Abstract
Software projects have begun to accept crowdsourcing in several different phases of software design and production. Ideally, mass parallel production through Crowdsourcing could be an option to rapid acquisition in software engineering by leveraging on infinite worker resource on the internet. It is important to understand the patterns and strategies of decomposing and uploading parallel tasks in order to maintain stable worker supply as well as satisfactory task completion rate.
To address that end this research reports an empirical analysis on the available tasks’ lifecycle patterns in crowdsourcing. Following waterfall model in Crowdsourced Software Development (CSD), this research identified four patterns for sequence of task arrival per project: 1) Prior Cycle, 2) Current Cycle, 3) Orbit Cycle and 4) Fresh Cycle.
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Alelyani, T., Mao, K., Yang, Y.: Context-centric pricing: early pricing models for software crowdsourcing tasks. In: Proceedings of the 13th International Conference on Predictive Models and Data Analytics in Software Engineering, pp. 63–72 (2017)
Archak, N.: Money, glory and cheap talk: analyzing strategic behavior of contestants in simultaneous crowdsourcing contests on topcoder. com. In: Proceedings of the 19th International Conference on World Wide Web, pp. 21–30 (2010)
Bernstein, M.S., Brandt, J., Miller, R.C., Karger, D.R.: Crowds in two seconds: enabling realtime crowd-powered interfaces. In: Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 33–42 (2011)
Difallah, D.E., Demartini, G., Cudré-Mauroux, P.: Scheduling human intelligence tasks in multi-tenant crowd-powered systems. In: Proceedings of the 25th International Conference on World Wide Web, pp. 855–865 (2016)
Faradani, S., Hartmann, B., Ipeirotis, P.G.: What’s the right price? Pricing tasks for finishing on time. In: Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence (2011)
Gordon, G.: A general purpose systems simulation program. In: Proceedings of the December 12–14, 1961, Eastern Joint Computer Conference: Computers-key to Total Systems Control, pp. 87–104 (1961)
Howe, J.: Crowdsourcing: How the power of the crowd is driving the future of business. Random House (2008)
Jiang, H., Matsubara, S.: Efficient task decomposition in crowdsourcing. In: Dam, H.K., Pitt, J., Xu, Y., Governatori, G., Ito, T. (eds.) PRIMA 2014. LNCS (LNAI), vol. 8861, pp. 65–73. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-13191-7_6
Khanfor, A., Yang, Y., Vesonder, G., Ruhe, G., Messinger, D.: Failure prediction in crowdsourced software development. In: 2017 24th Asia-Pacific Software Engineering Conference (APSEC), pp. 495–504. IEEE (2017)
Khazankin, R., Psaier, H., Schall, D., Dustdar, S.: QoS-based task scheduling in crowdsourcing environments. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds.) ICSOC 2011. LNCS, vol. 7084, pp. 297–311. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25535-9_20
Lakhani, K.R., Garvin, D.A., Lonstein, E.: Topcoder (a): Developing software through crowdsourcing. Harvard Business School General Management Unit Case (610–032) (2010)
LaToza, T.D., Van Der Hoek, A.: Crowdsourcing in software engineering: models, motivations, and challenges. IEEE Softw. 33(1), 74–80 (2015)
Mao, K., Capra, L., Harman, M., Jia, Y.: A survey of the use of crowdsourcing in software engineering. J. Syst. Softw. 126, 57–84 (2017)
Mao, K., Yang, Y., Li, M., Harman, M.: Pricing crowdsourcing-based software development tasks. In: 2013 35th International Conference on Software Engineering (ICSE), pp. 1205–1208. IEEE (2013)
Marcus, A., Wu, E., Karger, D., Madden, S., Miller, R.: Human-powered sorts and joins. arXiv preprint arXiv:1109.6881 (2011)
