Abstract
This paper investigates the attributes related to the software development process (SDP) that affect software reliability (SR). In addition, the impact of management review (MR) on SR during testing period is studied. An interactive path model is developed to examine interrelationships between SDP factors, MR and SR. Partial Least Square is used for examining the consistency of factors within the model and to test predictive validity based on the hypothesis developed for relationships among factors. The survey-based research study is conducted to validate the model by collecting data from software professionals working at different job positions. The statistical results reveal that there is a direct positive influence of SDP factors on SR and MR positively moderates the relation between testing and SR. This means that management’s frequent assessment of the testing process, together with better planning and execution of SDP components, improves SR.
Similar content being viewed by others
References
Açıkgöz, A., Günsel, A., Bayyurt, N., & Kuzey, C. (2014). Team climate, team cognition, team intuition, and software quality: The moderating role of project complexity. Group Decision and Negotiation, 23(5), 1145–1176.
Agrawal, M., & Chari, K. (2007). Software effort, quality, and cycle time: A study of CMM level 5 projects. IEEE Transactions on Software Engineering, 33(3), 145–156.
Ammann, P., & Offutt, J. (2016). Introduction to software testing. Cambridge University Press.
Anand, S., Verma, V., & Aggarwal, A. G. (2018). 2-Dimensional multi-release software reliability modelling considering fault reduction factor under imperfect debugging. Ingeniería Solidaria, 14(25), 1–12.
Azuma, M. (2001). SQuaRE: the next generation of the ISO/IEC 9126 and 14598 international standards series on software product quality. ESCOM (European Software Control and Metrics conference).
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
Benington, H. D. (1956). Production of large computer programs. In: ONR Symposium on advanced programming methods for digital computers, United States.
Boehm, B. (1986). A spiral model of software development and enhancement. ACM SIGSOFT Software Engineering Notes, 11(4), 14–24.
Bstieler, L. (2005). The moderating effect of environmental uncertainty on new product development and time efficiency. Journal of Product Innovation Management, 22(3), 267–284.
Buchalcevova, A. (2021). Towards higher software quality in very small entities: ISO/IEC 29110 software basic profile mapping to testing standards. International Journal of Information Technologies and Systems Approach (IJITSA), 14(1), 79–96.
Capiluppi, A., Ajienka, N., & Counsell, S. (2020). The effect of multiple developers on structural attributes: A study based on Java Software. Journal of Systems and Software, 167, 110593.
Cepeda-Carrion, G., Cegarra-Navarro, J.-G., & Cillo, V. (2019). Tips to use partial least squares structural equation modelling (PLS-SEM) in knowledge management. Journal of Knowledge Management, 23(1), 67–89.
Chatterjee, S., & Shukla, A. (2017). An ideal software release policy for an improved software reliability growth model incorporating imperfect debugging with fault removal efficiency and change point. Asia-Pacific Journal of Operational Research, 34(03), 1740017.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217.
Ciolkowski, M., Laitenberger, O., & Biffl, S. (2003). Software reviews, the state of the practice. IEEE Software, 20(6), 46–51.
Cook, T. D., & Campbell, D. T. (1979). The design and conduct of true experiments and quasi-experiments in field settings. Reproduced in part in Research in Organizations: Issues and controversies. Goodyear Publishing Company.
Croarken, M. (2001). Secrets of software success: Management insights from 100 software firms around the world [book review]. IEEE Annals of the History of Computing, 23(1), 65–65.
Demirel, S. T., & Das, R. (2018). Software requirement analysis: Research challenges and technical approaches. In: 2018 6th International Symposium on Digital Forensic and Security (ISDFS).
Dhir, S., Kumar, D., & Singh, V. (2017). Requirement paradigms to implement the software projects in agile development using analytical hierarchy process. International Journal of Decision Support System Technology (IJDSST), 9(3), 28–41.
Dhir, S., Kumar, D., & Singh, V. (2019). Success and failure factors that impact on project implementation using agile software development methodology. Software Engineering (pp. 647–654). Springer.
Everett, G. D., & McLeod, R., Jr. (2007). Software testing: Testing across the entire software development life cycle. Wiley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Forsberg, K., & Mooz, H. (1991). The relationship of system engineering to the project cycle. INCOSE International Symposium.
Freedman, D., & Weinberg, G. (1984). Reviews, walkthroughs, and inspections. IEEE Transactions on Software Engineering, 10(1), 68–72.
Galin, D. (2018). Software quality management standards and models.
Geisser, S. (2017). Predictive inference. Routledge.
Gupta, V., Kapur, P. K., & Kumar, D. (2017). Modeling and measuring attributes influencing DevOps implementation in an enterprise using structural equation modeling. Information and Software Technology, 92, 75–91.
Hair, J. F., Jr., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46, 1–12.
