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arxiv: 1906.11072 · v1 · pith:TK2WLNQ6new · submitted 2019-06-26 · 💻 cs.SE

Temporal Discounting in Software Engineering: A Replication Study

Pith reviewed 2026-05-25 15:18 UTC · model grok-4.3

classification 💻 cs.SE
keywords temporal discountingsoftware engineeringreplication studyintertemporal choicesprofessional experiencetechnical debt
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The pith

Software professionals with broader experience exhibit less temporal discounting in project decisions.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This replication study shows that software engineers and students tend to prefer immediate benefits over future ones when making project choices, a pattern called temporal discounting. The effect appears consistently across different countries and participant types, but varies greatly between individuals. Participants with wider professional experience discount the future less than those with narrower experience. Understanding this helps explain why long-term issues like technical debt are often under-addressed in practice.

Core claim

The results confirm the occurrence of temporal discounting in samples of both professional and student participants from different countries and demonstrate strong variance in discounting between study participants. Professional experience influenced discounting, with broader experience linked to less discounting.

What carries the argument

A questionnaire-based observational study measuring preferences in intertemporal choices, with professional experience breadth as the key background factor.

Load-bearing premise

The questionnaire and selected background factors like professional experience breadth accurately capture temporal discounting without being heavily influenced by unmeasured variables or the replication design changes.

What would settle it

A new study using the same questionnaire finding no significant difference in discounting rates between groups with broad and narrow professional experience.

Figures

Figures reproduced from arXiv: 1906.11072 by Alexander Chatzigeorgiou, Birgit Penzenstadler, Christoph Becker, Colin Venters, Fabian Fagerholm, Leticia Duboc, Rahul Mohanani, Stefanie Betz.

Figure 1
Figure 1. Figure 1: Example of the area under curve (AUC) approach for a single participant [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Discounting is pronounced, and most pronounced for [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 2
Figure 2. Figure 2: Median discount rate as a function of time horizon (original study). [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Intertemporal choice task questionnaire (excerpt). [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Participant demographics. company responsibility to broadly categorize respondents into comparable roles. We calculated the discount rate as a function of time horizons using the exponential model with annualized continuous compounding according to (2). We calculated the overall discount rate using the area under curve for the empirical function, as shown in (3). Descriptive statistics, e.g., frequency and… view at source ↗
Figure 5
Figure 5. Figure 5: Distribution of professional experience (areas of responsibility). [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Distribution of time savings (days) required to prefer a long-term [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗
Figure 5
Figure 5. Figure 5: For analysis, we binned the variable into three equal [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 7
Figure 7. Figure 7: Median discount rate for all participants across project time horizons. [PITH_FULL_IMAGE:figures/full_fig_p008_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Discounting by professional experience (Medians: low 2.46; medium [PITH_FULL_IMAGE:figures/full_fig_p009_8.png] view at source ↗
read the original abstract

Background: Many decisions made in Software Engineering practices are intertemporal choices: trade-offs in time between closer options with potential short-term benefit and future options with potential long-term benefit. However, how software professionals make intertemporal decisions is not well understood. Aim: This paper investigates how shifting time frames influence preferences in software projects in relation to purposefully selected background factors. Method: We investigate temporal discounting by replicating a questionnaire-based observational study. The replication uses a changed-population and -experimenter design to increase the internal and external validity of the original results. Results: The results of this study confirm the occurrence of temporal discounting in samples of both professional and student participants from different countries and demonstrate strong variance in discounting between study participants. We found that professional experience influenced discounting. Participants with broader professional experience exhibited less discounting than those with narrower experience. Conclusions: The results provide strong empirical support for the relevance and importance of temporal discounting in SE and the urgency of targeted interdisciplinary research to explore the underlying mechanisms and their theoretical and practical implications. The results suggest that technical debt management could be improved by increasing the breadth of experience available for critical decisions with long-term impact. In addition, the present study provides a methodological basis for replicating temporal discounting studies in software engineering.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript reports a replication of a prior questionnaire-based observational study on temporal discounting in software engineering decisions. Using a changed-population (professionals and students from multiple countries) and changed-experimenter design, it claims to confirm the presence of temporal discounting, document substantial inter-participant variance, and demonstrate that participants reporting broader professional experience exhibit less discounting than those with narrower experience. Practical implications are drawn for technical debt management and the value of interdisciplinary research.