Mejorado, D.M., Saremi, R., Yang, Y., Ramirez-Marquez, J.E.: Study on patterns and effect of task diversity in software crowdsourcing. In: Proceedings of the 14th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), pp. 1–10 (2020)
Mingozzi, A., Maniezzo, V., Ricciardelli, S., Bianco, L.: An exact algorithm for the resource-constrained project scheduling problem based on a new mathematical formulation. Manag. Sci. 44(5), 714–729 (1998)
Ngo-The, A., Ruhe, G.: Optimized resource allocation for software release planning. IEEE Trans. Softw. Eng. 35(1), 109–123 (2008)
Reinertsen, D.G.: Celeritas publishing (2009)
Ruhe, G., Saliu, M.O.: The art and science of software release planning. IEEE Softw. 22(6), 47–53 (2005)
Saremi, R.: A hybrid simulation model for crowdsourced software development. In: Proceedings of the 5th International Workshop on Crowd Sourcing in Software Engineering, pp. 28–29 (2018)
Saremi, R., Lotfalian Saremi, M., Desai, P., Anzalone, R.: Is this the right time to post my task? an empirical analysis on a task similarity arrival in topcoder. In: Yamamoto, S., Mori, H. (eds.) HCII 2020. LNCS, vol. 12185, pp. 96–110. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-50017-7_7
Saremi, R., Yang, Y., Khanfor, A.: Ant colony optimization to reduce schedule acceleration in crowdsourcing software development. In: Yamamoto, S., Mori, H. (eds.) HCII 2019. LNCS, vol. 11570, pp. 286–300. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22649-7_23
Saremi, R.L., Yang, Y., Ruhe, G., Messinger, D.: Leveraging crowdsourcing for team elasticity: an empirical evaluation at topcoder. In: 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP), pp. 103–112. IEEE (2017)
Saremi, R.L., Yang, Y.: Dynamic simulation of software workers and task completion. In: 2015 IEEE/ACM 2nd International Workshop on CrowdSourcing in Software Engineering, pp. 17–23. IEEE (2015)
Saremi, R.L., Yang, Y.: Empirical analysis on parallel tasks in crowdsourcing software development. In: 2015 30th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW), pp. 28–34. IEEE (2015)
Stol, K.J., Fitzgerald, B.: Two’s company, three’s a crowd: a case study of crowdsourcing software development. In: Proceedings of the 36th International Conference on Software Engineering, pp. 187–198 (2014)
Surowiecki, J.: The wisdom of crowds. Anchor (2005)
Urbaczek, J., Saremi, R., Saremi, M.L., Togelius, J.: Scheduling tasks for software crowdsourcing platforms to reduce task failure. arXiv preprint arXiv:2006.01048 (2020)
Wang, H., Ren, Z., Li, X., Jiang, H.: Solving team making problem for crowdsourcing with evolutionary strategy. In: 2018 5th International Conference on Dependable Systems and Their Applications (DSA), pp. 65–74. IEEE (2018)
Yang, Y., Karim, M.R., Saremi, R., Ruhe, G.: Who should take this task? dynamic decision support for crowd workers. In: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, pp. 1–10 (2016)
Yang, Y., Saremi, R.: Award vs. worker behaviors in competitive crowdsourcing tasks. In: 2015 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), pp. 1–10. IEEE (2015)
Yue, T., Ali, S., Wang, S.: An evolutionary and automated virtual team making approach for crowdsourcing platforms. In: Li, W., Huhns, M.N., Tsai, W.-T., Wu, W. (eds.) Crowdsourcing. PI, pp. 113–130. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-47011-4_7
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Saremi, R., Lotfalian Saremi, M., Jena, S., Anzalone, R., Bahabry, A. (2021). Impact of Task Cycle Pattern on Project Success in Software Crowdsourcing. In: Yamamoto, S., Mori, H. (eds) Human Interface and the Management of Information. Information-Rich and Intelligent Environments. HCII 2021. Lecture Notes in Computer Science(), vol 12766. Springer, Cham. https://doi.org/10.1007/978-3-030-78361-7_22
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