Best Code Quality Tools for Small Business

Aikido is the all-in-one security platform for development teams to secure their complete stack, from code to cloud. Aikido centralizes all code and cloud security scanners in one place. Aikido offers a range of powerful scanners including static code analysis (SAST), dynamic application security testing (DAST), container image scanning, and infrastructure-as-code (IaC) scanning. Aikido integrates AI-powered auto-fixing features, reducing manual work by automatically generating pull requests to resolve vulnerabilities and security issues. It also provides customizable alerts, real-time vulnerability monitoring, and runtime protection, enabling teams to secure their applications and infrastructure seamlessly.

Security Solutions for Your DevOps Process Automate scanning your code to find and fix vulnerabilities. Kiuwan Code Security is compliant with the strictest security standards, such OWASP or CWE. It integrates with top DevOps tools and covers all important languages. Static application security testing and source analysis are both effective, and affordable solutions for all sizes of teams. Kiuwan provides a wide range of essential functionality that can be integrated into your internal development infrastructure. Quick vulnerability detection: Simple and quick setup. You can scan your area and receive results in minutes. DevOps Approach to Code Security: Integrate Kiuwan into your Ci/CD/DevOps Pipeline to automate your security process. Flexible Licensing Options. There are many options. One-time scans and continuous scanning. Kiuwan also offers On-Premise or Saas models.

Codespy AI Detector offers a comprehensive solution to detect AI-generated source code across multiple widely-used programming languages, including Python, Java, C#, and JavaScript. This tool pinpoints code written by advanced AI systems such as ChatGPT and Claude, which may inadvertently introduce vulnerabilities or bugs in software. By highlighting these AI-originated segments, Codespy empowers development teams to review and correct potential issues before deployment. The detector integrates with popular tools like Visual Studio Code and even functions as a plugin for ChatGPT, streamlining the identification process. Companies can use Codespy to establish safe AI coding standards and manage innovation without sacrificing security. Its pricing is flexible, ranging from a free tier with limited scans to plans suited for small businesses and enterprises. Users worldwide rely on Codespy for its high accuracy and user-friendly interface. No credit card is needed to start using the free version, making it easy for teams to begin improving their AI code oversight immediately.

CppDepend serves as a robust code analysis solution specifically designed for C and C++ programming languages, aimed at aiding developers in the upkeep of intricate code repositories. It boasts an extensive array of functionalities that promote code quality, including static code analysis, which plays a critical role in uncovering potential coding problems like memory leaks, suboptimal algorithms, and breaches of coding conventions. One of CppDepend's significant features is its adherence to established coding standards such as Misra, CWE, CERT, and Autosar. These guidelines are essential across various sectors, especially in the creation of dependable and secure software for automotive, embedded, and other high-reliability environments. By conforming to these standards, CppDepend contributes to the assurance that the code meets industry-specific safety and reliability benchmarks. Additionally, the tool's seamless integration with widely-used development environments, along with its compatibility with continuous integration processes, positions it as an indispensable resource in agile development practices. This versatility enables teams to enhance their productivity while ensuring adherence to high-quality coding standards throughout the software development lifecycle.

SonarQube Server serves as a self-hosted solution for ongoing code quality assessment, enabling development teams to detect and address bugs, vulnerabilities, and code issues in real time. It delivers automated static analysis across multiple programming languages, ensuring that the highest standards of quality and security are upheld throughout the software development process. Additionally, SonarQube Server integrates effortlessly with current CI/CD workflows, providing options for both on-premise and cloud deployments. Equipped with sophisticated reporting capabilities, it assists teams in managing technical debt, monitoring progress, and maintaining coding standards. This platform is particularly well-suited for organizations desiring comprehensive oversight of their code quality and security while maintaining high performance levels. Furthermore, SonarQube fosters a culture of continuous improvement within development teams, encouraging proactive measures to enhance code integrity over time.

