Folklore in Software Engineering: A Definition and Conceptual Foundations

We explore the concept of folklore within software engineering, drawing from folklore studies to define and characterize narratives, myths, rituals, humor, and informal knowledge that circulate within software development communities. Using a literature review and thematic analysis, we curated exemplar folklore items (e.g., beliefs about where defects occur, the 10x developer legend, and technical debt). We analyzed their narrative form, symbolic meaning, occupational relevance, and links to knowledge areas in software engineering. To ground these concepts in practice, we conducted semi-structured interviews with 12 industrial practitioners in Sweden to explore how such narratives are recognized or transmitted within their daily work and how they affect it. Synthesizing these results, we propose a working definition of software engineering folklore as informally transmitted, traditional, and emergent narratives and heuristics enacted within occupational folk groups that shape identity, values, and collective knowledge. We argue that making the concept of software engineering folklore explicit provides a foundation for subsequent ethnography and folklore studies and for reflective practice that can preserve context-effective heuristics while challenging unhelpful folklore.

💡 Research Summary

This paper investigates the notion of folklore within the field of software engineering, borrowing concepts from folklore studies to define, categorize, and analyze the informal narratives, myths, rituals, humor, and tacit knowledge that circulate among software development communities. The authors begin by reviewing existing literature on software engineering culture, noting that while stories, “war tales,” and experience‑based anecdotes have been examined, a systematic folkloristic framework has been lacking. They adopt classic definitions from folklorists such as Alan Dundes—who describes folklore as informally transmitted traditional knowledge shared among a “folk group”—and Simon Bronner—who emphasizes folklore as living, performance‑oriented, and embedded in everyday routines.

Using these theoretical lenses, the researchers construct a set of dimensions they expect to capture software engineering folklore: myths, legends, anecdotes, rituals, artifacts, humor, superstitions, and informal knowledge. They then perform a literature search (Google Scholar and general web) for works that explicitly mention “software engineering folklore” or discuss related themes. From this exploratory collection they curate exemplar items, such as the belief that “bugs tend to cluster in certain modules,” the legendary “10× developer” productivity myth, and the concept of “technical debt” as a cultural artifact. Each item is coded for narrative form (myth, legend, anecdote, ritual, artifact), symbolic meaning (using Schein’s three‑level model of organizational culture), associated occupational groups (developers, testers, managers, architects, etc.), and mapped to one or more SWEBOK knowledge areas (testing, maintenance, design, etc.).

To ground the conceptual work in practice, the authors conduct semi‑structured interviews with twelve seasoned software practitioners in Sweden. Participants span a range of roles (project managers, requirements engineers, automation leads, senior developers, academics) and experience levels (9–41 years). The interview protocol is organized into three sections: (1) participants’ own definition of folklore in their work context; (2) exploration of four folklore types—myths/beliefs, anecdotes/legends, rituals/practices, artifacts/humor; and (3) transmission mechanisms and perceived impact (helpful, harmful, or mixed). Interviews lasted 45–60 minutes, were audio‑recorded where possible, transcribed, anonymized, and validated by participants.

Data analysis follows Braun and Clarke’s thematic analysis approach. Initial coding is both deductive (aligned with the predefined folklore dimensions) and inductive (allowing new categories to emerge). Coding reliability is ensured through a calibration interview coded by all authors, followed by double‑coding of the remaining interviews in rotating pairs. Themes are iteratively refined, and saturation is monitored; after the twelfth interview no substantially new themes appeared.

The analysis yields several key insights. First, folklore is transmitted through multiple channels: oral storytelling among colleagues, written notes or wiki entries, and digital platforms such as Slack, Reddit, or internal forums. Larger organizations rely more on digital artifacts, whereas smaller teams preserve oral traditions. Second, the symbolic meaning of folklore items occupies three cultural layers: basic underlying assumptions (e.g., “bugs cluster in module X”), espoused values (e.g., “code reviews build trust”), and visible artifacts (e.g., the moth in Grace Hopper’s logbook). Third, different occupational groups emphasize different folklore types: developers are most attuned to productivity myths (the 10× legend), testers to defect‑location myths, and managers to ritualized meetings (stand‑ups, retrospectives). Fourth, folklore exerts a dual impact. Positive effects include rapid dissemination of tacit knowledge, onboarding acceleration, and reinforcement of team identity. Negative effects arise when unverified myths shape decision‑making, create unrealistic expectations, or hinder adoption of new practices (e.g., the 10× myth influencing performance evaluations).

The authors propose a working definition: Software engineering folklore is informally transmitted, traditional and emergent narratives and heuristics enacted within occupational folk groups that shape identity, values, and collective knowledge. They argue that making this concept explicit provides a foundation for future ethnographic work, for reflective practice, and for preserving useful heuristics while critically challenging harmful myths.

Finally, the paper outlines avenues for further research: longitudinal studies of folklore evolution, cross‑cultural comparisons (e.g., between Nordic and Asian software communities), development of tools to capture and visualize folklore dynamics, and interventions such as “folklore workshops” that surface, evaluate, and possibly re‑author existing narratives. By framing software engineering culture through a folkloristic lens, the study opens a new interdisciplinary pathway for understanding how informal, story‑driven knowledge co‑exists with formal engineering processes.