Alternatives to BMC Compuware Xpediter

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.

Experience the power of CodeRush features immediately and witness their incredible capabilities. With robust support for C#, Visual Basic, and XAML, it offers the fastest .NET testing runner available, state-of-the-art debugging, and an unparalleled coding experience. Effortlessly locate symbols and files within your project and swiftly navigate to relevant code elements based on the current context. CodeRush boasts Quick Navigation and Quick File Navigation functionalities, streamlining the process of finding symbols and accessing files. Additionally, the Analyze Code Coverage feature enables you to identify which sections of your solution are safeguarded by unit tests, highlighting areas that may be vulnerable within your application. The Code Coverage window provides a detailed view of the percentage of statements covered by unit tests across each namespace, type, and member in your solution, empowering you to enhance your code quality effectively. By utilizing these features, you can significantly elevate your development workflow and ensure better application reliability.

Scout Monitoring is Application Performance Monitoring that shows you what charts cannot. Scout APM is an application performance monitoring tool that helps developers identify and fix performance problems before customers even see them. Scout APM's real-time alerting system, developer-centric interface, and tracing logic, which ties bottlenecks to source code directly, helps you spend less time on debugging, and more time creating great products. With an agent that instrument the dependencies needed at a fraction the overhead, you can quickly identify, prioritize and resolve performance issues - memory bloats, N+1 queries and slow database queries. Scout APM monitors Ruby, PHP and Python applications.

OpenCppCoverage is a free and open-source tool designed for measuring code coverage in C++ applications on Windows platforms. Primarily aimed at enhancing unit testing, it also aids in identifying executed lines during program debugging. The tool is compatible with compilers that generate program database files (.pdb) and allows users to execute their programs without the need for recompilation. Users can exclude specific lines based on regular expressions, and it offers coverage aggregation, enabling the merging of multiple coverage reports into a singular comprehensive document. It requires Microsoft Visual Studio 2008 or newer, including the Express edition, although it may also function with earlier versions of Visual Studio. Furthermore, tests can be conveniently run through the Test Explorer window, streamlining the testing process for developers. This versatility makes OpenCppCoverage a valuable asset for those focused on maintaining high code quality.

Xdebug is a powerful PHP extension that enhances the development workflow by offering various tools and functionalities. It allows developers to step through code in their integrated development environment as scripts run, making debugging much easier. The extension provides an enhanced version of the var_dump() function and delivers stack traces for notices, warnings, errors, and exceptions, clearly indicating the path leading to issues. Additionally, it logs all function calls, including arguments and their locations, to the disk, and can be configured to also record every variable assignment and return value for each function. This feature set enables developers, with the aid of visualization tools, to thoroughly examine the performance of their PHP applications and identify any bottlenecks. Moreover, Xdebug reveals the sections of code that are executed during unit testing with PHPUnit, aiding in better test coverage. For convenience, installing Xdebug via a package manager is typically the quickest method; simply replace the PHP version with the version you are currently using. You can also install Xdebug using PECL on both Linux and macOS, utilizing Homebrew for a streamlined setup process. Overall, Xdebug significantly enhances PHP development by providing essential debugging tools and performance insights.

Debugging should be straightforward, and AQTime Pro transforms intricate memory and performance data into clear, actionable insights, allowing for rapid identification of bugs and their underlying causes. While the process of locating and resolving unique bugs can often be laborious and complex, AQTime Pro simplifies this task significantly. With a suite of over a dozen profilers, it enables you to detect memory leaks, performance issues, and code coverage deficiencies with just a few clicks. This powerful tool empowers developers to eliminate all types of bugs efficiently, helping them return their focus to producing high-quality code. Don’t let code profiling tools limit you to a single codebase or framework, which can hinder your ability to uncover performance issues, memory leaks, and code coverage gaps specific to your project. AQTime Pro stands out as the versatile solution that can be employed across various codebases and frameworks within a single project. Its extensive language support includes popular programming languages such as C/C++, Delphi, .NET, Java, and more, making it an invaluable asset for diverse development environments. With AQTime Pro at your disposal, you can streamline your debugging process and enhance your coding efficiency like never before.

