Abstract
Practitioners adopt software metrics programs to support their software development from the perspective of either overall quality, performance, or both. Current literature details and justifies the role of a metrics program in a software organization’s software development, but empirical evidence to demonstrate its actual use and concomitant benefits remains scarce. In the context of an EU H2020 Project, we conducted a multiple case study to investigate how two software-intensive Agile companies utilized a metrics program in their software development. We invited practitioners from the two case companies to report on the actual use of the metrics program, the underlying rationale, and any benefits they may have witnessed. We also collected and analyzed metrics data from multiple use cases to explain the reported use of the metrics. The analysis revealed improvements like better code review practices and formalization of quality requirements management, either as a direct consequence or as a byproduct of the use of the metrics. The contrasting contexts like company size, project characteristics, and general perspective towards metrics programs could explain why one company viewed the metrics as a trigger for their reported improvements, while the other company saw metrics as the main driver for their improvements. Empirical evidence from our study should help practitioners adopt a more favorable view towards metrics programs, who were otherwise reluctant due to lack of evidence of their utility and benefits in industrial context.
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Workflow metrics such as Work in Progress, Cycle Time, and Throughput.
References
Liechti, O., Pasquier, J., Reis, R.: Beyond dashboards: On the many facets of metrics and feedback in agile organizations. In: Proceedings - 2017 IEEE/ACM 10th International Workshop on Cooperative and Human Aspects of Software Engineering, CHASE 2017, pp. 16–22 (2017)
Staron, M., Meding, W.: Ensuring reliability of information provided by measurement systems. In: Abran, A., Braungarten, R., Dumke, R.R., Cuadrado-Gallego, J.J., Brunekreef, J. (eds.) IWSM 2009. LNCS, vol. 5891, pp. 1–16. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-05415-0_1
Yang, Y., Falessi, D., Menzies, T., Hihn, J.: Actionable analytics for you. IEEE Softw. 35, 51–53 (2018)
Bird, C., Murphy, B., Nagappan, N., Zimmermann, T.: Empirical software engineering at Microsoft Research. In: Proceedings of the ACM Conference on Computer Supported Cooperative Work. CSCW, pp. 143–150 (2011)
Menzies, T., Zimmermann, T.: Software analytics: so what? IEEE Softw. 30, 31–37 (2013)
Zhang, D., Han, S., Dang, Y., Lou, J.G., Zhang, H., Xie, T.: Software analytics in practice. IEEE Softw. 30, 30–37 (2013)
Kupiainen, E., Mäntylä, M.V., Itkonen, J.: Using metrics in Agile and lean software development - A systematic literature review of industrial studies. Inf. Softw. Technol. 62, 143–163 (2015)
Staron, M., Meding, W.: Transparent measures: Cost-efficient measurement processes in SE. In: Software Technology Transfer Workshop, pp. 1–4, Kista, Sweden (2015)
Van Solingen, R., Berghout, E.: Integrating goal-oriented measurement in industrial software engineering: Industrial experiences with and additions to the Goal/Question/Metric method (GQM). In: Proceedings of Seventh International Software and Metrics Symposium, pp. 246–258 (2001)
Mendonça, M.G., Basili, V.R.: Validation of an approach for improving existing measurement frameworks. IEEE Trans. Softw. Eng. 26, 484–499 (2000)
Hall, T., Fenton, N.: Implementing effective software metrics programs. IEEE Softw. 14, 55–64 (1997)
Iversen, J., Mathiassen, L.: Cultivation and engineering of a software metrics program. Inf. Syst. J. 13, 3–19 (2003)
Staron, M., Meding, W.: Factors determining long-term success of a measurement program: An industrial case study. e-Informatica Softw. Eng. J. 1, 7–23 (2012)
Croll, A., Yoskovitz, B.: Lean Analytics: Use Data to Build a Better Startup Faster (2013)
Buse, R.P.L., Zimmermann, T.: Information needs for software development analytics - Microsoft research. MSR Technical report 2011-8, pp. 1–16 (2011)
Port, D., Taber, B.: Actionable analytics for strategic maintenance of critical software: An industry experience report. IEEE Softw. 35, 58–63 (2017)
Vacanti, D., Vallet, B.: Actionable Metrics at Siemens Health Services (2014)
Franch, X., et al.: Data-driven requirements engineering in agile projects: The Q-Rapids approach. In: Proceedings - 2017 IEEE 25th International Requirements Engineering Conference Workshops, REW 2017, pp. 411–414 (2017)
Ram, P., Rodriguez, P., Oivo, M.: Software process measurement and related challenges in agile software development: A multiple case study. In: Kuhrmann, M., et al. (eds.) PROFES 2018. LNCS, vol. 11271, pp. 272–287. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03673-7_20
Ram, P., Rodriguez, P., Oivo, M.: Success factors for effective process metrics operationalization in agile software development: A multiple case study. In: Proceedings of the 2019 International Conference on Software and System Process (2019)
López, L., et al.: Q-rapids tool prototype: supporting decision-makers in managing quality in rapid software development. In: Mendling, J., Mouratidis, H. (eds.) CAiSE 2018. LNBIP, vol. 317, pp. 200–208. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92901-9_17
Oriol, M., et al.: Data-driven elicitation of quality requirements in agile companies. In: Piattini, M., Rupino da Cunha, P., García Rodríguez de Guzmán, I., Pérez-Castillo, R. (eds.) QUATIC 2019. CCIS, vol. 1010, pp. 49–63. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29238-6_4
Tahir, T., Rasool, G., Gencel, C.: A systematic literature review on software measurement programs. Inf. Softw. Technol. 73, 101–121 (2016)
Dubinsky, Y., Talby, D., Hazzan, O., Keren, A.: Agile metrics at the Israeli Air Force. In: Agile Development Conference (ADC 2005), pp. 12–19. IEEE Computer Society (2005)
Díaz-Ley, M., García, F., Piattini, M.: Implementing software measurement programs in non mature small settings. In: Cuadrado-Gallego, J.J., Braungarten, R., Dumke, R.R., Abran, A. (eds.) IWSM/Mensura -2007. LNCS, vol. 4895, pp. 154–167. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85553-8_13
Runeson, P., Höst, M.: Guidelines for conducting and reporting case study research in software engineering. Empir. Softw. Eng. 14, 131–164 (2009)
Meneely, A.: Actionable metrics are better metrics. In: Perspectives on Data Science for Software Engineering, pp. 283–287. Elsevier (2016)
Acknowledgments
This work is a result of the Q-Rapids Project, funded by the European Union’s Horizon 2020 research and innovation program, under grant agreement No. 732253.
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Ram, P. et al. (2020). An Empirical Investigation into Industrial Use of Software Metrics Programs. In: Morisio, M., Torchiano, M., Jedlitschka, A. (eds) Product-Focused Software Process Improvement. PROFES 2020. Lecture Notes in Computer Science(), vol 12562. Springer, Cham. https://doi.org/10.1007/978-3-030-64148-1_26
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