Business Software for Kotlin

Flawnter automates static application security testing to detect hidden security bugs and quality issues at the source. Flawnter is a great alternative to manual code review. It can speed up the process and find bugs you may not have noticed. You can either create your own extensions for Flawnter or use existing ones. Extensions allow you to test more bugs and expand your testing coverage. Extensions are easy and allow you to access Flawnter functionality. Flawnter has a simple and flexible pricing structure that makes it affordable for all sizes of organizations to improve their application code security. Other options are also available.

Tggl was designed for teams that need to move quickly. The intuitive interface allows your entire team to modify the features of your app at any time. There are no longer lengthy deployment cycles for small changes. Tggl doesn't require technical knowledge so your product team can make decisions right away without developers. Tggl makes it easy for flags to be managed across mobile, web, or backend applications. You can organize your flags into projects or development environments. Tggl allows you to manage release dates, allow features for a select few users, for certain countries, and any custom business logic. You can randomly show different versions of a feature, and you will see which one performs best. Tggl ensures that every user has the same version of a feature, which makes your app more intuitive.

Descope is a CIAM platform meant for developers and IT teams. Customers can easily create frictionless and secure user journey flows for each user interaction using our no-code workflow builder and SDKs. Descope allows developers to spend more time working on core app projects by abstracting the details of authentication methods, session management, and risk management. Our platform makes it easy to manage users, tenants, RBAC, SCIM provisioning, and identity federation without any hassle. Customers use Descope to enhance user experience with passwordless authentication, improve security with risk-based MFA, and centralize user identities across all business-facing apps.

Qwen-7B is the 7-billion parameter iteration of Alibaba Cloud's Qwen language model series, also known as Tongyi Qianwen. This large language model utilizes a Transformer architecture and has been pretrained on an extensive dataset comprising web texts, books, code, and more. Furthermore, we introduced Qwen-7B-Chat, an AI assistant that builds upon the pretrained Qwen-7B model and incorporates advanced alignment techniques. The Qwen-7B series boasts several notable features: It has been trained on a premium dataset, with over 2.2 trillion tokens sourced from a self-assembled collection of high-quality texts and codes across various domains, encompassing both general and specialized knowledge. Additionally, our model demonstrates exceptional performance, surpassing competitors of similar size on numerous benchmark datasets that assess capabilities in natural language understanding, mathematics, and coding tasks. This positions Qwen-7B as a leading choice in the realm of AI language models. Overall, its sophisticated training and robust design contribute to its impressive versatility and effectiveness.

Dyte's Video SDK and APIs are SOC 2, GDPR, and HIPAA compliant. Embed scalable, customisable and secure video call into your web or mobile app with just few lines of code. It is compatible with Android, iOS, React Native, Angular and many more languages. With an uptime of 99.99%, industry-leading documentation, UI kit and out of the box plugins, customize the video experience within minutes.

Mistral 7B is a language model with 7.3 billion parameters that demonstrates superior performance compared to larger models such as Llama 2 13B on a variety of benchmarks. It utilizes innovative techniques like Grouped-Query Attention (GQA) for improved inference speed and Sliding Window Attention (SWA) to manage lengthy sequences efficiently. Released under the Apache 2.0 license, Mistral 7B is readily available for deployment on different platforms, including both local setups and prominent cloud services. Furthermore, a specialized variant known as Mistral 7B Instruct has shown remarkable capabilities in following instructions, outperforming competitors like Llama 2 13B Chat in specific tasks. This versatility makes Mistral 7B an attractive option for developers and researchers alike.

The barKoder SDK for Barcode Scanner will transform your users' smartphones and tablets into rugged barcode scanners without the need to purchase & maintain expensive hardware with a short lifespan. barKoder can decode more than 30 barcode symbols, including 1D (Codabar, Code 25, Code 39. Code 93, Code 128, EAN, Interleaved 2of5, MSI Plessey, Pharmacode, Telepen, UPC, etc.) & 2D barcodes (Aztec Code, Data Matrix, PDF417, QR Code, etc.) across Android, iOS, Linux, Flutter The latest version of barKoder's barcode scanner SDK features a revolutionary Batch MultiScan engine that allows for the scanning of multiple barcodes simultaneously. It also includes the ultra-powerful DPM Mode for scanning Data Matrix code engraved using Direct Part Marking methods.

