Christoph Becker
ABSTRACT
Technical Debt arises from decisions that favour short-term outcomes at the cost of longer-term disadvantages. They may be taken knowingly or based on missing or incomplete awareness of the costs; they are taken in different roles, situations, stages and ways. Whatever technical or business factor motivate such decisions, they always imply a trade-off in time, a 'now vs. later'. How exactly are such decisions made, and how have they been studied?
This paper analyzes how decisions on technical debt are studied in software engineering via a systematic literature review. It examines the presently published Software Engineering research on Technical Debt, with a particular focus on decisions involving time. The findings reveal surprising gaps in published work on empirical research in decision making. We observe that research has rarely studied how decisions are made, even in papers that focus on the decision process. Instead, most attention is focused on engineering measures and feeding them into an idealized decision making process. These findings lead to a set of recommendations for future empirical research on Technical Debt.
- Paris Avgeriou, Philippe Kruchten, Ipek Ozkaya, and Carolyn Seaman. 2016. Managing Technical Debt in Software Engineering (Dagstuhl Seminar 16162). Dagstuhl Reports 6, 4(2016), 110--138.Google Scholar
- Lee Roy Beach and Raanan Lipshitz. 1993. Why classical decision theory is an inappropriate standard for evaluating and aiding most human decision making. (1993). http://psycnet.apa.org/psycinfo/1993-97634-002Google Scholar
- Christoph Becker, Ruzanna Chitchyan, Stefanie Betz, and Curtis McCord. 2018. Trade-off Decisions Across Time in Technical Debt Management: Literature review Coding and Reference Documentation. (2018).Google Scholar
- Christoph Becker, Dawn Walker, and Curtis McCord. 2017. Intertemporal choice: decision making and time in software engineering. In Proceedings of the 10th International Workshop on Cooperative and Human Aspects of Software Engineering. IEEE Press, 23--29. Google ScholarDigital Library
- Christoph Becker, Dawn Walker, and Curtis McCord. 2017. A systematic literature review on intertemporal choice in software engineering-protocol and results. arXiv preprint arXiv: 1701.08310 (2017).Google Scholar
- Stephany Bellomo, Neil Ernst, Robert Nord, and Rick Kazman. 2014. Toward Design Decisions to Enable Deployability: Empirical Study of Three Projects Reaching for the Continuous Delivery Holy Grail. In Proceedings of the 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN '14). IEEE Computer Society, Washington, DC, USA, 702--707. Google ScholarDigital Library
- Michael Berry and Aybüke Aurum. 2006. Measurement and Decision Making. In Value-Based Software Engineering. Springer, 155--177.Google Scholar
- Stefan Biffl, Aybuke Aurum, Barry Boehm, Hakan Erdogmus, and Paul Grünbacher. 2006. Value-based software engineering. Springer Science & Business Media. Google ScholarDigital Library
- Neil A Ernst, Stephany Bellomo, Ipek Ozkaya, Robert L Nord, and Ian Gorton. 2015. Measure it? manage it? ignore it? software practitioners and technical debt. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering. ACM, 50--60. Google ScholarDigital Library
- Shane Frederick, George Loewenstein, and Ted O'donoghue. 2002. Time discounting and time preference: A critical review. Journal of economic literature 40, 2 (2002), 351--401.Google ScholarCross Ref
- Yuepu Guo, Carolyn Seaman, and Fabio QB da Silva. 2016. Costs and obstacles encountered in technical debt management-A case study. Journal of Systems and Software 120 (2016), 156--169. Google ScholarDigital Library
- Yuepu Guo, Rodrigo Oliveira Spínola, and Carolyn Seaman. 2016. Exploring the costs of technical debt management-a case study. Empirical Software Engineering 21, 1 (2016), 159--182. Google ScholarDigital Library
- Ralph L Keeney and Howard Raiffa. 1993. Decisions with multiple objectives: preferences and value trade-offs. Cambridge university press.Google Scholar
- Barbara Kitchenham. 2004. Procedures for performing systematic reviews. Keele, UK, Keele University 33, 2004 (2004), 1--26.Google Scholar
- Gary Klein. 2008. Naturalistic Decision Making. Human Factors 50, 3 (June 2008), 456--460.Google ScholarCross Ref
- Gary A. Klein (Ed.). 1993. Decision making in action : models and methods. Ablex Pub., Norwood, N.J.Google Scholar
- Gary A Klein. 1999. Sources of power: How people make decisions. MIT press.Google Scholar
- Tim Klinger, Peri Tarr, Patrick Wagstrom, and Clay Williams. 2011. An enterprise perspective on technical debt. In Proceedings of the 2nd Workshop on managing technical debt. ACM, 35--38. Google ScholarDigital Library
- Per Lenberg, Robert Feldt, and Lars Göran Wallgren. 2015. Behavioral software engineering: A definition and systematic literature review. Journal of Systems and Software 107 (2015), 15--37. Google ScholarDigital Library
- Marko Leppänen, Samuel Lahtinen, Kati Kuusinen, Simo Mäkinen, Tomi Männistö, Juha Itkonen, Jesse Yli-Huumo, and Timo Lehtonen. 2015. Decision-making framework for refactoring. In Managing Technical Debt (MTD), 2015 IEEE 7th International Workshop on. IEEE, 61--68.Google ScholarCross Ref
