Important Dates
- Submissions Deadline: 1 July 2024
- Publication: February 2025
Before 2023, Low Code/No Code was emerging as a growing industry with the potential to permit so-called “citizen programmers” to assemble code without having to mind the tedious syntax of traditional coding languages. Often resembling Lego-like construction on a screen, Low Code/No Code permitted the assembly of functional modules in such a fashion as to accomplish relatively common enterprise tasks. The 2019 $11.45B market cap for such packages was projected to have a compound annual growth rate (CAGR) of 22.7% from 2020-2027. It is viewed as an economical way to increase corporate productivity.
In 2023, however, large language models (LLMs) became sufficiently robust to burst onto the scene as generative AI. At a minimum, generative AI permits code validation, but with the right prompts, automated code generation also becomes possible. While engineering firms, especially in aerospace, have been autogenerating code for a long time, generative AI opened the doors further to cadres of citizen programmers.
Early generative AI, however, lacked the power to perform the simplest of mathematics. The failure to properly reason numerically inhibited the ability to create sophisticated algorithmic programs. With the quiet announcement of Q* (Q Star) at Open AI, an otherwise semantically trained LLM was further enabled with reason. Significantly, generative AI took a step towards logical reasoning, at least for the moment, at a rudimentary level.
With these developments, should software professionals be concerned with the Fear of Being Obsolete (FOBO) or should they rejoice over the luxury of not having to deal with repetitious coding tasks? Worse, does Q* suggest a gain in the momentum of the p(doom) sentiment? While coder obsolescence may not be immediate, the new vectors in Low Code/No Code potential may pose a longer-term threat to even the most sophisticated algorithm developers who elect to stick with traditional coding techniques.
Given this backdrop, this Special Issue of Computer seeks submissions that deal with Low Code/No Code in all of its forms. This entails but is not limited to consideration of the following elements.
- Where Low Code/No Code is applicable or not applicable
- Limitations on Low Code/No Code based on increasing levels of complexity.
- Strengths and weaknesses of Low Code/No Code built-in functions, algorithms, and abstractions.
- Low Code/No Code boundaries.
- Low Code/No Code inherent security management limitations.
- Code verification and validation, traditional, LLM or AI-assisted.
- Contrasts between LLMs coding vs commercial GUI Low Code/No Code packages vs autonomous coding practices.
- Research initiatives in speech or thought-driven coding.
- Low Code/No Code GUI issues.
- Low Code/No Code Integration with other corporate code, including legacy code.
- The ability of Low Code/No Code to Scale to enterprise levels.
- Role of ML/NLP in future coding models.
- Governance in a Low Code/No Code organization.
- Models for corporate adoption of Low Code/No Code and a resulting market share.
- Role of Low Code/No Code in enabling Digital Transformation.
- Threat automated/augmented coding presents to traditional programmers.
- Extension to executable papers
- Implications for High-Performance Computing (HPC)
- Implications for workforce development and education
- Global reach
Submission Guidelines
For author information and guidelines on submission criteria, visit the Author’s Information page. Please submit papers through the ScholarOne system and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. If requested, abstracts should be sent by email to the guest editors directly.
Questions?
Contact the guest editors at co2-25@computer.org