In honor of Cleopatra, whose magnificent fate concluded amidst the tragic incident involving a snake, we are excited to introduce Codestral Mamba, a Mamba2 language model specifically designed for code generation and released under an Apache 2.0 license. Codestral Mamba represents a significant advancement in our ongoing initiative to explore and develop innovative architectures. It is freely accessible for use, modification, and distribution, and we aspire for it to unlock new avenues in architectural research. The Mamba models are distinguished by their linear time inference capabilities and their theoretical potential to handle sequences of infinite length. This feature enables users to interact with the model effectively, providing rapid responses regardless of input size. Such efficiency is particularly advantageous for enhancing code productivity; therefore, we have equipped this model with sophisticated coding and reasoning skills, allowing it to perform competitively with state-of-the-art transformer-based models. As we continue to innovate, we believe Codestral Mamba will inspire further advancements in the coding community.

Introducing Mistral NeMo, our latest and most advanced small model yet, featuring a cutting-edge 12 billion parameters and an expansive context length of 128,000 tokens, all released under the Apache 2.0 license. Developed in partnership with NVIDIA, Mistral NeMo excels in reasoning, world knowledge, and coding proficiency within its category. Its architecture adheres to industry standards, making it user-friendly and a seamless alternative for systems currently utilizing Mistral 7B. To facilitate widespread adoption among researchers and businesses, we have made available both pre-trained base and instruction-tuned checkpoints under the same Apache license. Notably, Mistral NeMo incorporates quantization awareness, allowing for FP8 inference without compromising performance. The model is also tailored for diverse global applications, adept in function calling and boasting a substantial context window. When compared to Mistral 7B, Mistral NeMo significantly outperforms in understanding and executing detailed instructions, showcasing enhanced reasoning skills and the ability to manage complex multi-turn conversations. Moreover, its design positions it as a strong contender for multi-lingual tasks, ensuring versatility across various use cases.

The Mixtral 8x22B represents our newest open model, establishing a new benchmark for both performance and efficiency in the AI sector. This sparse Mixture-of-Experts (SMoE) model activates only 39B parameters from a total of 141B, ensuring exceptional cost efficiency relative to its scale. Additionally, it demonstrates fluency in multiple languages, including English, French, Italian, German, and Spanish, while also possessing robust skills in mathematics and coding. With its native function calling capability, combined with the constrained output mode utilized on la Plateforme, it facilitates the development of applications and the modernization of technology stacks on a large scale. The model's context window can handle up to 64K tokens, enabling accurate information retrieval from extensive documents. We prioritize creating models that maximize cost efficiency for their sizes, thereby offering superior performance-to-cost ratios compared to others in the community. The Mixtral 8x22B serves as a seamless extension of our open model lineage, and its sparse activation patterns contribute to its speed, making it quicker than any comparable dense 70B model on the market. Furthermore, its innovative design positions it as a leading choice for developers seeking high-performance solutions.

Zed is an advanced code editor crafted for seamless collaboration between humans and AI, emphasizing high performance. Developed entirely in Rust to maximize the efficiency of multiple CPU cores and GPU resources, it allows for the integration of emerging LLMs into your coding workflow for tasks such as code generation, transformation, and analysis. The platform facilitates real-time communication with team members, enabling collaborative note-taking, screen sharing, and project management. With its multibuffer system, users can edit selected excerpts from the entire codebase on a single interface. It also supports inline code evaluation through Jupyter runtimes, allowing for joint notebook editing. Zed is compatible with numerous programming languages, thanks to Tree-sitter, WebAssembly, and the Language Server Protocol. Its quick native terminal is integrated with Zed's language-aware task runner and AI features, enhancing productivity. The editor offers first-class modal editing through Vim bindings, incorporating functionalities such as text objects and marks for efficient navigation. Built by a diverse global community of thousands of developers, Zed encourages users to enhance their experience with a wide array of extensions that expand language capabilities, provide various themes, and more. Furthermore, its user-friendly design aims to streamline development workflows, making it an ideal choice for programmers looking to elevate their coding efficiency.

