Introduction
The evolution of AI and natural language processing has given rise to powerful platforms like ChatGPT, which can generate human-like text, including code snippets. However, as described in the below previous blogs, use of platforms like ChatGPT to augment software development can introduce serious risk. Additionally, the use-cases with best outcomes are limited to snippet-level-to-feature-level code generation. In this blog, we will investigate how YouGen Sharp surpasses the limitations of platforms like ChatGPT to produce the highest quality outcomes and the greatest benefit to custom software development productivity. This blog post is meant to follow reading of YouGen Software. Code Generation: Large Language Models vs Template-Driven Techniques and YouGen Software. The Risks Involved with Using ChatGPT for C# Code Generation.
Ease of Use:
ChatGPT has given rise to a new skill-set referred to as "prompt engineering". This term refers to the fact that relevance and quality of outputs from ChatGPT are directly dependent on how specifically and robustly the question entered to the prompt is. In short, developers need to know how to ask a question the right way in order to get the right answer. Two developers could attempt the same prompting with the same goal in mind and receive two different outputs. Additionally, outputs must be vetted for correctness, modified for adherence to stylistic, architectural, and security standards, imported into a codebase, and reviewed by teams.
YouGen Sharp, by contrast involves a simple workflow with far more productive, predictable output. Developers enter a connection string including a credential with schema reading permissions to a SQL Server or Oracle database into the downloaded YouGen Sharp client, click a button, and a whole-solution codebase is generated based on the data schema targeted. Within seconds, developers can open the generated solution and run it, debug its features, or extend the codebase as necessary to add business logic as needed. Generated code is a stylistically cohesive, designed to be as modular, easy to read, easy to extend as possible.
Generation Scope:
ChatGPT is best used to generate code from a snippet-to-feature scope. Ensuring good fit for inclusion within a codebase is up to the developer. Whole-solution architecture, coding standards, and relevance to data-driven-design principles are out of scope without volunteering this information into the large language model runtime. As described in YouGen Software. The Risks Involved with Using ChatGPT for C# Code Generation, volunteering this information involves organizational risk, so safest use-cases are limited to more trivial outcomes. Delivering quality products using code generation with ChatGPT requires a well-designed, standards-compliant whole-solution architecture and codebase to exist prior to including generated code.
YouGen Sharp was designed from the ground up to deliver a full-solution codebase including a well-defined series of projects and coded features. Outputs are carefully architected to deliver a rich set of immediately runnable capabilities, all built around your data schemas. Software development lifecycle focuses around adding features according to convention and standards to generated modern solution codebases. YouGen Sharp is an excellent way to immediately start fresh and drastically reduce the time-line to deliver brand new solutions based on your data schemas.
Strategic and Stylistic Coherency:
Given the diversity of outputs that may result from ChatGPT prompting attempts, the likelihood that outputs match a development team's standards for techniques, code formatting, and other preferences is low. Sure, generated outputs can be modified to meet team standards, but at times the effort to upgrade the outputs is equal to the effort to write code from scratch.
YouGen Sharp generates codebases according to a deterministic algorithm, delivering strategic and stylistic coherency across the full solution worth of projects and code files. Given a scenario where no changes to the data schema targets have occurred, outputs from running the same version of YouGen Sharp are identical. Code format and style decisions represent the C# community's most common conventions. This consistency allows for rules-based automation of refactoring generated codebases, efficiently and easily, en-masse using tools like Resharper or CodeMaid should development teams adopt other conventions.
Versioned Generational Consistency:
ChatGPT generates outputs based on the evolving training-state of its underlying model. Its outputs represent the highest weighted relevancy to the data available at the last time of training. This has several negative consequences. One is that outputs are biased towards common prevalence. The more common a coding strategy can be found in the training data, the more likely the strategy will be represented in generated outputs. More common does not always mean best result. The second consequence is that output capability and quality for cutting-edge techniques based off new SDK releases or algorithms is far less than for older SDKs and common algorithms. A third consequence is that the same prompt entered weeks, months, or years apart into ChatGPT will produce different answers. This reduces capability for building repeatable processes, strategic "lock-in", and overall productivity.
YouGen Sharp generates outputs identically per version of the runtime, given no changes to the target data schemas. This enables team trust in reliability and stability of outputs, and enhances the capability to produce strategic and stylistic coherency between projects and their software development lifecycles over time. This stability increases product quality, staff trainability, and enables "lock-in" on implementation techniques, SDK versions, and vulnerability assessment.
Vulnerability Minimization:
ChatGPT has proven awareness of common code vulnerabilities, but has demonstrated that it commonly generates source code that is not robust against even those same vulnerabilities. See How Security is Code Generated by ChatGPT for a much deeper investigation on the topic.