ThinkReview is an innovative code-review solution powered by AI, designed specifically for developers utilizing GitLab and Azure DevOps, providing immediate assessments of merge requests and pull requests directly within the web interface. It eliminates the need for intricate setup or configuration by automatically recognizing when a MR/PR is being viewed, retrieving the relevant code changes, and presenting an AI-generated review panel that features concise summaries, security alerts, quality recommendations, and automatically generated comments. Users can interact in a conversational manner with the code modifications, pose inquiries, regenerate review insights, and get insightful follow-up questions to facilitate deeper discussions. It accommodates both self-hosted and cloud-based environments, operates seamlessly out of the box, and comes as a browser extension with functionalities like automatic MR/PR detection, intelligent summaries, comment creation, and support for multiple languages. Prioritizing efficiency and user-friendliness, ThinkReview aims to enhance code quality and speed up review processes by integrating AI into the developers’ existing workflows, ultimately fostering a more productive coding environment. By streamlining the code review process, it empowers teams to maintain high standards while accelerating development timelines.

Amazon CodeGuru is an advanced developer tool that leverages machine learning to offer insightful suggestions for enhancing code quality and pinpointing the most costly lines of code within an application. By seamlessly incorporating Amazon CodeGuru into your current software development processes, you can benefit from integrated code reviews that highlight and optimize costly code segments, ultimately leading to cost savings. Additionally, Amazon CodeGuru Profiler assists developers in identifying the most expensive lines of code, providing detailed visualizations and actionable advice for optimizing performance and reducing expenses. Furthermore, the Amazon CodeGuru Reviewer employs machine learning techniques to detect significant issues and elusive bugs during the development phase, thereby elevating the overall quality of the codebase while facilitating more efficient application development. This powerful combination of tools ensures that developers not only write better code but also maintain a focus on cost efficiency throughout the software lifecycle.

Deliver high-quality code by systematically reviewing it, engaging in discussions about modifications, sharing insights, and detecting issues across various version control systems like SVN, Git, Mercurial, CVS, and Perforce. Establish structured, workflow-oriented, or rapid code reviews while designating reviewers from your team to enhance collaboration. Transform any code review into a dynamic conversation by commenting on particular lines of code, files, or entire changesets. Prioritize important actions with consolidated views of your coding activities, including commits, reviews, and comments. Utilize data to elevate code quality by identifying sections of your codebase that may lack adequate review. Obtain a snapshot of the review status to track potential delays caused by pending reviews. Maintain a thorough audit trail that encapsulates all details of code reviews, including the historical context of each review. Tailor your Jira Software workflow to ensure it halts if any reviews are still in progress. Enhance your development processes by integrating Jira Software with Bitbucket Server, Bamboo, and a multitude of additional developer tools, thus streamlining the entire code management lifecycle. This integration facilitates more efficient collaboration and fosters a culture of continuous improvement within your development team.

Proactively discover, predict, and resolve errors with the continuous code improvement platform.

CodeScene's powerful features go beyond traditional code analysis. Visualize and evaluate all the factors that influence software delivery and quality, not just the code itself. Make informed, data-driven decisions based on CodeScene’s actionable insights and recommendations. CodeScene guides developers and technical leaders to: - Get a holistic overview and evolution of your software system in one single dashboard. - Identify, prioritize, and tackle technical debt based on return on investment. - Maintain a healthy codebase with powerful CodeHealth™ Metrics, spend less time on rework and more time on innovation. - Seamlessly integrate with Pull Requests and editors, get actionable code reviews and refactoring recommendations. - Set Improvement goals and quality gates for teams to work towards while monitoring the progress. - Support retrospectives by identifying areas for improvement. - Benchmark performance against personalized trends. - Understand the social side of the code, measure socio-technical factors like key personnel dependencies, knowledge sharing and inter-team coordination.

Visual Expert is a static code analyzer for Oracle PL/SQL, SQL Server T-SQL and PowerBuilder. It identifies code dependencies to let you modify the code without breaking your application. It also scans your code to detect security flaws, quality, performance and maintenability issues. Identify breaking changes with impact analysis. Scan the code to find security vulnerabilities, bugs and maintenance issues. Integrate continuous code inspection in a CI workflow. Understand the inner workings and document your code with call graphs, code diagrams, CRUD matrices, and object dependency matrices (ODMs). Automatically generate source code documentation in HTML format. Navigate your code with hyperlinks. Compare two pieces of code, databases or entire applications. Improve maintainability. Clean up code. Comply with development standards. Analyze and improve database code performance: Find slow objects and SQL queries, optimize a slow object, a call chain, a slow SQL query, display a query execution plan.

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.