ZeroPath is an innovative security platform harnessing AI technology to simplify application security for developers. It integrates smoothly with current CI/CD workflows, allowing for continuous, human-like security assessments and pull request (PR) evaluations. Utilizing its AI-powered code vulnerability scanning, ZeroPath effectively identifies and resolves critical issues such as broken authentication, logic errors, and outdated dependencies. To ensure a hassle-free installation, the platform incorporates a GitHub app that is compatible with GitHub, GitLab, and BitBucket. Notably, ZeroPath excels at uncovering intricate vulnerabilities that other scanning tools might miss, providing quicker security checks while minimizing false positives. Beyond merely flagging issues, ZeroPath proactively generates PRs with patches when it is confident that the changes won't disrupt application functionality, thus alleviating noise and preventing backlog buildup. Additionally, the platform's robust features also include Static Application Security Testing (SAST) and the identification of weaknesses in authentication processes and business logic. This comprehensive approach empowers developers to maintain high security standards with ease.

Lapce is an innovative, open-source code editor designed to provide a swift and responsive experience, especially beneficial for developers tackling extensive projects or intricate codebases. Developed using Rust, Lapce takes advantage of native development's performance benefits to ensure a seamless editing experience that minimizes delays. The editor boasts a sleek, contemporary interface alongside advanced features like multi-caret editing, split views, and integrated terminal capabilities. By incorporating support for the Language Server Protocol (LSP), Lapce delivers accurate autocompletion, syntax highlighting, and efficient code navigation for a variety of programming languages, ultimately boosting developer productivity. Its high degree of extensibility, comprehensive plugin support, and emphasis on performance position Lapce as an optimal choice for developers seeking a lightweight yet robust editor that effectively combines simplicity with functionality, making it appealing to both novices and experienced coders alike. Furthermore, Lapce's commitment to community-driven development ensures that it continues to evolve, addressing the needs of users and keeping pace with the ever-changing landscape of software development.

Qwen2.5 represents a state-of-the-art multimodal AI system that aims to deliver highly precise and context-sensitive outputs for a diverse array of uses. This model enhances the functionalities of earlier versions by merging advanced natural language comprehension with improved reasoning abilities, creativity, and the capacity to process multiple types of media. Qwen2.5 can effortlessly analyze and produce text, interpret visual content, and engage with intricate datasets, allowing it to provide accurate solutions promptly. Its design prioritizes adaptability, excelling in areas such as personalized support, comprehensive data analysis, innovative content creation, and scholarly research, thereby serving as an invaluable resource for both professionals and casual users. Furthermore, the model is crafted with a focus on user engagement, emphasizing principles of transparency, efficiency, and adherence to ethical AI standards, which contributes to a positive user experience.

Tülu 3 is a cutting-edge language model created by the Allen Institute for AI (Ai2) that aims to improve proficiency in fields like knowledge, reasoning, mathematics, coding, and safety. It is based on the Llama 3 Base and undergoes a detailed four-stage post-training regimen: careful prompt curation and synthesis, supervised fine-tuning on a wide array of prompts and completions, preference tuning utilizing both off- and on-policy data, and a unique reinforcement learning strategy that enhances targeted skills through measurable rewards. Notably, this open-source model sets itself apart by ensuring complete transparency, offering access to its training data, code, and evaluation tools, thus bridging the performance divide between open and proprietary fine-tuning techniques. Performance assessments reveal that Tülu 3 surpasses other models with comparable sizes, like Llama 3.1-Instruct and Qwen2.5-Instruct, across an array of benchmarks, highlighting its effectiveness. The continuous development of Tülu 3 signifies the commitment to advancing AI capabilities while promoting an open and accessible approach to technology.

