Measurements in the Early Stage Software Start-ups: A Multiple Case Study in a Nascent Ecosystem

Open access

Abstract

Context: Software measurement is crucial to stay competitive and deliver quality software products.

Problem: While much research has been done on measurement in large companies in developed countries, there is limited research on measurement in start-ups. So far there are no studies on whether these results apply to nascent ecosystems, such as those in East Africa.

Goal: The aim of this study is to understand the use and perceived benefits of measurement in software start-ups in East Africa.

Method: We performed a multi-case study on 19 software start-ups in hubs in Uganda and Kenya, through conducting semi-structured interviews. We transcribed and analyzed them using the content analysis technique.

Results: We identified that start-ups are using a number of business and product-oriented metrics. Furthermore, we found no evidence on the use of design-oriented metrics. Nonetheless, start-ups have considerable expectations on the benefits of measuring. Finally, metrics found in this study partially differ from metrics used in start-ups in developed countries.

Conclusion: There is a need to create a more inclusive characterization for measurement as early start-ups in East Africa cannot yet be represented with known models.

[1] Abran A. Software metrics and software metrology. John Wiley & Sons, 2010.

[2] Albrecht A. J. and Gaffney J. E. Software function, source lines of code, and development e ort prediction: a software science validation. IEEE transactions on software engineering, (6):639–648, 1983.

[3] Bajwa S. S., Gencel C., and Abrahamsson P. Software product size measurement methods. In Proceedings of International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement, IWSM-Mensura, volume 14, pages 176–190.

[4] Bhattacharyya G. K. and Johnson R. A. Statistical methods and concepts, 1977.

[5] Chorev S. and Anderson A. R. Success in israeli high-tech start-ups; critical factors and process. Technovation, 26(2):162–174, 2006.

[6] Comer P. and Chard J. A measurement maturity model. Software Quality Journal, 2(4):277–289, 1993.

[7] Croll A. and Yoskovitz B. Lean analytics: Use data to build a better startup faster. “ O’Reilly Media, Inc.”, 2013.

[8] Crowne M. Why software product startups fail and what to do about it. evolution of software product development in startup companies. In Engineering Management Conference, 2002. IEMC’02. 2002 IEEE International, volume 1, pages 338–343. IEEE, 2002.

[9] Cukier D., Kon F., and Krueger N. Designing a maturity model for software startup ecosystems. In International Conference on Product-Focused Software Process Improvement, pages 600–606. Springer, 2015.

[10] Daskalantonakis M. K., Yacobellis R. H., and Basili V. R. A method for assessing software measurement technology. Quality Engineering, 3(1):27–40, 1990.

[11] Díaz-Ley M., García F., and Piattini M. Mis-pyme software measurement capability maturity model–supporting the definition of software measurement programs and capability determination. Advances in Engineering Software, 41(10-11):1223–1237, 2010.

[12] Duc A. N. and Abrahamsson P. Minimum viable product or multiple facet product? the role of mvp in software startups. In International Conference on Agile Software Development, pages 118–130. Springer, 2016.

[13] Fenton N. and Bieman J. Software metrics: a rigorous and practical approach. CRC press, 2014.

[14] Giardino C., Wang X., and Abrahamsson P. Why early-stage software startups fail: a behavioral framework. In International Conference of Software Business, pages 27–41. Springer, 2014.

[15] Kitchenham B. and Mendes E. Software productivity measurement using multiple size measures. IEEE Transactions on Software Engineering, 30(12):1023–1035, 2004.

[16] Klotins E., Unterkalmsteiner M., and Gorschek T. Software engineering knowledge areas in startup companies: a mapping study. In International Conference of Software Business, pages 245–257. Springer, 2015.

[17] Paranjape B., Rossiter M., and Pantano V. Performance measurement systems: successes, failures and future–a review. Measuring Business Excellence, 10(3):4–14, 2006.

[18] Park R. E. Software size measurement: A framework for counting source statements. Technical report, CARNEGIE-MELLON UNIV PITTSBURGH PA SOFTWARE ENGINEERING INST, 1992.

[19] Paternoster N., Giardino C., Unterkalmsteiner M., Gorschek T., and Abrahamsson P. Software development in startup companies: A systematic mapping study. Information and Software Technology, 56(10):1200–1218, 2014.

[20] Quinn Patton M. Qualitative research and evaluation methods, 2002.

[21] Ries E. Minimum viable product: a guide. Startup lessons learned, 2009.

[22] Ries E. The lean startup: How today’s entrepreneurs use continuous innovation to create radically successful businesses. Crown Books, 2011.

[23] Rompho N. Operational performance measures for startups. Measuring Business Excellence, 22(1):31–41, 2018.

[24] Runeson P. and Höst M. Guidelines for conducting and reporting case study research in software engineering. Empirical Software Engineering, 14(2):131, Dec 2008.

[25] Shi Y., Xu D., and Vessey I. Early-stage software start-up survival: the effects of managerial actions on firm performance. In International Conference on HCI in Business, pages 761–771. Springer, 2015.

[26] Staron M. and Meding W. Mesram–a method for assessing robustness of measurement programs in large software development organizations and its industrial evaluation. Journal of Systems and Software, 113:76–100, 2016.

[27] Sutton S. M. The role of process in software start-up. IEEE Software, 17(4):33–39, 2000.

[28] Unterkalmsteiner M., Abrahamsson P., Wang X., Nguyen-Duc A., Shah S., Bajwa S. S., Baltes G. H., Conboy K., Cullina E., Dennehy D., et al. Software startups–a research agenda. e-Informatica Software Engineering Journal, 10(1), 2016.

[29] Yin R. Case Study Research: Design and Methods. Applied Social Research Methods. SAGE Publications, 2003.

[30] Yin R. K. Applications of case study research. Sage, 2011.

[31] Yin R. K. Case study research and applications: Design and methods. Sage publications, 2017.

Foundations of Computing and Decision Sciences

The Journal of Poznan University of Technology

Journal Information


CiteScore 2017: 0.82

SCImago Journal Rank (SJR) 2017: 0.212
Source Normalized Impact per Paper (SNIP) 2017: 0.523

Mathematical Citation Quotient (MCQ) 2017: 0.02

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 72 72 37
PDF Downloads 52 52 26