YouGen Sharp generates code that has been vetted against known vulnerabilities and produces outcomes that represent industry best practices to minimize the potential for risk. One of the most important parts of our SDLC processes for YouGen Sharp involves tracking the most up-to-date information available related to vulnerabilities that may impact the SDKs and algorithms underlying our generational outputs. We make a commitment to our subscribers to communicate any vulnerabilities identified and remediate them through patching of our YouGen Sharp runtimes.
Performance Optimization:
ChatGPT is a great tool for generating snippet and feature-level code that "works" to accomplish the goal at hand. But the scope of generation does not factor in any knowledge of underlying software architecture, integrated systems, or other highly relevant areas of performance optimization.
YouGen Sharp is architected to deliver whole-solution architecture with features and algorithms carefully implemented to represent the most optimum balance of performance, code-intuitivity, and maintainability for C# development teams.
Maintainability, Upgradeability and Roadmap:
ChatGPT was not specifically designed to produce quality source code outputs, but for general purpose language interpretation and response. Thus, its use cases for code generation come with no guarantees on relevance, quality, maintainability, upgradeability or roadmap.
Each general release of YouGen Sharp strives to produce ever more maintainable and futureable codebases. In fact, one of the primary use-cases for YouGen Sharp is generating whole-solution upgrade replacements for aging, unmaintainable codebases. YouGen Sharp's architectural roadmap and feature-set are informed by the feedback from our subscribers, and are largely intended to follow the roadmap for the .NET SDK.
Upskilling:
ChatGPT is a great tool for investigating coded feature implementation strategies. It is highly productive when used for research efforts, able to produce outcomes that give developers ideas and options from an objective perspective, largely biased toward prevalence of comon algorithms in the model training data. ChatGPT represents an opportunity to efficiently discover how other development teams have commonly converged on answers to problems.
YouGen Sharp takes a more holistic angle on use-cases for upskilling dev teams. One of the most common and effective upskilling paths in software development teams is implementing a pattern of providing teams a working implementation example that represents best practices and includes a wide scope. This kind of example is not only a way to teach algorithms and standards when onboarding developers, but offer a big-picture view that justifies a feature-level implementation strategy in conjunction with the solution architecture as a whole. Any sort of algorithmic and stylistic standards enforcement is made easier by enabling developers toward full, robust codebases as a starting point as opposed to the vacuum of carte-blanche, start-from-scratch scenarios.
Privacy and Propriety:
ChatGPT in its current state is high-risk, low-transparency product. Nobody knows how prompt inputs may be used to further refine large language models. There is no guarantee that developers using ChatGPT aren't leaking organizational secrets or proprietary intellectual property. ChatGPT's creator OpenAI already has suffered hacks and data breaches. In one case, over 100 thousand accounts were stolen and are now for sale on the dark web. In another case, a data breach revealed many users' prompt data history to other users. ChatGPT is not a safe option for nontrivial code generation. Additionally, OpenAI has been sued for using unauthorized proprietary data to train its models.
YouGen Sharp offers an ideal alternative to the unsafe option of ChatGPT. From a technical perspective, YouGen Sharp runs locally on subscriber machines and connects to your database instances privately over your network topology. The downloaded tooling only involves a single transaction over the internet to authenticate the subscriber with YouGen Software servers and obtain the subscription tier used to determine the scope of generation. Additionally, your schema data never leaves the machine used to trigger generation, and only schema data is read from your databases. We encourage all subscribers to test these facts. YouGen Software LLC guarantees in our YouGen Software. Conditions of use that we will never obtain your data, share your schema, or use any of your organization's intellectual property. We can guarantee your organization's privacy and propriety because we intentionally never gain access to any sensitive data to begin with. Finally, YouGen Software only generates code and features that are compliant with licensing models of SDKs employed. In the end, you own the code generated and and are subject only to the terms of the permissive licenses involved with the SDKs employed. We try to favor MIT license when selecting generation targets and related SDKs.
Conclusion:
ChatGPT is a useful tool for software development teams to use for the purposes of research and implementation options assessment. It poses serious organizational risks, however, when used as a tool to generate code for adoption into your codebases. Additionally, the generated outputs from ChatGPT have limitations on scope and knowledge of your organization's data schemas, solution architecture, coding and stylistic standards and preferences. Volunteering this information to the ChatGPT prompt should be considered absolutely prohibited.
YouGen Sharp offers a far better alternative to gaining astounding increases in productivity and code quality for software teams. Our whole-solution generation algorithm minimizes risk, maximizes code ownership, and provides a future for software teams to upskill and improve in consistency over time. We keep our subscribers safe through guarantees to never obtain our subscribers' proprietary data. We provide the simplest path to begin producing more value from your software development team. Finally, the solutions, projects, features, and implementations YouGen Sharp generates for our subscribers are informed by our subscribers. We take your feedback seriously when planning for future releases with the goal of producing the most value for you for the software development areas you find most valuable.
Helpful Links:
Over 100,000 ChatGPT accounts stolen and sold on dark web | TechRadar
ChatGPT creator OpenAI sued for stealing private data | Fortune