Hanaysha, J. R. (2021). Impact of price promotion, corporate social responsibility, and social media marketing on word of mouth. Business Perspectives and Research, 9, 446.
Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565–580.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204.
IEC. (2001). 9126-1 (2001). Software Engineering Product Quality-Part 1: Quality Model. International Organization for Standardization.
IEEE. (1990). IEEE standard glossary of software engineering terminology. IEEE.
IEEE. (2008). 1028–2008 IEEE standard for software reviews and audits. IEEE.
ISO. (2015). 9001: 2015 Quality management systems. Requirements (ISO 9001: 2015). European Committee for Standardization.
Jung, H.-W., Kim, S.-G., & Chung, C.-S. (2004). Measuring software product quality: A survey of ISO/IEC 9126. IEEE Software, 21(5), 88–92.
Kapur, P., Pham, H., Gupta, A., & Jha, P. (2011). Software reliability assessment with OR applications. Springer.
Khan, A. A., & Keung, J. (2016). Systematic review of success factors and barriers for software process improvement in global software development. IET Software, 10(5), 125–135.
Kramer, M. (2018). Best practices in systems development lifecycle: An analyses based on the waterfall model. Review of Business & Finance Studies, 9(1), 77–84.
Lemke, G. (2018). The software development life cycle and its application.
Lewis, W. E. (2017). Software testing and continuous quality improvement. Auerbach publications.
Machado, P., Vincenzi, A., & Maldonado, J. C. (2007). Software testing: An overview. In: Pernambuco summer school on software engineering.
McCall, J. A., Richards, P. K., & Walters, G. F. (1977). Factors in software quality, volumes I, II, and III. US Rome Air Development Center Reports, US Department of Commerce.
Paulk, M. (2002). Capability maturity model for software. Encyclopedia of software engineering. Wiley.
Pham, T., & Pham, H. (2019). A generalized software reliability model with stochastic fault-detection rate. Annals of Operations Research, 277(1), 83–93.
Pyzdek, T. (2003). The six sigma handbook: The complete guide for greenbelts, blackbelts, and managers at all levels, revised and expanded. McGraw-Hill.
Rigby, P. C., German, D. M., & Storey, M.-A. (2008). Open source software peer review practices: a case study of the apache server. In: Proceedings of the 30th international conference on Software engineering.
Ringle, C., Wende, S., & Becker, J. (2014). Software SmartPLS 3.0. Hamburg: SmartPLS.
Royce, W. W. (1987). Managing the development of large software systems: concepts and techniques. In: Proceedings of the 9th international conference on Software Engineering.
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. Handbook of market research (pp. 1–40). Springer.
Stewart, K. J., & Gosain, S. (2006). The moderating role of development stage in free/open source software project performance. Software Process: Improvement and Practice, 11(2), 177–191.
Suki, N. M., & Suki, N. M. (2017). Determining students’ behavioural intention to use animation and storytelling applying the UTAUT model: The moderating roles of gender and experience level. The International Journal of Management Education, 15(3), 528–538.
Suryn, W., Abran, A., & April, A. (2003). ISO/IEC SQuaRE: The second generation of standards for software product quality. Acta Press.
Tam, C., da Costa Moura, E. J., Oliveira, T., & Varajão, J. (2020). The factors influencing the success of on-going agile software development projects. International Journal of Project Management, 38(3), 165–176.
Tao, H., Chen, Y., & Wu, H. (2020). A reallocation approach for software trustworthiness based on trustworthy attributes. Mathematics, 8(1), 14.
Wang, E. T., Ju, P.-H., Jiang, J. J., & Klein, G. (2008). The effects of change control and management review on software flexibility and project performance. Information & Management, 45(7), 438–443.
Wiegers, K. E. (2002). Peer reviews in software: A practical guide. Addison-Wesley.
Wong, K.K.-K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1–32.
Yamada, S. (2014). Software reliability modeling: Fundamentals and applications (Vol. 5). Cham: Springer.
Zhang, X., & Pham, H. (2000). An analysis of factors affecting software reliability. Journal of Systems and Software, 50(1), 43–56.
Zhang, X., Shin, M.-Y., & Pham, H. (2001). Exploratory analysis of environmental factors for enhancing the software reliability assessment. Journal of Systems and Software, 57(1), 73–78.
Zhu, M., & Pham, H. (2017). Environmental factors analysis and comparison affecting software reliability in development of multi-release software. Journal of Systems and Software, 132, 72–84.
Zhu, M., Zhang, X., & Pham, H. (2015). A comparison analysis of environmental factors affecting software reliability. Journal of Systems and Software, 109, 150–160.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Verma, V., Tandon, A. & Aggarwal, A.G. The Moderating Effect of Management Review in Enhancing Software Reliability: A Partial Least Square Approach. Inf Syst Front 24, 1845–1863 (2022). https://doi.org/10.1007/s10796-021-10209-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10796-021-10209-6