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Reseach Article

Software Development Automation: An Approach to Automate the Processes of SDLC

by A.R.V. Anthony, G.M. Dilshan Prasad, S.U. Randunuge, S.R.A.M.P.A. Alahakoon, Dinuka R. Wijendra, Jenny Krishara
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 37
Year of Publication: 2020
Authors: A.R.V. Anthony, G.M. Dilshan Prasad, S.U. Randunuge, S.R.A.M.P.A. Alahakoon, Dinuka R. Wijendra, Jenny Krishara
10.5120/ijca2020920942

A.R.V. Anthony, G.M. Dilshan Prasad, S.U. Randunuge, S.R.A.M.P.A. Alahakoon, Dinuka R. Wijendra, Jenny Krishara . Software Development Automation: An Approach to Automate the Processes of SDLC. International Journal of Computer Applications. 175, 37 ( Dec 2020), 44-51. DOI=10.5120/ijca2020920942

@article{ 10.5120/ijca2020920942,
author = { A.R.V. Anthony, G.M. Dilshan Prasad, S.U. Randunuge, S.R.A.M.P.A. Alahakoon, Dinuka R. Wijendra, Jenny Krishara },
title = { Software Development Automation: An Approach to Automate the Processes of SDLC },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 37 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 44-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number37/31694-2020920942/ },
doi = { 10.5120/ijca2020920942 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:32.811449+05:30
%A A.R.V. Anthony
%A G.M. Dilshan Prasad
%A S.U. Randunuge
%A S.R.A.M.P.A. Alahakoon
%A Dinuka R. Wijendra
%A Jenny Krishara
%T Software Development Automation: An Approach to Automate the Processes of SDLC
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 37
%P 44-51
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software development complexity is one of the most important factors that must be determined by clear procedures or methods in software production. It is determined practically by using a quantitative value, which is based into one or more qualitative attributes. These attributes focus on how the codes’ internal and external behavior. But the software complexity should be computed beyond, that level since the complexity identifies the effort of determining the internal logic behind the software. Therefore, software complexity should be expressed as a combination of the different phrases of the software development life cycle namely requirement analysis, source code implementation, maintenance, testing and quality checking as well. As a solution, the methodology of reducing the overall software complexity by creating a software development application has been considered, which will automate the requirement analysis, software logic implementation, maintenance and the testing process in the overall software development cycle without restraining the software complexity into one or more quality attributes.

References
  1. Cosine Similarity- https://www.machinelearningplus.com/nlp/cosine-similarity/
  2. PlantUML – Library to generate diagram. Retrieved June, 30, 2020 from https://plantuml.com/starting
  3. GraphViz – graph visualising software. Retrieved June 30, 2020 from http://www.graphviz.org/.
  4. Non-commenting source statements. Retrieved July, 31, 2020, from https://pmd.github.io/latest/pmd_java_metrics_index.html#non-commenting-source-statements-ncss
  5. Ryan Stansifer, Basics of the Java Language. In Notes about the Java Programming Language. Retrieved July, 27, 2020, from https://cs.fit.edu/~ryan/java/language/basics.html
  6. Recursion. In Wikipedia. Retrieved July, 27, 2020, from https://en.wikipedia.org/wiki/Recursion_(computer_science)
  7. Control Structures. In Wikipedia. Retrieved July, 27, 2020, from https://en.wikiversity.org/wiki/Control_structures
  8. McCabe (December 1976). "A Complexity Measure". IEEE Transactions on Software Engineering (4): 308–320. doi:10.1109/tse.1976.233837.
  9. Java code metrics - Cyclomatic Complexity (CYCLO). Retrieved July, 31, 2020, from https://pmd.github.io/latest/pmd_java_metrics_index.html#McCabe76
  10. G. A. Campbell, "Cognitive Complexity — An Overview and Evaluation," 2018 IEEE/ACM International Conference on Technical Debt (TechDebt), Gothenburg, 2018, pp. 57-58.K. Elissa, “Title of paper if known,” unpublished.
  11. Danny Verpoort, Insights in Cyclomatic and Cognitive Complexity in Your Application https://medium.com/takeaway-tech/insights-in-cyclomatic-and-cognitive-complexity-in-your-application-58922ae59e80
  12. Random Forest. In Wikipedia. Retrieved July, 27, 2020, from https://en.wikipedia.org/wiki/Random_forest
  13. Supervised Learning. In Wikipedia. Retrieved July, 27, 2020, from https://en.wikipedia.org/wiki/Supervised_learning
  14. Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. GloVe: Global Vectors for Word Representation.
  15. Singh, Sandeep. "Analysis of bug tracking tools." International Journal of Scientific & Engineering Research 4, no. 7 (2013): 134.
  16. Marko, Trajkov, and Smiljkovic Aleksandar. "A Survey of Bug Tracking Tools: Presentation, Analysis and Trends." aleksland. com/wp-content/uploads/2011/01/Survey. pdf (2011).
  17. Muqeem, M., & Beg, M. R. (2014, July). Validation of requirement elicitation framework using finite state machine. In 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT) (pp. 1210-1216). IEEE.
  18. More, P., & Phalnikar, R. (2012). Generating UML diagrams from natural language specifications. International Journal of Applied Information Systems, Foundation of Computer Science, 1(8), 19-23.
  19. Average time to develop a custome software. Accessed on September 01, 2019 from https://soltech.net/how-long-does-it-take-to-build-custom-software/
Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Code complexity UML generation