Unit testing made simple: You can write tests without modifying your existing code, including legacy systems. This applies to static methods, private methods, non-virtual methods, out parameters, and even class members and fields. Our professional edition is available at no cost for developers globally, alongside options for paid support packages. By enhancing your code integrity, you can consistently produce high-quality code. You can create entire object models with just a single command, enabling you to mock static methods, private methods, constructors, events, LINQ queries, reference arguments, and more, whether they are live or future elements. The automated test suggestion feature tailors recommendations specifically for your code, while our intelligent test runner efficiently executes only the tests that are impacted, providing you with rapid feedback. Additionally, our coverage tool allows you to visualize your code coverage directly in your editor as you develop, ensuring that you keep track of your testing progress. This comprehensive approach not only saves time but also significantly enhances the reliability of your software.

If you think your Git repositories deserve the best, you should absolutely get Gitfox. This lightweight Git client has been written exclusively for macOS and definitely looks like it belongs here. Use one coherent interface to make sense of your repository, improve your code quality and commit faster! Superior Diffs Know what's changed — don't guess. Inline Changes are highlighted to take the guesswork out of your diffs. Image Diffs help you make sure the correct assets go into your project. Line Staging breaks your work down into smaller steps. Only commit what you want to.

Discover an innovative approach to assess technical debt and code quality that caters to both engineering executives and non-technical managers alike. By harnessing the latent capabilities of your team, you can gain crucial insights that enhance product delivery. With Duecode, you remain in sync with your team’s progress, receiving up-to-the-minute information about software quality and identifying your top contributors. This platform provides essential visibility into each developer's workflow and highlights potential vulnerabilities in your project's code. You don't need any technical background to grasp the intricacies of your project’s performance. Through the analysis of an impressive 2.5 billion lines of code and 172,000 repositories, we have distilled code quality into a simple letter ranking system. Enhance the transparency of your project's technical debt with Duecode, enabling you to identify challenges early and address them effectively. Additionally, maintain your codebase's integrity by pinpointing excessive commits and averting disarray within your code structure. By adopting this proactive approach, your team can ensure sustained software excellence and innovation.

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.

This module offers metrics for code coverage specifically tailored for Perl, highlighting the extent to which tests engage with the code. By utilizing Devel::Cover, users can identify sections of their code that remain untested and decide on additional tests necessary to enhance coverage. Essentially, code coverage serves as a proxy indicator of software quality. Devel::Cover has reached a commendable level of stability, incorporating an array of features typical of effective coverage tools. It provides detailed reports on statement, branch, condition, subroutine, and pod coverage. Generally, the data on statement and subroutine coverage is reliable, while branch and condition coverage may not always align with expectations. For pod coverage, it leverages Pod::Coverage, and if Pod::Coverage::CountParents is accessible, it will utilize that for more comprehensive insights. Overall, Devel::Cover stands out as an essential tool for Perl developers seeking to improve their code's robustness through better testing practices.

Tarpaulin serves as a tool for reporting code coverage specifically designed for the cargo build system, drawing its name from a durable cloth typically employed to protect cargo on ships. At present, it effectively provides line coverage, though it may still exhibit some minor inaccuracies in its output. Significant efforts have been made to enhance its compatibility across various projects, yet unique combinations of packages and build configurations can lead to potential issues, so users are encouraged to report any discrepancies they encounter. Additionally, the roadmap offers insights into upcoming features and improvements. On Linux systems, Tarpaulin utilizes Ptrace as its default tracing backend, which is limited to x86 and x64 architecture; however, this can be switched to llvm coverage instrumentation by specifying the engine as llvm, which is the default method on Mac and Windows platforms. Furthermore, Tarpaulin can be deployed in a Docker environment, making it a practical solution for users who prefer not to run Linux directly but still wish to utilize its capabilities locally. This versatility makes Tarpaulin a valuable tool for developers looking to improve their code quality through effective coverage analysis.

Coverage offers tools for gathering, processing, and formatting coverage data specifically for Dart. The function Collect_coverage retrieves coverage information in JSON format from the Dart VM Service, while format_coverage transforms this JSON coverage data into either the LCOV format or a more readable, pretty-printed layout for easier interpretation. This set of tools enhances the ability to analyze code coverage effectively.

To create test coverage reports for Xcode projects and integrate them into your continuous integration (CI) system, make sure to activate the coverage feature by checking the "Gather coverage data" option while modifying the scheme settings. This setup will help you track code quality and ensure that your tests effectively cover the necessary parts of your application, streamlining your development process.