SourceDebug is a robust and efficient project-focused programming editor, code explorer, and debugging tool designed to enhance your understanding of code as you work and strategize. It features integrated dynamic analysis for languages such as C/C++ and Objective-C, making it versatile for various coding tasks. With SourceDebug, you can debug applications even when the source code is stored in different locations, ensuring flexibility in your workflow. The application seamlessly combines editing, browsing, compiling, and debugging functionalities for both local and remote projects. This tool is particularly useful for rapidly familiarizing yourself with an existing codebase, enabling a smooth transition to new projects. SourceDebug thoroughly analyzes your project, allowing for effortless navigation and code editing. You can quickly jump to variables, functions, or included files, enhancing productivity. The Smart Bookmark feature is a standout, as it records your browsing position for easy access later. Additionally, it supports debugging through GDB or LLDB-MI over various protocols such as SSH, ADB, Telnet, Rlogin, and Local Cygwin, with GDB server debugging also available. Users can show Quickwatch, Watches, Callstack, Variables, Memory, Breakpoint List, Disassemble, and Thread List as necessary. Furthermore, SourceDebug supports various storage solutions, including SFTP, FTP, and local drives, making it a comprehensive tool for developers. This versatility empowers programmers to tackle complex projects with ease and efficiency.

IDA Pro serves as a powerful disassembler that generates execution maps to represent the binary instructions executed by the processor in a symbolic format, specifically assembly language. With the implementation of advanced techniques, IDA Pro is able to translate machine-executable code into assembly language source code, enhancing the readability of complex code. Additionally, its debugging feature incorporates dynamic analysis, allowing it to support various debugging targets and manage remote applications effectively. The tool's cross-platform debugging capabilities facilitate immediate debugging and provide easy connections to both local and remote processes, while also accommodating 64-bit systems and various connection options. Furthermore, IDA Pro empowers human analysts by allowing them to override its decisions or provide hints, ensuring a more intuitive and efficient analysis of binary code. This flexibility significantly enhances the analyst's ability to interact with the disassembler, making the process of analyzing intricate binaries not only more manageable but also more effective overall.

GNU DDD serves as a graphical interface for various command-line debuggers, including GDB, DBX, WDB, and others like Ladebug and JDB, among others. In addition to standard front-end capabilities like displaying source code, DDD is particularly renowned for its interactive graphical representation of data, which allows users to visualize data structures as graphs. Supporting the ideals of software freedom can be achieved by purchasing items from the FSF shop. To utilize DDD effectively, you must have the GNU debugger (GDB) version 4.16 or newer, though depending on the specific program being debugged, alternative command-line debuggers may also be required. DDD not only enhances the debugging experience but also encourages users to engage with the principles of open-source software.

Coverage.py serves as a powerful utility for assessing the code coverage of Python applications. It tracks the execution of your program, recording which segments of the code have been activated, and subsequently reviews the source to pinpoint areas that could have been executed yet remained inactive. This measurement of coverage is primarily utilized to evaluate the efficacy of testing efforts. It provides insights into which portions of your code are being tested and which are left untested. To collect data, you can use the command `coverage run` to execute your test suite. Regardless of how you typically run your tests, you can incorporate coverage by executing your test runner with the coverage tool. If the command for your test runner begins with "python," simply substitute the initial "python" with "coverage run." To restrict coverage evaluation to only the code within the current directory and to identify files that have not been executed at all, include the source parameter in your coverage command. By default, Coverage.py measures line coverage, but it is also capable of assessing branch coverage. Additionally, it provides information on which specific tests executed particular lines of code, enhancing your understanding of test effectiveness. This comprehensive approach to coverage analysis can significantly improve the quality and reliability of your codebase.

