Mechanism For Detection of Software Design Defects

International Journal of Computer Science and Engineering
© 2020 by SSRG - IJCSE Journal
Volume 7 Issue 3
Year of Publication : 2020
Authors : Kalalali Roseline Asimini-Hart, Bennet Okoni, Nuka Nwiabu
: 10.14445/23488387/IJCSE-V7I3P102

pdf
Citation:
MLA Style:

Kalalali Roseline Asimini-Hart, Bennet Okoni, Nuka Nwiabu, "Mechanism For Detection of Software Design Defects" SSRG International Journal of Computer Science and Engineering 7.3 (2020): 12-21.

APA Style:

Kalalali Roseline Asimini-Hart, Bennet Okoni, Nuka Nwiabu,(2020). Mechanism For Detection of Software Design Defects. SSRG International Journal of Computer Science and Engineering 7(3), 12-21.

Abstract:

This dissertation provides a mechanism for the detection of software design defect. There are stages of design defect which includes planning, analysis, design, implementation and testing in which this dissertation focuses on the design process alone. There are basic principles of software design which are ambiguity, inferiority, inconsistency and incorrectness. This dissertation is picking inconsistency and incorrectness as the two variables to work with to test5 for software defect. The design methodology is an object-oriented design which also has five stages to actualize the aim of this dissertation. The first stage of the OOD is been used which is to define the context and external interaction with the system thereby produces an SRS (Software requirement Specification) Document with the developer. After developing the software, the tester tests the software using the two chosen variables to test against the SRS Document to ascertain whether the software developed is in conformity with the laid down document. In the testing process, expert system is used. machine learning under the supervised learning where the system is trained with an algorithm and the SRS data stored into the database.

References:

[1] Dresch, Aline, Lacerda, Daniel Pacheco; Jr. Ose Antonio Valle Antunes (2015). “Design Science Research: A Method for Science and Technology Advancement Cham”. Springer, pp. I doi:10, 1007/978-3-319-07374-3.
[2] Hoshggoftaar, T., & Allen, E. (1998). “Predicting the order of fault-prone Modules in legacy software”.
[3] Kemerer, C. F. & Mark, C. (2009). The impact of design and code reviews on software Quality: “An Empirical study based on PSP Data” IEEE Transactions on Software Engineering. Vol. 35 No. 4.
[4] Liu, Khoshgoftaar, &Seliya (2010). “International Conference or Machine Learning and Applications”.
[5] Zhang Yanjun, “Design and Development of Chinese Teaching Software based on Chinese Audio-visual Multimedia Corpus”, SRG International Journal of Electrical and Electronics Engineering Volume 5 Issue 10 Oct 2018
[6] Mende, T., &Koschri, R. (2009). “Revisiting the evaluation of defect prediction models? Process International Conference on Predictor models in software engineering”.
[7] Ohlsson, N., &Alberg, H. (1996). “Predicting fault probe software module in telephone switches” IEEE Trans Software Engineering, 22(12), 886-894.
[8] OMG (2010). “Unified Modelling Languages, superstructure specification, version 2.1.1, http://www.omg.org/spec/UML/2.1.1/superstructure /PDF/.
[9] Orthogonal defect classification, “A concept for In-Process Measurements, IEEE Transactions on Software Engineering”, SE 18. P. 943 – 956.
[10] Wise, A. (2006). Litter-JIL. “1.5 Language Report on Technical Report”, Department of Computer science, University of Massachusetts.
[11] Zheng, J., Williams, L., Nagappan, N., Snipes, W. Hudepohl, J. P. &Vonk, M. A. 2006). “On the value of static Analysis for fault Detection on Software”. IEEE. Transactions on Software Engineering, 32, (4).

Key Words:

software, design, OOD, software efficiency, software inconsistency,