Significance. The changed-population and changed-experimenter replication design is a clear methodological strength that addresses threats to external validity present in single-study designs. If the reported experience effect survives proper covariate adjustment and full statistical reporting, the work would supply usable empirical grounding for the relevance of temporal discounting to SE practice and would support targeted recommendations about experience breadth in decision-making teams.

major comments (3)
  1. [Results] Results section: the manuscript supplies no sample sizes, exclusion rules, statistical tests, p-values, confidence intervals, or effect sizes for either the confirmation of temporal discounting or the professional-experience effect. Without these quantities the central claims cannot be evaluated for reliability or practical importance.
  2. [Results / §5] Analysis of background factors (Results / §5): the reported association between self-reported breadth of professional experience and reduced discounting does not state whether the model controlled for age, total years in industry, education level, or other correlated covariates. If these variables absorb the variance, the experience-breadth claim is not supported.
  3. [Method] Method section: no validation or pilot data are presented establishing that the questionnaire instrument isolates temporal discounting preferences from response biases, social-desirability effects, or other confounds introduced by the changed experimenter and population.
minor comments (2)
  1. [Abstract] The abstract would be strengthened by inclusion of at least the key sample sizes and the direction and approximate magnitude of the experience effect.
  2. Figure captions and axis labels should explicitly indicate the discounting measure (e.g., discount rate or indifference point) and the exact operationalization of 'breadth of professional experience'.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive comments, which highlight important gaps in statistical reporting and methodological transparency. We address each major comment below and will revise the manuscript accordingly to strengthen the presentation of results and methods.

read point-by-point responses
  1. Referee: [Results] Results section: the manuscript supplies no sample sizes, exclusion rules, statistical tests, p-values, confidence intervals, or effect sizes for either the confirmation of temporal discounting or the professional-experience effect. Without these quantities the central claims cannot be evaluated for reliability or practical importance.

    Authors: We agree that the submitted manuscript does not include these details in the Results section. The data collection yielded specific sample sizes and applied exclusion criteria, and statistical analyses were performed, but these were not reported in the text. In the revised version we will add a Participants subsection and a dedicated statistical reporting subsection that includes sample sizes, exclusion rules, the tests used, p-values, confidence intervals, and effect sizes for both the temporal discounting confirmation and the experience effect. revision: yes

  2. Referee: [Results / §5] Analysis of background factors (Results / §5): the reported association between self-reported breadth of professional experience and reduced discounting does not state whether the model controlled for age, total years in industry, education level, or other correlated covariates. If these variables absorb the variance, the experience-breadth claim is not supported.

    Authors: The analysis in §5 is based on a direct association without multivariate controls for correlated variables such as age or total years in industry. We acknowledge that this leaves open the possibility that the observed effect is not unique to experience breadth. In the revision we will add a multiple regression analysis that includes these covariates and report whether the experience-breadth association remains after adjustment. revision: yes

  3. Referee: [Method] Method section: no validation or pilot data are presented establishing that the questionnaire instrument isolates temporal discounting preferences from response biases, social-desirability effects, or other confounds introduced by the changed experimenter and population.

    Authors: The instrument was taken directly from the original study. We did not conduct new pilot validation for the changed population and experimenter. We will expand the Method section to discuss potential response biases and any consistency checks performed on the collected data, and we will explicitly note the absence of new validation as a limitation of the replication design. revision: partial

Circularity Check

0 steps flagged

Empirical replication with independent data collection; no derivations or self-referential reductions

full rationale

This paper reports results from a questionnaire-based observational replication on new participant samples (professionals and students from different countries). The central claims rest on direct empirical observations of temporal discounting rates and their association with self-reported professional experience breadth. No equations, fitted parameters, predictive models, or derivation chains appear in the work. Self-citations to the original study supply methodological context but do not substitute for or reduce the new observations; the replication design explicitly changes population and experimenter to increase validity. The reported findings are therefore self-contained against external benchmarks and do not reduce to prior inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

Empirical replication study; relies on standard questionnaire analysis and the assumption that self-reported preferences on hypothetical scenarios map to real project decisions. No new entities or fitted parameters are introduced.

axioms (2)
  • domain assumption Questionnaire responses on hypothetical intertemporal choices validly measure discounting behavior in software project contexts
    Invoked in the method and results sections to interpret observed preferences as evidence of temporal discounting.
  • standard math Standard statistical comparison of means or correlations suffices to detect influence of professional experience
    Used to support the claim that broader experience reduces discounting.

pith-pipeline@v0.9.0 · 5778 in / 1341 out tokens · 35977 ms · 2026-05-25T15:18:35.491009+00:00 · methodology

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