TotalView debugging software offers essential tools designed to expedite the debugging, analysis, and scaling of high-performance computing (HPC) applications. This software adeptly handles highly dynamic, parallel, and multicore applications that can operate on a wide range of hardware, from personal computers to powerful supercomputers. By utilizing TotalView, developers can enhance the efficiency of HPC development, improve the quality of their code, and reduce the time needed to bring products to market through its advanced capabilities for rapid fault isolation, superior memory optimization, and dynamic visualization. It allows users to debug thousands of threads and processes simultaneously, making it an ideal solution for multicore and parallel computing environments. TotalView equips developers with an unparalleled set of tools that provide detailed control over thread execution and processes, while also offering extensive insights into program states and data, ensuring a smoother debugging experience. With these comprehensive features, TotalView stands out as a vital resource for those engaged in high-performance computing.

Introducing Xcode 12, which features a fresh design perfectly suited for macOS Big Sur. This version boasts customizable font sizes for the navigator, improved code completion, and innovative document tabs, making the coding experience more efficient and visually appealing. By default, Xcode 12 creates Universal apps that seamlessly run on Macs equipped with Apple Silicon without requiring any code alterations. With its layout tailored for macOS Big Sur, Xcode 12 showcases a navigator sidebar that extends to the top of the window and features distinctly clear toolbar buttons. The larger default font enhances readability, while users can select from various size options to suit their preferences. The introduction of new document tabs simplifies the organization of files within your workspace, allowing for a more structured workflow. This tab model enables users to effortlessly open new tabs with a double-click or keep track of selected files as they navigate. Furthermore, document tabs can be rearranged to form a cohesive set of files, and users have the ability to customize how content is displayed in each tab for optimal efficiency. Overall, Xcode 12 enhances the development experience with its thoughtful design and user-friendly features.

Coco® is a versatile tool designed for measuring code coverage across multiple programming languages. It utilizes automatic instrumentation of source code to assess the coverage of statements, branches, and conditions during testing. When a test suite is executed against this instrumented application, it generates data that can be thoroughly analyzed later. Through this analysis, developers can gain insights into the extent of source code tested, identify gaps in test coverage, determine which additional tests are necessary, and observe changes in coverage over time. Moreover, it helps in pinpointing redundant tests, as well as identifying untested or obsolete code segments. By evaluating the effect of patches on both the code and the overall coverage, Coco provides a comprehensive overview of testing efficacy. It supports various coverage metrics, including statement coverage, branch coverage, and Modified Condition/Decision Coverage (MC/DC), making it adaptable for diverse environments such as Linux, Windows, and real-time operating systems. The tool is compatible with various compilers, including GCC, Visual Studio, and embedded compilers. Users can also choose from different report formats, including text, HTML, XML, JUnit, and Cobertura, to suit their needs. Additionally, Coco can seamlessly integrate with a multitude of build, testing, and continuous integration frameworks, such as JUnit, Jenkins, and SonarQube, enhancing its utility in a developer's workflow. This comprehensive range of features makes Coco an essential asset for any team focused on ensuring high-quality software through effective testing practices.

The JCov open-source initiative is designed to collect quality metrics related to the development of test suites. By making JCov accessible, the project aims to enhance the verification of regression test executions within OpenJDK development. The primary goal of JCov is to ensure transparency regarding test coverage metrics. Promoting a standard coverage tool like JCov benefits OpenJDK developers by providing a code coverage solution that evolves in harmony with advancements in the Java language and VM. JCov is entirely implemented in Java and serves as a tool to assess and analyze dynamic code coverage for Java applications. It offers features that measure method, linear block, and branch coverage, while also identifying execution paths that remain uncovered. Additionally, JCov can annotate the program's source code with coverage data. From a testing standpoint, JCov is particularly valuable for identifying execution paths and understanding how different pieces of code are exercised during testing. This detailed insight helps developers enhance their testing strategies and improve overall code quality.