- Raanan Lipshitz, Gary Klein, Judith Orasanu, and Eduardo Salas. 2001. Taking stock of naturalistic decision making. Journal of Behavioral Decision Making 14, 5 (Dec. 2001), 331--352.Google ScholarCross Ref
- George Loewenstein, Ted O'Donoghue, and Matthew Rabin. 2003. Projection Bias in Predicting Future Utility. The Quarterly Journal of Economics 118, 4 (2003), 1209--1248.Google ScholarCross Ref
- George Loewenstein, Daniel Read, and Roy F Baumeister. 2003. Time and decision: Economic and psychological perspectives of intertemporal choice. Russell Sage Foundation.Google Scholar
- George Loewenstein, Scott Rick, and Jonathan D Cohen. 2008. Neuroeconomics. Annu. Rev Psychol. 59 (2008), 647--672.Google ScholarCross Ref
- Philipp Mayring. 2000. Qualitative Content Analysis. In Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, Vol. 1.Google Scholar
- Steve McConnell. 2007. Technical debt. Software Best Practices, Nov (2007).Google Scholar
- Frederico Oliveira, Alfredo Goldman, and Viviane Santos. 2015. Managing technical debt in software projects using scrum: An action research. In Agile Conference (AGILE), 2015. IEEE, 50--59. Google ScholarDigital Library
- Johnny Saldaña. 2012. The Coding Manual for Qualitative Researchers. Number 14. Sage.Google Scholar
- Helen Sharp, Yvonne Dittrich, and Cleidson RB de Souza. 2016. The role of ethnographic studies in empirical software engineering. IEEE Transactions on Software Engineering 42, 8 (2016), 786--804. Google ScholarDigital Library
- Clauirton Siebra A Siebra, Graziela S Tonin, Fabio QB Silva, Rebeka G Oliveira, Antonio LOC Junior, Regina CG Miranda, and Andre LM Santos. 2012. Managing technical debt in practice: an industrial report. In Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement. ACM, 247--250. Google ScholarDigital Library
- Will Snipes, Brian Robinson, Yuepu Guo, and Carolyn Seaman. 2012. Defining the decision factors for managing defects: a technical debt perspective. In Managing Technical Debt (MTD), 2012 Third International Workshop on. IEEE, 54--60. Google ScholarDigital Library
- Evangelos Triantaphyllou. 2000. Multi-Criteria Decision Making Methods. Springer US, Boston, MA, 5--21.Google Scholar
- A Tversky and D Kahneman. 1981. The framing of decisions and the psychology of choice. Science 211, 4481 (1981), 453--458.Google Scholar
- Amos Tversky and Daniel Kahneman. 1983. Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological review 90, 4 (1983), 293.Google Scholar
- Amos Tversky and Daniel Kahneman. 1986. Rational Choice and the Framing of Decisions. The Journal of Business 59, 4 (1986), S251--S278.Google ScholarCross Ref
- John Von Neumann and Oskar Morgenstern. 1944. Theory of games and economic behavior. Princeton university press.Google Scholar
- John Von Neumann and Oskar Morgenstern. 1944. Theory of games and economic behavior. Princeton university press.Google Scholar
- Elke U Weber. 2006. Experience-based and description-based perceptions of long-term risk: Why global warming does not scare us (yet). Climatic change 77, 1 (2006), 103--120.Google Scholar
- Roel Wieringa, Neil Maiden, Nancy Mead, and Colette Rolland. 2006. Requirements engineering paper classification and evaluation criteria: a proposal and a discussion. Requirements Engineering 11, 1 (2006), 102--107. Google ScholarDigital Library
- Jesse Yli-Huumo, Andrey Maglyas, and Kari Smolander. 2015. The benefits and consequences of workarounds in software development projects. In International Conference of Software Business. Springer, 1--16.Google ScholarCross Ref
- Carmen Zannier, Mike Chiasson, and Frank Maurer. 2007. A model of design decision making based on empirical results of interviews with software designers. Information and Software Technology 49, 6 (2007), 637--653. Google ScholarDigital Library
Index Terms
- Trade-off decisions across time in technical debt management: a systematic literature review
Recommendations
A portfolio approach to technical debt management
MTD '11: Proceedings of the 2nd Workshop on Managing Technical DebtTechnical debt describes the effect of immature software artifacts on software maintenance - the potential of extra effort required in future as if paying interest for the incurred debt. The uncertainty of interest payment further complicates the ...
Temporal discounting in technical debt: how do software practitioners discount the future?
TechDebt '19: Proceedings of the Second International Conference on Technical DebtTechnical Debt management decisions always imply a trade-off among outcomes at different points in time. In such intertemporal choices, distant outcomes are often valued lower than close ones, a phenomenon known as temporal discounting. Technical Debt ...
Using technical debt data in decision making: potential decision approaches
MTD '12: Proceedings of the Third International Workshop on Managing Technical DebtThe management of technical debt ultimately requires decision making -- about incurring, paying off, or deferring technical debt instances. This position paper discusses several existing approaches to complex decision making, and suggests that exploring ...
Comments