Sahi Pro
Sahi Pro is a suite automation tools for web, Web-services, Windows desktop and Java applications.
Sahi Pro features include automatic waits, recorders and accessor spy, inbuilt frame and editor, parallel playback, automatic reporting, automatic logging, and reporting. Also, Sahi Pro can save 70% of the time and effort that is normally spent on test automation.
Sahi Pro has been trusted by more than 400 companies around the world and is quickly becoming the preferred tool for test automation in the agile world.
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Kinde
Authentication is a pivotal moment in your customer's journey. With Kinde, you can take full control. We provide passwordless authentication, social logins, and enterprise SSO to give your users flexible, secure access. You can fully customize the UI with your own designs and domains, ensuring a seamless, on-brand experience. For complex needs, our powerful workflows let you run custom code during authentication. Plus, you can easily organize business customers using our organizations feature, allowing you to fine-tune the experience for each one.
Beyond authentication, Kinde helps you monetize your business quickly. You can effortlessly create subscription plans and collect revenue. Our platform is built to support B2C, B2B, and B2B2C business models, with robust organization management and flexible billing logic that scales as you grow.
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Google ClusterFuzz
ClusterFuzz serves as an expansive fuzzing framework designed to uncover security vulnerabilities and stability flaws in software applications. Employed by Google, it is utilized for testing all of its products and acts as the fuzzing engine for OSS-Fuzz. This infrastructure boasts a wide array of features that facilitate the seamless incorporation of fuzzing into the software development lifecycle. It offers fully automated processes for bug filing, triaging, and resolution across multiple issue tracking systems. The system supports a variety of coverage-guided fuzzing engines, optimizing results through ensemble fuzzing and diverse fuzzing methodologies. Additionally, it provides statistical insights for assessing fuzzer effectiveness and monitoring crash incidence rates. Users can navigate an intuitive web interface that simplifies the management of fuzzing activities and crash reviews. Furthermore, ClusterFuzz is compatible with various authentication systems via Firebase and includes capabilities for black-box fuzzing, minimizing test cases, and identifying regressions through bisection. In summary, this robust tool enhances software quality and security, making it invaluable for developers seeking to improve their applications.
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Fuzzing Project
Fuzzing serves as an effective method for identifying software bugs. Essentially, it involves generating numerous randomly crafted inputs for the software to process in order to observe the outcomes. When a program crashes, it usually indicates that there is a problem. Despite being a widely recognized approach, it is often surprisingly straightforward to uncover bugs, including those with potential security risks, in commonly used software. Memory access errors, especially prevalent in programs developed in C/C++, tend to be the most frequently identified issues during fuzzing. While the specifics may vary, the underlying problem is typically that the software accesses incorrect memory locations. Modern Linux or BSD systems come equipped with a variety of fundamental tools designed for file display and parsing; however, most of these tools are ill-equipped to handle untrusted inputs in their present forms. Conversely, we now possess advanced tools that empower developers to detect and investigate these vulnerabilities more effectively. These innovations not only enhance security but also contribute to the overall stability of software systems.
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