OneTest Embedded simplifies the automation of creating and deploying component test harnesses, test stubs, and test drivers with ease. With just a single click from any development environment, users can profile memory usage and performance, evaluate code coverage, and visualize how programs execute. This tool also enhances proactive debugging, helping developers identify and rectify code issues before they escalate into failures. It fosters a continuous cycle of test generation by executing, reviewing, and enhancing tests to quickly achieve comprehensive coverage. Building, executing on the target, and generating reports takes only one click, which is essential in preventing performance problems and application crashes. Furthermore, OneTest Embedded can be customized to accommodate unique memory management techniques prevalent in embedded software. It also provides insights into thread execution and switching, which is crucial for gaining a profound understanding of the system's operational behavior under testing conditions. Ultimately, this powerful tool streamlines testing processes and enhances software reliability.

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.

Testwell CTC++ is an advanced tool that focuses on instrumentation-based code coverage and dynamic analysis specifically for C and C++ programming languages. By incorporating additional components, it can also extend its functionality to languages such as C#, Java, and Objective-C. Moreover, with further add-ons, CTC++ is capable of analyzing code on a wide range of embedded target machines, including those with very limited resources, such as minimal memory and lacking an operating system. This tool offers various coverage metrics, including Line Coverage, Statement Coverage, Function Coverage, Decision Coverage, Multicondition Coverage, Modified Condition/Decision Coverage (MC/DC), and Condition Coverage. As a dynamic analysis tool, it provides detailed execution counters, indicating how many times each part of the code is executed, which goes beyond simple executed/not executed data. Additionally, users can utilize CTC++ to assess function execution costs, typically in terms of time taken, and to activate tracing for function entry and exit during testing phases. The user-friendly interface of CTC++ makes it accessible for developers seeking efficient analysis solutions. Its versatility and comprehensive features make it a valuable asset for both small and large projects.

Seagence's unique execution pathway technology, combined with machine learning, allows you to receive realtime alerts that pinpoint the root cause of any defects in your Java production applications. You can fix your code without any debugging. When you start your application, attach a lightweight runtime Java agent. Seagence agent tracks data about how requests are processed as users access the application. Seagence needs to have enough sample for analysis within 24 hours. Seagence's analytics engine receives the data in realtime. It detects defects and alerts when they occur. Seagence can uncover all defects in your application, even those that are not obvious. Seagence provides defect and root cause information to help you fix your code. Seagence monitors your production application continuously and finds defects and root causes in real-time. This eliminates the need to debug.

Real-time application debugging is made possible through Google Cloud's Cloud Debugger, which allows developers to examine the current state of an application without the need to pause or hinder its performance. This means that users remain unaffected while you gather information about the call stack and variables at any point in your source code. By utilizing this feature, you can gain insights into how your application behaves in a live environment, enabling you to pinpoint elusive bugs and enhance overall code quality. Furthermore, the ability to analyze live application states can greatly streamline the troubleshooting process, making it easier to maintain robust software.

Defang is a developer-focused platform designed to streamline the development, deployment, and debugging of cloud applications. Utilizing AI-driven tools, Defang empowers developers to quickly evolve their concepts into fully operational applications hosted on their selected cloud services. The platform accommodates various programming languages such as Go, JavaScript, and Python, enabling users to kickstart their projects with example templates or create outlines through natural language instructions. With just a single command, Defang automates the building and deployment processes, managing configurations related to computing, storage, load balancing, networking, logging, and security seamlessly. The Defang Command Line Interface (CLI) enhances user interaction with the platform, providing installation methods through shell scripts, Homebrew, Winget, Nix, or direct downloads. Developers can specify their services using compose.yaml files, which Defang leverages to facilitate application deployment in the cloud. Overall, this platform significantly reduces the complexity traditionally associated with cloud application development, making it more accessible for developers at all skill levels.

