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arxiv: 2606.11051 · v1 · pith:CPKV6YYTnew · submitted 2026-06-09 · 💻 cs.SE · cs.HC

Making Software Meaningful

Eagon Meng , Abutalib Namazov , Carmel Schare , Alcino Cunha , Daniel Jackson This is my paper

Pith reviewed 2026-06-27 12:16 UTC · model grok-4.3

classification 💻 cs.SE cs.HC
keywords explicit meaningdomain phenomenasoftware behaviorusabilitymodularityaccountabilitystakeholder vocabularysoftware engineering
0
0 comments X

The pith

Committing to explicit meaning—via a shared representation of domain individuals, actions and facts—improves software usability, modularity and accountability.

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

The paper claims that software can be improved across three separate dimensions by adopting one practice: constructing and agreeing on an explicit representation of its behavior as observed in the application domain. This representation uses individuals, the actions they participate in, and the facts produced by those actions as a common vocabulary that grounds all discussion, artifacts and activities among stakeholders. Actions are further partitioned into concepts to create larger units of meaning. The approach is illustrated through three examples: aligning users and designers on the same meaning for usability gains, mapping meaning units to code units when generating software with large language models, and defining agent behavior through a code of conduct expressed in those same terms.

Core claim

Adopting a commitment to explicit meaning entails building and maintaining a representation of software behavior observed in the domain of application, where the phenomena are individuals, actions they participate in, and facts that result from actions; these can be organized into concepts by partitioning the set of actions. This single representation then serves as the grounding vocabulary for all discourse about the software. The paper shows how this commitment produces concrete gains in usability by aligning user and designer views, in modularity by letting large language models generate code that maps directly to meaning units, and in accountability by having agents adhere to a meaning-b

What carries the argument

The explicit meaning representation, consisting of domain individuals, actions, and resulting facts, organized into concepts by partitioning actions, which grounds all stakeholder discourse and artifacts.

If this is right

  • Aligning users and designers on one shared meaning representation improves software usability.
  • Mapping units of meaning directly to units of code lets large language models produce modular and legible implementations.
  • Expressing an agent's intended behavior as a code of conduct in the same meaning vocabulary makes the agent accountable.
  • All artifacts and activities become grounded in the same vocabulary of individuals, actions, and facts.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same vocabulary could reduce ambiguity when multiple teams or organizations must coordinate on requirements.
  • It offers a potential bridge between informal domain descriptions and more formal verification techniques without requiring full logical formalization upfront.
  • Legacy systems might be made more maintainable by first extracting and documenting their implicit meaning representation before refactoring.

Load-bearing premise

Stakeholders can feasibly construct, agree upon, and maintain a shared representation of software behavior using domain individuals, actions, and facts without prohibitive cost, persistent disagreement, or loss of needed expressiveness.

What would settle it

A concrete software project in which stakeholders attempt to build and use such a domain-phenomena representation yet produce no measurable gains in usability, modularity, or accountability, or encounter irresolvable disagreement that halts progress.

read the original abstract

Adopting a single measure can improve the usability, modularity and accountability of software: a commitment to explicit meaning. This entails constructing and agreeing upon a representation of the behavior of the software, as observed in the domain of application. The phenomena comprising this behavior become a vocabulary that grounds all discourse about the software, among all stakeholders, and for all artifacts and activities. These phenomena are individuals; actions they participate in; and facts that result from actions. They can be organized, by partitioning the set of actions, into concepts, offering larger units of meaning. Examples of exploiting meaning are given in three areas: designing for usability (by aligning user and designer on a single shared meaning); generating modular code with LLMs (by mapping units of meaning to units of code, achieving not only modularity but also legibility); and making agents accountable (by having them adhere to a code of conduct that defines their intended behavior).

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

2 major / 2 minor

Summary. The manuscript proposes that committing to explicit meaning representations—constructed from domain phenomena as individuals, actions, and facts, then organized into concepts—can serve as a unifying measure to improve software usability, modularity, and accountability. It illustrates the idea through three application areas: aligning user and designer understandings for usability design, mapping meaning units to code units when generating software with LLMs, and enforcing agent behavior via an explicit code of conduct.

Significance. If the central proposal holds, the work could offer a foundational conceptual tool for software engineering by grounding all artifacts and stakeholder discourse in a shared domain vocabulary, potentially reducing fragmentation across design, implementation, and operation. The paper's conceptual breadth across usability, LLM-assisted development, and accountability is a strength, as is its emphasis on phenomena-based representations rather than ad-hoc abstractions.

major comments (2)
  1. [Abstract] Abstract and the three illustrative areas: the central claim that explicit meaning improves the three properties rests on the unexamined feasibility of stakeholders constructing, agreeing upon, and maintaining a shared representation of behavior; the examples supply no discussion of mechanisms for resolving disagreements or bounding maintenance costs, leaving the load-bearing practical assumption unaddressed.
  2. [LLM code generation area] The LLM code-generation example: the assertion that mapping units of meaning to units of code yields both modularity and legibility is presented without a concrete mapping procedure, comparison to existing modularization techniques, or demonstration that the resulting code remains correct with respect to the original meaning representation.
minor comments (2)
  1. The distinction between 'facts that result from actions' and the concepts formed by partitioning actions could be clarified with a short formal or diagrammatic example early in the text.
  2. The manuscript would benefit from explicit pointers to related work in domain-driven design or ontology-based software engineering to situate the proposal.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and thoughtful report. We address the two major comments point by point below, clarifying the conceptual scope of the manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract and the three illustrative areas: the central claim that explicit meaning improves the three properties rests on the unexamined feasibility of stakeholders constructing, agreeing upon, and maintaining a shared representation of behavior; the examples supply no discussion of mechanisms for resolving disagreements or bounding maintenance costs, leaving the load-bearing practical assumption unaddressed.

    Authors: The manuscript advances a conceptual proposal that explicit meaning representations, once established, can serve as a unifying measure across usability, modularity, and accountability. The central claim concerns the downstream benefits of grounding artifacts and discourse in such a representation; it does not purport to supply or evaluate the upstream processes of construction, stakeholder agreement, or ongoing maintenance. These activities are treated as prerequisites whose detailed mechanisms (including disagreement resolution and cost bounding) lie outside the paper's scope. The examples illustrate exploitation of an already-available meaning vocabulary rather than its creation. revision: no

  2. Referee: [LLM code generation area] The LLM code-generation example: the assertion that mapping units of meaning to units of code yields both modularity and legibility is presented without a concrete mapping procedure, comparison to existing modularization techniques, or demonstration that the resulting code remains correct with respect to the original meaning representation.

    Authors: The LLM example is offered at an illustrative level to show how an explicit vocabulary of individuals, actions, facts, and concepts could supply natural decomposition boundaries for generated code. No concrete mapping algorithm is supplied because the contribution is the organizing principle itself, not an implementation recipe; any such procedure would be domain- and LLM-specific. The paper does not compare against existing modularization methods because it positions meaning-based units as a complementary rather than competing criterion. Correctness is preserved by construction when the meaning representation functions as the authoritative specification and the mapping remains faithful to it. revision: no

Circularity Check

0 steps flagged

No significant circularity

full rationale

The paper is a position paper advancing a conceptual proposal for explicit meaning representations in software. It contains no equations, fitted parameters, predictions of derived quantities, or load-bearing self-citations. The argument is presented as an independent commitment to domain phenomena (individuals, actions, facts, concepts) rather than any derivation that reduces to its own inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

The abstract introduces no explicit free parameters, mathematical axioms, or new postulated entities; the framework is presented as a conceptual commitment rather than a formal system with fitted quantities.

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