Enhance your productivity by ensuring only high-quality code is released, as SonarQube Cloud (previously known as SonarCloud) seamlessly evaluates branches and enriches pull requests with insights. Identify subtle bugs to avoid unpredictable behavior that could affect users and address security vulnerabilities that threaten your application while gaining knowledge of application security through the Security Hotspots feature. Within moments, you can begin using the platform right where your code resides, benefiting from immediate access to the most current features and updates. Project dashboards provide vital information on code quality and readiness for release, keeping both teams and stakeholders in the loop. Showcase project badges to demonstrate your commitment to excellence within your communities. Code quality and security are essential across your entire technology stack, encompassing both front-end and back-end development. That’s why we support a wide range of 24 programming languages, including Python, Java, C++, and many more. The demand for transparency in coding practices is on the rise, and we invite you to be a part of this movement; it's completely free for open-source projects, making it an accessible opportunity for all developers! Plus, by participating, you contribute to a larger community dedicated to improving software quality.

Scalable, end to end management for third party code, license compliance and Open Source has been a critical supplier for modern software businesses. It has changed the way people think about code. FOSSA provides the infrastructure to enable modern teams to succeed with open source. FOSSA's flagship product allows teams to track open source code used in their code. It also automates license scanning and compliance. FOSSA's tools have been used to ship software by over 7,000 open-source projects (Kubernetes Webpack, Terraform and ESLint) as well as companies like Uber, Ford, Zendesk and Motorola. FOSSA code is used by many in the software industry today. FOSSA is a venture-funded startup that has been backed by Cosanoa Ventures and Bain Capital Ventures. Marc Benioff (Salesforce), Steve Chen(YouTube), Amr Asadallah (Cloudera), Jaan Talin (Skype), Justin Mateen (Tinder) are some of the affiliate angels.

Enhance the quality of your code by adopting healthier coding practices and refining your code review process. Codecov offers a suite of integrated tools designed to organize, merge, archive, and compare coverage reports seamlessly. This service is free for open-source projects, with paid plans beginning at just $10 per user each month. It supports multiple programming languages, including Ruby, Python, C++, and JavaScript, and can be effortlessly integrated into any continuous integration (CI) workflow without the need for extensive setup. The platform features automatic merging of reports across all CI systems and languages into a unified document. Users can receive tailored status updates on various coverage metrics and review reports organized by project, folder, and test type, such as unit or integration tests. Additionally, detailed comments on the coverage reports are directly included in your pull requests. Committed to safeguarding your data and systems, Codecov holds SOC 2 Type II certification, which verifies that an independent third party has evaluated and confirmed their security practices. By utilizing these tools, teams can significantly increase code quality and streamline their development processes.

Our Cloud IDE streamlines your workflow by setting up a development environment within seconds, allowing you to effortlessly code, learn, build, and collaborate on various projects. With Codeanywhere's exceptional web-based code editor, you'll quickly forget any previous coding tools you’ve used. It fully supports all major programming languages, including JavaScript/TypeScript, PHP, Python, Ruby, Go, Java, C/C++, and C#, along with many others. Enjoy intelligent editing capabilities like auto-complete, code refactoring, symbol renaming, and the ability to jump to definitions, among various other features. You can debug your code effectively using breakpoints, call stacks, and an interactive console. The platform includes a fully functional Git client and is expandable with a wide range of existing extensions. Additionally, you can launch powerful containers in mere seconds, which can be completely preconfigured to suit your preferred programming environment. Develop and execute your code on our infrastructure while having full sudo access, and benefit from prebuilt development environments equipped with the necessary tools and databases already installed for all leading programming languages. This makes it easier than ever to start working on your project without any hassle.