Quickly identify performance issues and gain insights into the workings of a complex C/C++ application using Orbit, a standalone profiling and debugging tool designed for both Windows and Linux environments. This tool is specifically engineered to assist developers in comprehending and visualizing the execution flow within intricate applications. By providing an overarching perspective on the internal operations, Orbit enhances the developer's grasp of complex systems, enabling them to swiftly pinpoint performance bottlenecks. The tool seamlessly operates with any C/C++ application, provided it has access to the Pdb file, allowing you to initiate profiling immediately after downloading Orbit. Upon launch, Orbit integrates itself within the target process, hooking into specific functions, and is effective even with highly optimized final or shipping builds. Its sampling feature is particularly beneficial when starting your investigation, as it is fast, reliable, and continuously active. Orbit optimizes the profiling process by combining sampling techniques with dynamic instrumentation, ensuring a more efficient workflow for developers seeking to enhance application performance. Additionally, the ability to visualize execution paths greatly aids in understanding how different components interact within the system.

Unexpected outcomes are a common occurrence in software development. With complete insight into the entire sequence of calls, developers can pinpoint the origins of errors and unexpected results in real time with remarkable accuracy. The discipline of software engineering heavily depends on unit testing to create efficient and production-ready software solutions. LangSmith offers similar capabilities tailored specifically for LLM applications. You can quickly generate test datasets, execute your applications on them, and analyze the results without leaving the LangSmith platform. This tool provides essential observability for mission-critical applications with minimal coding effort. LangSmith is crafted to empower developers in navigating the complexities and leveraging the potential of LLMs. We aim to do more than just create tools; we are dedicated to establishing reliable best practices for developers. You can confidently build and deploy LLM applications, backed by comprehensive application usage statistics. This includes gathering feedback, filtering traces, measuring costs and performance, curating datasets, comparing chain efficiencies, utilizing AI-assisted evaluations, and embracing industry-leading practices to enhance your development process. This holistic approach ensures that developers are well-equipped to handle the challenges of LLM integrations.

Elevate your log management with Honeycomb, a platform designed specifically for contemporary development teams aiming to gain insights into application performance while enhancing log management capabilities. With Honeycomb’s rapid query functionality, you can uncover hidden issues across your system’s logs, metrics, and traces, utilizing interactive charts that provide an in-depth analysis of raw data that boasts high cardinality. You can set up Service Level Objectives (SLOs) that reflect user priorities, which helps in reducing unnecessary alerts and allows you to focus on what truly matters. By minimizing on-call responsibilities and speeding up code deployment, you can ensure customer satisfaction remains high. Identify the root causes of performance issues, optimize your code efficiently, and view your production environment in high resolution. Our SLOs will alert you when customers experience difficulties, enabling you to swiftly investigate the underlying problems—all from a single interface. Additionally, the Query Builder empowers you to dissect your data effortlessly, allowing you to visualize behavioral trends for both individual users and services, organized by various dimensions for enhanced analytical insights. This comprehensive approach ensures that your team can respond proactively to performance challenges while refining the overall user experience.

Real-time error detection and fix suggestions, along with swift and secure refactoring options that allow for easy one-step undo, intelligent code completion, the identification of unused code, and helpful documentation prompts, assist all Go developers—from beginners to seasoned experts—in crafting fast, efficient, and dependable code. Delving into and deciphering team projects, legacy code, or unfamiliar systems can be time-consuming and challenging. GoLand's navigation tools facilitate seamless movement through code by allowing instant transitions to shadowed methods, various implementations, usages, declarations, or interfaces tied to specific types. You can easily navigate between different types, files, or symbols, and assess their usages, all while benefiting from organized grouping by the type of usage. Additionally, integrated tools enable you to run and debug applications effortlessly, as you can write and test your code without needing extra plugins or complex configurations, all within the IDE environment. With a built-in Code Coverage feature, you can ensure that your tests are thorough and comprehensive, preventing any critical areas from being overlooked. This comprehensive set of tools ultimately streamlines the development process and enhances overall productivity.

Developers can track errors and monitor performance to see what is important, find faster solutions, and continuously learn about their applications, from the frontend to backend. Sentry's performance monitoring can help you trace performance issues down to slow database queries and poorly performing api calls. Sentry's application performance monitoring is enhanced by stack traces. Identify performance issues quickly before they cause downtime. To see the entire distributed trace from end to end, you can identify the API call that is not performing well and highlight any errors. Breadcrumbs help you make application development easier by showing you the events that led to the error.

