Atrophy in Aging Systems: Evidence, Dynamics, and Antidote

Published Online:https://doi.org/10.1287/isre.2023.1218

References

  • Agarwal R, Tiwana A (2015) Evolvable systems: Through the looking glass of IS. Inform. Systems Res. 26(3):473–479.LinkGoogle Scholar
  • Arbesman S (2017) Overcomplicated: Technology at the Limits of Comprehension (Portfolio, New York).Google Scholar
  • Arthur B (2009) The Nature of Technology (Free Press, New York).Google Scholar
  • Banker R, Slaughter S (2000) The moderating effects of structure on volatility and complexity in software enhancement. Inform. Systems Res. 11(3):219–240.LinkGoogle Scholar
  • Barr A (2018) The Problem with Software: Why Smart Engineers Write Bad Code (MIT Press, Cambridge, MA).CrossrefGoogle Scholar
  • Benbya H, Nan N, Tanriverdi H, Yoo Y (2020) Complexity and information systems research in the emerging digital world. Management Inform. Systems Quart. 44(1):1–17.Google Scholar
  • Biémont C, Vieira C (2006) Junk DNA as an evolutionary force. Nature 443(7111):521–524.CrossrefGoogle Scholar
  • Booch G (2007) The economics of architecture-first. IEEE Software 24(5):18–20.CrossrefGoogle Scholar
  • Booch G (2008) Measuring architectural complexity. IEEE Software 25(4):14–15.CrossrefGoogle Scholar
  • Borges H, Valente M (2018) What’s in a GitHub Star? Understanding repository starring practices in a social coding platform. J. Systems Software 146:112–129.CrossrefGoogle Scholar
  • Clearfield C (2019) Meltdown: What Plane Crashes, Oil Spills, and Dumb Business Decisions Can Teach Us About How to Succeed at Work and at Home (Penguin, London).Google Scholar
  • Coleman D (1994) using metrics to evaluate software system maintainability. IEEE Computer 27(8):44–49.CrossrefGoogle Scholar
  • Coleridge S (1798) The rime of the ancyent marinere. Lyrical Ballads (J. & A. Arch, London).Google Scholar
  • Eick S, Graves T, Karr A, Marron J, Mockus A (2001) Does code decay? Assessing evidence from change management data. IEEE Trans. Software Engrg. 27(1):1–12.CrossrefGoogle Scholar
  • Ford N, Parsons R, Kua P (2017) Building Evolutionary Architectures: Support Constant Change (O’Reilly, Sebastopol, CA).Google Scholar
  • Fürstenau D, Baiyere AKN (2019) A dynamic model of embeddedness in digital infrastructures. Inform. Systems Res. 30(4):1319–1342.LinkGoogle Scholar
  • Garcia J, Kouroshfar E, Ghorbani N, Malek S (2022) Forecasting architectural decay from evolutionary history. IEEE Trans. Software Engrg. 48(7):2439–2454.CrossrefGoogle Scholar
  • Ghanbari H, Vartiainen T, Siponen M (2018) Omission of quality software development practices: A systematic literature review. ACM Comput. Survey 51(2):1–27.CrossrefGoogle Scholar
  • Herraiz I, Rodriguez D, Robles G, Gonzalez-Barahona J (2013) The evolution of the laws of software evolution: A discussion based on a systematic literature review. ACM Comput. Survey 46(2):1–28.CrossrefGoogle Scholar
  • Kelly J, McGrath J (1988) On Time and Method (Sage, Thousand Oaks, CA).CrossrefGoogle Scholar
  • Kruchten P, Nord R, Ozkaya I (2012) Technical debt: From metaphor to theory and practice. IEEE Software 29(6):18–21.CrossrefGoogle Scholar
  • Lehman M (1979) On understanding laws, evolution, and conservation in the large-program life cycle. J. Systems Software 1:213–221.CrossrefGoogle Scholar
  • Lindberg A, Berente N, Gaskin J, Lyytinen K (2016) Coordinating interdependencies in online communities. Inform. Systems Res. 27(4):751–772.LinkGoogle Scholar
  • MacCormack A, Rusnak J, Baldwin C (2006) Exploring the structure of complex software designs: An empirical study of open source and proprietary code. Management Sci. 52(7):1015–1030.LinkGoogle Scholar
  • McCabe T (1976) A complexity measure. IEEE Trans. Software Engrg. 2(4):308–320.CrossrefGoogle Scholar
  • Minsky M (2006) The Emotion Machine (Simon & Schuster, New York).Google Scholar
  • Narayanan S, Balasubramanian S, Swaminathan J (2009) A matter of balance: Specialization, task variety, and individual learning in a software maintenance environment. Management Sci. 55(11):1861–1876.LinkGoogle Scholar
  • Pentland B, Liu P, Kremser W, Hærem T (2020) The dynamics of drift in digitized processes. Management Inform. Systems Quart. 44(1):19–47.CrossrefGoogle Scholar
  • Rolland K, Mathiassen L, Rai A (2018) Managing digital platforms in user organizations: The interactions between digital options and digital debt. Inform. Systems Res. 29(2):419–443.LinkGoogle Scholar
  • Salganik M (2017) Bit by Bit: Social Research in the Digital Age (Princeton University Press, Princeton, NJ).Google Scholar
  • Simon H (1962) The architecture of complexity. Proc. Amer. Philosophical Soc. 106(6):467–482.Google Scholar
  • Smith C (1981) A Search for Structure (MIT Press, Cambridge, MA).Google Scholar
  • Sobhy D, Bahsoon R, Minku L, Kazman R (2021) Evaluation of software architectures under uncertainty: A systematic literature review. ACM Trans. Software Engrg. Methodology 30(4):1–50.CrossrefGoogle Scholar
  • Steelman Z, Havakhor T, Sabherwal R, Sabherwal S (2019) Performance consequences of information technology investments: Implications of emphasizing new or current information technologies. Inform. Systems Res. 30(1):204–218.LinkGoogle Scholar
  • Subramanyam R, Ramasubbu N, Krishnan M (2012) In search of efficient flexibility: Effects of software component granularity on development effort, defects, and customization effort. Inform. Systems Res. 23(3):787–803.LinkGoogle Scholar
  • Tiwana A (2016) Platform desertion by app developers. J. Management Inform. Systems 32(4):40–77.CrossrefGoogle Scholar
  • Tiwana A (2018) Platform synergy: Architectural origins and competitive consequences. Inform. Systems Res. 24(9):829–848.LinkGoogle Scholar
  • Tufte E (2020) Seeing with Different Eyes: Meaning, Space, Data, Truth (Graphics Press, Cheshire, CT).Google Scholar
  • Wareham J, Fox P, Giner J (2014) Technology ecosystem governance. Organ. Sci. 25(4):1195–1215.LinkGoogle Scholar
  • Wittmann M (2017) Felt Time: The Science of How We Experience Time (MIT Press, Boston).Google Scholar
  • Yoo Y, Henfridsson O, Lyytinen K (2010) The new organizing logic of digital innovation: An agenda for information systems research. Inform. Systems Res. 21(4):724–735.LinkGoogle Scholar
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