Methodology of software development vs. code quality – a comparative analysis of two cases

Bartłomiej Zalewski

b.r.zalewski@gmail.com
Lublin University of Technology (Poland)

Marek Miłosz


(Poland)

Abstract

Code quality is strongly dependent on using best coding practices during it’s development. This paper presents various code quality metrics in object oriented programming and computer tools to it automatic measurement. Two cases of software development by two different teams were considered. Code quality was analyzed in five following program versions. This study shows better value of almost (but not all) code quality metrics developed using agile methodology. It raises the conclusion about agile methodology advantage.



[1] Čeponis, J., Venčkauskas, A., Čeponienė, L., Zonys, A.: Extending Rule Set for Static Code Analysis in. .NET. Platform. Information Technology And Control, 45, 2016, 99-108.
[2] Iivari J.: The relationship between organizational culture and the deployment of agile methods. Information and Software Technology, 53, 2011, 509-520.
[3] Holmström H., Alahyari H., Bosh J.: Climbing the "Stairway to Heaven" -- A Mulitiple-Case Study Exploring Barriers in the Transition from Agile Development towards Continuous Deployment of Software. Software Engineering and Advanced Applications (SEAA), 2012 38th EUROMICRO Conference on, 2012, 392-399.
[4] Vinju J.J., Godfrey M.W.: What Does Control Flow Really Look Like? Eyeballing the Cyclomatic Complexity Metric. Source Code Analysis and Manipulation (SCAM), 2012 IEEE 12th International Working Conference on, 2012, 154 - 163.
[5] Posnett D., Hindle A., Devanbu P.: A simpler model of software readability. MSR '11 Proceedings of the 8th Working Conference on Mining Software Repositories, 2011, 73-82.
[6] Yousef A.H.: Extracting software static defect models using data mining. Ain Shams Engineering Journal, 6, 2015, 133-144. [7] Elish M.O., Al.-Yafei A.H., Al.-Mulhem M,: Empirical comparison of three metrics suites for fault prediction in packages of object-oriented systems: A case study of Eclipse. Advances in Engineering Software, 42, 2011, 852-859.
[8] Bluemke I.E., Zając P., Metryki MOOD w systemie Rational Rose w: red. Huzar Z., Mazur Z., Problemy i metody inżynierii oprogramowania, Wydawnictwa Naukowo – Techniczne, Warszawa, 2003.
[9] Martin R.C., Zwinne wytwarzanie oprogramowania. Najlepsze zasady, wzorce i praktyki, Helion, 2015.
[10] Radjenović D., Heričko M., Torkar R., Živkovič A.: Software fault prediction metrics: A systematic literature review. Information and Software Technology, 55, 2013, 1397-1418.
[11] http://www.inmost.org.pl/articles/Metryki_obiektowe_jako_ws kaAniki_jakoAci_kodu_i_projektu [04.06.2016].
[12] Szyjewski Z., Muszyńska K., Zarządzanie projektami i modelowanie procesów, Polskie Towarzystwo Informatyczne, Warszawa, 2013.
[13] https://avandeursen.com/2014/08/29/think-twice-before-usingthe-maintainability-index/ [08.06.2016].
[14] https://msdn.microsoft.com/en-us/library/bb385914.aspx [08.06.2016].
[15] Arapidis C.: Sonar Code Quality Testing Essentials: Achieve Higher Levels Of Software Quality With Sonar. Birmingham, Packt Publishing, 2012.
[16] Derezińska A., Rudnik M.: Quality Evaluation of ObjectOriented and Standard Mutation Operators Applied to C# Programs. Lecture Notes in Computer Science, 7304, 2012, 42-57.
[17] Kayarvizhy N., Kanmani S.: An Automated Tool for Computing Object Oriented Metrics Using XML. Advances in Computing and Communications, 191, 2011, 69-79.
[18] Zalewski B.: Metryki oceny jakości oprogramowania i ich stosowalność. Praca magisterska pod kierunkiem Miłosza M., Politechnika Lubelska, Lublin, 2016, 71.
[19] Taibi D., Janes A., Lenarduzzi V.: Towards a Lean Approach to Reduce Code Smells Injection: An Empirical Study. Agile Processes, in Software Engineering, and Extreme Programming, 251, 2016, 300-304.

Published
2016-11-14

Cited by

Zalewski, B., & Miłosz, M. (2016). Methodology of software development vs. code quality – a comparative analysis of two cases . Journal of Computer Sciences Institute, 1(1), 54–59. https://doi.org/10.35784/jcsi.112

Authors

Bartłomiej Zalewski 
b.r.zalewski@gmail.com
Lublin University of Technology Poland

Authors

Marek Miłosz 

Poland

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