The purpose of this paper is to propose a set of test metrics required to quantify the quality of the software. A detailed research was done to analyse the testing process including functional, performance, security and usability testing around latest technologies covering cloud computing, big data, machine learning, artificial intelligence and internet of things. Effort, schedule, productivity, defects, quality and cost are fundamental parameters of any project. There are several metrics around these parameters covering all phases of project including project initiation, planning, executing, monitoring and controlling and closing. There was a time when weekly, monthly, quarterly or yearly metrics reports were published based on collected data. Confirming authenticity of that collected data was also a challenge. In current scenario looking at the adaption of continuous software engineering we proposed a new term called Automated Continuous Quality (ACQ) Metrics Dashboard which will act as product stability index or project health indicator. This could be used by organizations to track and generate all the required reports at real time. Any individual could select any of the project parameters for any period of time to generate a report. It would use continuous data collected by continuous monitoring of the tools.

Metrics, Continuous Testing, Continuous Delivery, Continuous Integration, 4S Metrics, ACT (Automated Continuous Testing), T Model

[1]. Aman Kumar Sharma, Dr. Arvind Kalia, Dr. Hardeep , “An Analysis of Optimum Software Quality Factors”, IOSR Journal of Engineering, 2(4) ,2012 , 663-669.
[2]. C.Mallikarjuna, K. Sudheer Babu, P. Chitti Babu, “A Report on the Analysis of Software Maintenance and Impact on Quality Factors”, International Journal of Engineering Sciences Research-IJESR , Vol 05, Article 01335, 2014.
[3]. Tahir, MacDonell, S.G., “A Systematic mapping study on dynamic software quality metrics”, Proc. 28th IEEE International Conference on Software Maintenance ,Riva del Garda, Italy, 2012, 326-335.
[4]. K.P. Srinivasan, Dr. T.Devi, “A Complete and Comprehensive Metrics Suite for Object-Oriented Design Quality Assessment”, International Journal of Software Engineering and Its Applications 8(2), 2014, 173-188.
[5]. G Bavota, A De Lucia, A Marcus, R Oliveto, “Using structural and semantic measures to improve software modularization”, Emprical Software Engineering, 18(5),2013, 901-932.
[6]. Alan Gillies , Software Quality: Theory and Management , 3rd edition, Lulu.
[7]. C.Mallikarjuna, K. Sudheer Babu, P. Chitti Babu, “A Report on the Analysis of Software Maintenance and Impact on Quality Factors”, International Journal of Engineering Sciences Research-IJESR , Vol 05, Article 01335, 2014
[8]. B. Kitchenham and S. Charters, Guidelines for performing Systematic Literature Reviews in Software Engineering. 2007.
[9]. Y. Levy and T. J. Ellis, “A systems approach to conduct an effective literature review in support of information systems research,” Informing Sci. Int. J. Emerg. Transdiscipl., vol. 9, no. 1, pp. 181–212, 2006.
[10]. C. Wohlin, Experimentation in software engineering : an introduction. Boston: Kluwer, 2000.
[11]. M. J. Ordonez and H. M. Haddad, “The State of Metrics in Software Industry,” in a Fifth International Conference on Information Technology: New Generations, 2008. ITNG 2008, 2008, pp. 453–458.
[12]. S. Misra and M. Omorodion, “Survey on Agile Metrics and Their Inter-relationship with Other Traditional Development Metrics,” SIGSOFT Softw Eng Notes, vol. 36, no. 6, pp. 1–3, Nov. 2011.
[13]. D. Hartmann and R. Dymond, “Appropriate agile measurement: using metrics and diagnostics to deliver business value,” in Agile Conference, 2006, 2006, p. 6 pp.– 134.
[14]. I. Hydara, N. Admodisastro, Information and Software Testing, Elsevier, Current state of research on cross-site scripting (XSS) – A systematic literature review, Volume 58, Feb 2015, Pages 170-186.
[15]. S.Subashini, Journal of Network and Computer Applications, Elsevier, A survey on security issues in service delivery models of cloud computing, Volume 34, Issue 1, January 2o11, Pages 1-11.
[16]. Dheeraj, International Journal of Electrical and Computer Engineering (IJECE)- Proposed t-model to cover 4S quality metrics based on empirical study of root cause of software failures, Vol 9, No-2, April 2019