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Software Engineering Analytics—The Need of Post COVID-19 Business: An Academic Review

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Computational Management

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 18))

Abstract

“Man Proposes, God Disposes”. COVID-19; the unexpected pandemic decease is a good testimony of the above proverb by exemplifying global business operations shutting down. Pre COVID-19, the business across the globe more or less are planned one; running smoothly; trying to reach their goals and objectives; satisfying the customers, finally leading to leapfrog the companies’ profits. This was the scenario, before the coronavirus; the alias of COVID-19 pandemic, which was germinated in one of the most scientific cities in china; Wuhan. Entire world business collapsed; another global economic recession after 2008; touching all the continents, countries, business, tribes, religions, lifestyles, as well as professional lives. No medicine was unable to save the lakhs of human life from contamination. Even different country leaders practised various preventive methods in order to cure the decease to save human life. In this light, this book chapter will explore the state of the art of COVID-19 across the globe with respect to business. The entire data analysis is based on secondary on-line data and thematically narrated. The book chapter furtherly discussed in detail connotes, process and state of art of software engineering and software analytics in business for sustainability. The analysis reveals that software analytics technology is the only industry lightly affected, should grow rapidly and it is the only solution provider to improve the process, and sustain business via better-automated software. In long term incurs less cost, time management, less manual intervention, integration of enterprise departments, virtual meetings, and e-commerce are the beauty of software analytics.

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References

  1. Chan JFW, Yuan S, Kok KH, To KKW, Chu H, Yang J, et al (2020) 333 RWS Poon, HW Tsoi, SKF Lo, KH Chan, VKM Poon, WM Chan, JD Ip, JP Cai, 334 VCC Cheng, H. Chen, CKM Hui, KY Yuen, A familial cluster of pneumonia associated 335 with the 2019 novel coronavirus indicating person-to-person transmission: a study of a 336 family cluster. Lancet 395:514–523

    Google Scholar 

  2. Bakkalbasi N, Bauer K, Glover J, Wang L (2006) Three options for citation tracking: Google Scholar, Scopus and Web of Science. Biomed Digit Libr 3(1):7

    Article  Google Scholar 

  3. Fabbrini F, Fusani M, Gnesi S, Lami G (2000) Quality evaluation of software requirement specifications. In: Proceedings of the software and internet quality week 2000 conference, pp 1–18

    Google Scholar 

  4. Salger F, Engels G, Hofmann A (2009) Inspection effectiveness for different quality attributes of software requirement specifications: an industrial case study. In: 2009 ICSE workshop on software quality. IEEE, pp 15–21

    Google Scholar 

  5. Pekar V, Felderer M, Breu R (2014) Improvement methods for software requirement specifications: a mapping study. In: 2014 9th international conference on the quality of information and communications technology. IEEE, pp 242–245

    Google Scholar 

  6. Singh Y, Sabharwal S, Sood M (2004) A systematic approach to measure the problem complexity of software requirement specifications of an information system. Int J Inf Manage Sci 15(1):69–90

    MATH  Google Scholar 

  7. Hassine J, Dssouli R, Rilling J (2004) Applying reduction techniques to software functional requirement specifications. In: International workshop on system analysis and modeling. Springer, Berlin, Heidelberg, pp 138–153

    Google Scholar 

  8. Sullivan KJ, Griswold WG, Cai Y, Hallen B (2001) The structure and value of modularity in software design. ACM SIGSOFT Softw Eng Notes 26(5):99–108

    Google Scholar 

  9. Shaw M, Garlan D (1996) Software architecture, vol 101. Prentice Hall, Englewood Cliffs

    MATH  Google Scholar 

  10. Heer J, Agrawala M (2006) Software design patterns for information visualization. IEEE Trans Visual Comput Gr 12(5):853–860

    Article  Google Scholar 

  11. Détienne F (2001) Software design–cognitive aspect. Springer Science & Business Media

    Google Scholar 

  12. Terwilliger RB, Campbell RH (1989) Please: executable specifications for incremental software development. J Syst Softw 10(2):97–112

    Article  Google Scholar 

  13. Rising L, Janoff NS (2000) The Scrum software development process for small teams. IEEE Softw 17(4):26–32

    Article  Google Scholar 

  14. Jiang JJ, Klein G, Hwang HG, Huang J, Hung SY (2004) An exploration of the relationship between software development process maturity and project performance. Inf Manag 41(3):279–288

    Article  Google Scholar 

  15. Clarke P, O’Connor RV (2012) The situational factors that affect the software development process: towards a comprehensive reference framework. Inf Softw Technol 54(5):433–447