Datalore is a platform for collaborative data science and analytics that aims to improve the entire analytics workflow and make working with data more enjoyable for both data scientists as well as data-savvy business teams. Datalore is a collaborative platform that focuses on data teams workflow. It offers technical-savvy business users the opportunity to work with data teams using no-code and low-code, as well as the power of Jupyter Notebooks. Datalore allows business users to perform analytic self-service. They can work with data using SQL or no-code cells, create reports, and dive deep into data. It allows core data teams to focus on simpler tasks. Datalore allows data scientists and analysts to share their results with ML Engineers. You can share your code with ML Engineers on powerful CPUs and GPUs, and you can collaborate with your colleagues in real time.

Integrate your team's code evaluations with automated style suggestions across all programming languages in a single platform. Connecting your repository takes just a few clicks, and our review process is completed faster than ever. You can either adopt the recommended style guides or tailor each tool to meet your team's preferences. Utilize auto-fixing features to rectify style discrepancies, allowing you to concentrate on providing constructive feedback. Stickler CI retains your code solely for the duration of the review process, ensuring that your data is secure; once the review comments are made, your code is promptly deleted from our servers. Gradually enhance and unify the quality of your code with each pull request, ensuring that your coding standards are consistently applied amid ongoing changes without hindering your team's workflow. Achieve uniformity in your code quality and style by automatically employing style and quality verification tools. You have the option to either stick with the default settings or customize linters to align with your current coding standards, making it easier for your team to maintain high-quality code. In this way, you can foster a collaborative environment while promoting best practices in coding.

Material serves as a versatile framework of principles, elements, and resources that enhance user interface design practices. With its foundation in open-source code, Material fosters collaboration between designers and developers, enabling teams to efficiently create visually appealing products. Drawing inspiration from the tangible aspects of the world, such as textures and light dynamics, Material Design innovatively reinterprets traditional mediums like paper and ink. The approach is anchored in print design techniques, including typography, grids, spacing, scaling, color usage, and imagery, to establish hierarchy and meaning that engage users in a deeper experience. Additionally, motion plays a crucial role by directing focus and ensuring smooth continuity through subtle feedback and seamless transitions. As various components appear on the screen, they not only evolve but also reshape the surrounding environment, creating a dynamic interaction that leads to further transformations. This interconnectedness of design elements enhances the overall user experience, making it more immersive and enjoyable.

Mocking serves as an effective method to enhance the readability and maintainability of code during testing. In a series of three articles, I aim to explore the foundational concepts, features, and unique aspects of the MockK library. This innovative open-source library, available on GitHub, is dedicated to simplifying the mocking process in Kotlin. When it comes to property injection, the library first attempts to align properties by their names, followed by matching them based on class or superclass hierarchies. For further customization, users can refer to the lookupType parameter. Notably, property injection continues to function even when private visibility is enforced. Additionally, when selecting constructors for injection, the library prioritizes those with the highest number of arguments, proceeding to those with fewer. This thoughtful design enhances the user experience and flexibility in testing scenarios.

Based on architectural principles, such as Domain-Driven Design (DDD) and Command-Query Responsibility Segregation (CQRS), the Axon Framework provides the building blocks that CQRS requires and helps create scalable and extensible applications while maintaining application consistency in distributed systems.

You can now discover a platform for rapid application development that will accelerate your digital initiatives without vendor dependence, low-code limitations, or usage-based fees. Jmix is a general purpose open architecture that uses a future-proof technology stack and can support multiple digital initiatives throughout the organization. Jmix applications are yours and can be used independently by using an open-source runtime that uses mainstream technologies. With a server-side frontend model and fine-grained access controls, your data is protected. Java and Kotlin developers can be considered full-stack Jmix developers. You don't need separate frontend or backend teams. Visual tools are useful for developers who are new to the platform or have not had much experience. Jmix's data-centric approach makes it easy to migrate legacy applications. Jmix boosts productivity and provides ready-to-use components to help you get the job done.