 2025
Erken Görünüm Tarihi 16 Aralık 2025
Yayımlanma Tarihi 22 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 18 Sayı: 2

Kaynak Göster

IEEE H. Altunel, “Çok Boyutlu Yazılım Geliştirme Verimlilik Değerlendirme Modeli Önerisi ve Uzaktan Çalışma Ortamlarında Kullanım Örnekleri”, bbmd, c. 18, sy. 2, ss. 163–173, 2025, doi: 10.54525/bbmd.1719996.