Research Article
Klasik ve Sezgisel Bulanık İkili Karşılaştırma ile Yazılım Geliştirme Projelerinin Maliyet Tahmini: Uygulama Örneği
Abstract
Kaynak ve zaman
planlamanın başarılı bir şekilde yürütülebilmesi için, yazılım geliştirme
faaliyetlerinde maliyet tahminleme çok önemlidir. Maliyeti düşük tahmin edilen
projelerde; gereğinden az kaynak atanması, gerçekçi olmayan planlama vb.
sorunlar yaşanabilmekteyken tersi durumda kaynaklar israf edilmekte ve müşteri
memnuniyeti düşebilmektedir. Tahmin edilen maliyetin doğruluğu, yazılım
geliştirme projelerinin doğru bir şekilde önceliklendirilmesine, kaynakların
etkin bir şekilde kullanılmasına, değişiklik isteklerinin başarılı bir şekilde
yönetilmesine katkı sağlar. Bu nedenle, maliyetin gerçekçi bir şekilde
öngörülmesini sağlayacak uygun yöntemin seçimi, tüm proje paydaşları açısından
büyük önem arz etmektedir. Bu çalışmada, öncelikle deneyimli uzmanların
görüşünden yararlanarak yazılım geliştirme maliyet tahmini için etkin kriterler
belirlenmiş ve Klasik İkili Karşılaştırma yöntemi ile kriterlerin önem
seviyeleri elde edilmiştir. Yazılım sektöründeki yoğun rekabet ve
belirsizlikler, maliyet tahminleme için ihtiyaç duyulan tam ve kesin bilgi
akışını zorlaştırmaktadır. Özellikle önceden belirlenmiş ölçekler kullanılarak yapılan
değerlendirmelerde, kriterlerin göreceli öneminin ölçekte yer alan değerler ile
tam olarak karşılanamaması, bulanık sayılar ile karar vermenin önemini
arttırmaktadır. Bu nedenle, uzman görüşü yardımıyla belirlenen kriterlerin öneminin
tespiti için çalışmada ayrıca Sezgisel (Hesitant) Bulanık İkili Karşılaştırma
önerilmiştir. Yöntemlerin etkinliğinin anlaşılması için, Türkiye’de hizmet
vermekte olan bir yazılım şirketinin tamamlanmış projelerinin maliyeti tahmin
edilmiştir. Gerçekleşen maliyetlere kıyasla, Sezgisel Bulanık İkili
Karşılaştırma yönteminin klasik yöntemden daha başarılı sonuçlar verdiği
görülmüştür.
Keywords
yazılım maliyet tahminleme karar verme Klasik İkili Karşılaştırma Sezgisel Bulanık İkili Karşılaştırma
References
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Year 2017,
Volume: 10 Issue: 2, 129 - 137, 28.04.2017
Abstract
References
- [1] S.W. Lin, V.M. Bier, “A Study of Expert Overconfidence”, Reliability Engineering & System Safety, 93, 711-721, 2008. [2] H. Arkes, “Overconfidence in Judgmental Forecasting” in J. S. Armstrong, Principles of Forecasting, Kluwer Academic Publishers, 495-515, 2001. [3] A. Stellman, J. Greene, “Applied Software Project Management”, O’Reilly Media, 2005. [4] K, Wiegers, “Stop Promising Miracles”, Software Development, 8, 49 –53, 2000. [5] E. Miranda. “Improving Subjective Estimates Using Paired Comparisons”, Software, IEEE 87-91, 2001. [6] G.N. Parkinson. “Parkinson's Law and Other Studies in Administration”. Boston, USA: Houghton-Miffin, 1957. [7] R. Nelson. “Management Handbook for the Estimation of Computer Programming Costs”, Systems Development Corporation, 1966. [8] C.E., Walston, C.P. Felix. “A Method of Programming Measurement and Estimation. IBM Systems Journal, 16, 54-73, 1977. [9] B.W. Boehm. “Software Engineering Economics”, Englewood Cliffs, NJ, Prentice-Hall, 1981. [10] B.W. Boehm. “Software Cost Estimation with COCOMO II. New Jersey, Prentice Hall, 2000. [11] S. Bilgaiyan, S. Mishra, M. Das, “A review of software cost estimation in agile software development using soft computing techniques”, 2016 2nd International Conference on Computational Intelligence and Networks (CINE), Bhubaneswar, 2016, 112-117. [12] R. Sarno, J. Sidabutar, Sarwosri, “Comparison of different neural network architectures for