    Article  Google Scholar 

  16. Kaner C, Bach J, Pettichord B (2008) Lessons learned in software testing. Wiley

    Google Scholar 

  17. Kuhn DR, Wallace DR, Gallo AM (2004) Software fault interactions and implications for software testing. IEEE Trans Software Eng 30(6):418–421

    Article  Google Scholar 

  18. Cadar C, Sen K (2013) Symbolic execution for software testing: three decades later. Communications 56(2):82–90

    Google Scholar 

  19. Hailpern B, Santhanam P (2002) Software debugging, testing, and verification. IBM Syst J 41(1):4–12

    Article  Google Scholar 

  20. Dearle A (2007) Software deployment, past, present and future. In: Future of software engineering (FOSE'07). IEEE, pp 269–284

    Google Scholar 

  21. Hall RS, Heimbigner D, Wolf AL (1999) A cooperative approach to support software deployment using the software dock. In: Proceedings of the 1999 international conference on software engineering (IEEE Cat. No. 99CB37002). IEEE, pp 174–183

    Google Scholar 

  22. Carzaniga A, Fuggetta A, Hall RS, Heimbigner D, Van Der Hoek A, Wolf AL (1998) A characterization framework for software deployment technologies. Colorado State University Fort Collins Department of Computer Science

    Google Scholar 

  23. Bennett KH, Rajlich VT (2000) Software maintenance and evolution: a roadmap. In: Proceedings of the conference on the future of software engineering. ACM, pp 73–87

    Google Scholar 

  24. Dishaw MT, Strong DM (1998) Supporting software maintenance with software engineering tools: a computed task–technology fit analysis. J Syst Softw 44(2):107–120

    Article  Google Scholar 

  25. Yau SS, Collofello JS (1980) Some stability measures for software maintenance. IEEE Trans Software Eng 6:545–552

    Article  Google Scholar 

  26. Bertolino A (2007) Software testing research: achievements, challenges, dreams. In: 2007 future of software engineering. IEEE Computer Society, pp 85–103

    Google Scholar 

  27. Buse RP, Zimmermann T (2010) Analytics for software development. In: Proceedings of the FSE/SDP workshop on future of software engineering research. ACM, pp 77–80

    Google Scholar 

  28. Buse RP, Zimmermann T (2012) Information needs for software development analytics. In: Proceedings of the 34th international conference on software engineering. IEEE Press, pp 987–996

    Google Scholar 

  29. Zhang D, Dang Y, Lou JG, Han S, Zhang H, Xie T (2011) Software analytics as a learning case in practice: Approaches and experiences. In: Proceedings of the international workshop on machine learning technologies in software engineering. ACM, pp 55–58

    Google Scholar 

  30. Martínez-Fernández, S., Vollmer, A. M., Jedlitschka A, Franch X, López L, Ram P, et al (2019) Continuously assessing and improving software quality with software analytics tools: a case study. IEEE access

    Google Scholar 

  31. Zhang D, Han S, Dang Y, Lou JG, Zhang H, Xie T (2013) Software analytics in practice. IEEE Softw 30(5):30–37.2

    Google Scholar 

  32. Abdellatif TM, Capretz LF, Ho D (2015) Software analytics to software practice: a systematic literature review. In: Proceedings of the first international workshop on BIG data software engineering. IEEE Press, pp 30–36

    Google Scholar 

  33. Shah A—Senior Management Trainee ERS Practice (2017) Engineering analytics–what is next in software engineering? Accessed dated on 20/6/2019. https://www.hcltech.com/blogs/engineering-analytics-what-next-software-engineering

  34. Menzies T, Williams L, Zimmermann T (2016) Perspectives on data science for software engineering. Morgan Kaufmann

    Google Scholar 

  35. Menzies T, Zimmermann T (2018) Software analytics: what’s next? IEEE Softw 35(5):64–70

    Article  Google Scholar 

  36. Hassan AE, Hindle A, Runeson P, Shepperd M, Devanbu P, Kim S (2013) Roundtable: what’s next in software analytics? IEEE Softw 30(4):53–56

    Article  Google Scholar 

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Correspondence to Somayya Madakam .

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Madakam, S., Revulagadda, R.K. (2021). Software Engineering Analytics—The Need of Post COVID-19 Business: An Academic Review. In: Patnaik, S., Tajeddini, K., Jain, V. (eds) Computational Management. Modeling and Optimization in Science and Technologies, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-030-72929-5_11

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