NCover Desktop is a Windows-based tool designed to gather code coverage data for .NET applications and services. Once the coverage data is collected, users can view comprehensive charts and metrics through a browser interface that enables detailed analysis down to specific lines of source code. Additionally, users have the option to integrate a Visual Studio extension known as Bolt, which provides integrated code coverage features, showcasing unit test outcomes, execution times, branch coverage visualization, and highlighted source code directly within the Visual Studio IDE. This advancement in NCover Desktop significantly enhances the accessibility and functionality of code coverage solutions. By measuring code coverage during .NET testing, NCover offers insights into which parts of the code were executed, delivering precise metrics on unit test coverage. Monitoring these statistics over time allows developers to obtain a reliable gauge of code quality throughout the entire development process, ultimately leading to a more robust and well-tested application. By utilizing such tools, teams can ensure a higher standard of software reliability and performance.

JaCoCo, a free Java code coverage library developed by the EclEmma team, has been refined through years of experience with existing libraries. The master branch of JaCoCo is built and published automatically, ensuring that each build adheres to the principles of test-driven development and is therefore fully functional. For the most recent features and bug fixes, users can consult the change history. Additionally, the SonarQube metrics assessing the current JaCoCo implementation can be found on SonarCloud.io. It is possible to integrate JaCoCo seamlessly with various tools and utilize its features right away. Users are encouraged to enhance the implementation and contribute new functionalities. While there are multiple open-source coverage options available for Java, the development of the Eclipse plug-in EclEmma revealed that most existing tools are not well-suited for integration. A significant limitation is that many of these tools are tailored to specific environments, such as Ant tasks or command line interfaces, and lack a comprehensive API for embedding in diverse contexts. Furthermore, this lack of flexibility often hinders developers from leveraging coverage tools effectively across different platforms.

Conducting runtime code reviews for every change made in the code editor and during continuous integration (CI) helps identify performance, security, and stability issues before deployment. This proactive approach ensures that problems are addressed while coding, preventing them from reaching production. Team members can collaborate to troubleshoot application behavior without needing to replicate each other's development environments. CI can automate the generation of AppMaps, providing alerts for performance and security vulnerabilities, while also allowing for comparisons of observability and alerts across different branches and teams. By integrating AppMap into CI, developers can automate observability, generate OpenAPI documentation, and accomplish much more. Furthermore, AppMap code reviews provide access to comprehensive resources that aid in identifying the root causes of any unexpected behavior. The use of sequence diagram diffs effectively illustrates changes in behavior within the code, offering a clear visual representation of modifications and their impact. This process not only enhances code quality but also fosters better communication and understanding among team members.

Step away from the hassle of writing essays, as Squire effortlessly generates pull request descriptions on your behalf. This tool ensures your team remains aligned through concise descriptions and comprehensive changelogs. With an efficient workflow, Squire engages your team in reviewing PRs while providing them with complete context from your codebase. It excels at identifying various issues, including significant breaking changes, security vulnerabilities, and even minor typographical errors. By enhancing code quality, Squire facilitates a smoother transition of your PRs into production. As a context-sensitive agent, Squire collaborates with you to craft descriptions, evaluate PRs, and adapt to your preferred review style. It not only understands your team's reviewing habits but also customizes its approach through explicit settings and by learning from your team's interactions. Furthermore, it helps to delineate and organize ownership and accountability throughout your entire engineering infrastructure, while ensuring compliance by implementing and upholding regulations on your engineering elements. Ultimately, Squire is your partner in achieving a more streamlined and efficient development process.

Access immediate code evaluations from qualified engineers, augmented by AI technology. Each time you initiate a pull request, you can seamlessly integrate senior engineers into your workflow. Accelerate the delivery of superior, secure code with the support of AI-driven code assessments. Whether your development team comprises 5 or 5,000 members, PullRequest will elevate your code review system and tailor it to suit your requirements. Our expert reviewers assist in identifying security threats, uncovering concealed bugs, and addressing performance challenges prior to deployment. This entire process is integrated into your current tools for maximum efficiency. Our seasoned reviewers, bolstered by AI analysis, can target critical security vulnerabilities effectively. We employ advanced static analysis that incorporates both open-source resources and proprietary AI, providing reviewers with enhanced insights. Allow your senior personnel to focus on strategic initiatives while making substantial strides in resolving issues and refining code, even as other team members continue to develop. With this innovative approach, your team can maintain productivity while ensuring code quality.