software cost estimation”, 2015 International Conference on Computer, Control, Informatics and its Applications (IC3INA), Bandung, 2015, 68-73. [13] S.M.S. Jafari, F. Ziaaddini, “Optimization of software cost estimation using harmony search algorithm”, 2016 1st Conference on Swarm Intelligence and Evolutionary Computation (CSIEC), Bam, 2016, 131-135. [14] F.S. Gharehchopogh, R. Rezaii, B. Arasteh, “A new approach by using tabu search and genetic algorithms in software cost estimation”, 2015 9th International Conference on Application of Information and Communication Technologies (AICT), Rostov on Don, 2015, 113-117. [15] F.S. Gharehchopogh, I. Maleki, A. Talebi, “Using hybrid model of artificial bee colony and genetic algorithms in software cost estimation”, 2015 9th International Conference on Application of Information and Communication Technologies (AICT), Rostov on Don, 2015, 102-106. [16] T.R. Benala, S.C. Dehuri, S.C. Satapathy, C.S. Raghavi, “Genetic algorithm for optimizing neural network based software cost estimation”, International Conference on Swarm, Evolutionary, and Memetic Computing. Springer Berlin Heidelberg, 2011. [17] N. Kushwaha, Suryakant, “Software cost estimation using the improved fuzzy logic framework”, 2014 Conference on IT in Business, Industry and Government (CSIBIG), Indore, 2014, 1-5. [18] A. Mittal, K. Parkash, H. Mittal, “Software cost estimation using fuzzy logic”, ACM SIGSOFT Software Engineering Notes 35, 1-7, 2010. [19] C.L. Hwang, K, Yoon. “Multiple Attributes Decision Making Methods and Applications”, Berlin Heidelberg, Springer, 1981. [20] T.L. Saaty. “The Analytic Hierarchy Process”, McGraw – Hill Inc. 1980. [21] J.J Buckley, “Fuzzy Hierarchical Analysis”, Fuzzy Sets and Systems, 17, 233-247, 1985. [22] B. Zhu, Z. Xu, “Analytic Hierarchy Process-Hesitant Group Decision Making”, European Journal of Operational Research, 239, 794– 801, 2014. [23] B. Oztaysi, S.C. Onar, E. Boltürk, C. Kahraman, “Hesitant Fuzzy Analytic Hierarchy Process”, FUZZ-IEEE , 1-7, 2015. [24] T.L., Saaty. “How to Make a Decision: The Analytic Hierarchy Process”, European Journal of Operational Research, 48, 9–26, 1990. [25] L. A. Zadeh, “Fuzzy Sets”, Information and Control, 8(3), 338–353, 1965. [26] F.T. Bozbura, A. Beskese, C. Kahraman, “Prioritization of Human Capital Measurement Indicators Using Fuzzy AHP”, Expert Systems with Applications 32, 1100-1112, 2007. [27] V. Torra, “Hesitant Fuzzy Sets”. International Journal of Intelligent Systems, 25, 529–539, 2010. [28] H. Liu, R.M. Rodriguez, “A Fuzzy Envelope for Hesitant Fuzzy Linguistic Term Set and Its Application to Multi-Criteria Decision Making”, Information Sciences, 258, 220–238, 2014. [29] D. Filev, R.R. Yager, “On the Issue of Obtaining OWA Operator Weights”, Fuzzy Sets and Systems, 94, 157-169, 1998. [30] I. Jacobson, “Object-Oriented Software Engineering: A Use Case Driven Approach”, Addison-Wesley, 1993. [31] K.. Ribu, “Estimating Object-Oriented Software Projects with Use Cases. MSc Thesis, Oslo, Norway, 2001. [32] H.M. Sneed, “Estimation of the Development Costs of Object-Oriented Software”, Informatik Spektrum, 19, 133-140, 1996. [33] T.W. Koh, M.H. Selamat, A.A.A. Ghani, R. Abdullah, “Review of Complexity Metrics for Object-Oriented Software Products”, International Journal of Computer Science and Network Security, 8, 314-320, 2008.
There are 1 citations in total.
Details
| Subjects | Engineering |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | April 28, 2017 |
| Submission Date | April 26, 2017 |
| Published in Issue | Year 2017 Volume: 10 Issue: 2 |