Arm DDT stands out as the premier debugger for servers and high-performance computing (HPC) in research, industry, and educational settings, serving software engineers and scientists who work with C++, C, and Fortran in parallel and threaded environments across both CPUs and GPUs, including those from Intel and Arm. Renowned for its robust capabilities, Arm DDT excels at automatically identifying memory issues and divergent behavior, enabling users to attain exceptional performance across various scales. This versatile tool supports multiple server and HPC architectures, offering seamless cross-platform functionality. Additionally, it provides native parallel debugging for Python applications, ensuring comprehensive support for a range of programming needs. Arm DDT is distinguished by its leading memory debugging features and exceptional support for C++ and Fortran debugging, along with an offline mode that allows for non-interactive debugging sessions. It is also equipped to manage and visualize substantial data sets effectively. Available as a standalone tool or as a component of the Arm Forge debug and profile suite, Arm DDT boasts an intuitive graphical interface that simplifies the process of detecting memory bugs and divergent behaviors across diverse computational scales. This makes it an invaluable resource for engineers and researchers alike, ultimately facilitating the development of high-performance applications.

Open-source and free to use, this tool is compatible across various platforms and caters to all EVM blockchains. The Solidity Debugger Pro (sdbg) is an extension for VS Code that enhances the debugging experience for Solidity projects with a plethora of features. It accommodates all EVM-compatible blockchains, making it simple for developers to debug their smart contracts either locally or through a forked node. Additionally, sdbg offers integrated debugging support specifically designed for the widely-used Hardhat framework, ensuring a seamless development process. With its robust capabilities, sdbg significantly improves the efficiency of debugging in Solidity projects.

Maintain high-quality code while adhering to agile development cycles. Jtest's extensive Java testing tools will ensure that you code flawlessly at every stage of Java software development. Streamline Compliance with Security Standards. Ensure that your Java code conforms to industry security standards. Automated generation of compliance verification documentation Get Quality Software Out Faster Java testing tools can be integrated to detect defects faster and more efficiently. Reduce time and costs by avoiding costly and complicated problems later. Increase your return on unit testing. Create a set of JUnit test suites that are easy to maintain and optimize for code coverage. Smart test execution allows you to get faster feedback from CI as well as within your IDE. Parasoft Jtest integrates seamlessly into your development ecosystem and CI/CD pipeline for real-time, intelligent feedback about your testing and compliance progress.

Allocate your efforts wisely between developing applications and writing corresponding test code. For Java and Groovy, utilizing an advanced code coverage tool is essential, and OpenClover stands out by evaluating code coverage while also gathering over 20 different metrics. This tool highlights the areas of your application that lack testing and integrates coverage data with metrics to identify the most vulnerable sections of your code. Additionally, its Test Optimization feature monitors the relationship between test cases and application classes, allowing OpenClover to execute only the tests pertinent to any modifications made, which greatly enhances the efficiency of test execution time. You may wonder if testing simple getters and setters or machine-generated code is truly beneficial. OpenClover excels in its adaptability, enabling users to tailor coverage measurement by excluding specific packages, files, classes, methods, and even individual statements. This flexibility allows you to concentrate your testing efforts on the most critical components of your codebase. Moreover, OpenClover not only logs the results of tests but also provides detailed coverage analysis for each individual test, ensuring that you have a thorough understanding of your testing effectiveness. Emphasizing such precision can lead to significant improvements in code quality and reliability.

Mayhem is an innovative fuzz testing platform that integrates guided fuzzing with symbolic execution, leveraging a patented technology developed at CMU. This sophisticated solution significantly minimizes the need for manual testing by autonomously detecting and validating defects in software. By facilitating the delivery of safe, secure, and reliable software, it reduces the time, cost, and effort typically required. One of Mayhem's standout features is its capability to gather intelligence about its targets over time; as its understanding evolves, it enhances its analysis and maximizes overall code coverage. Every vulnerability identified is an exploitable and confirmed risk, enabling teams to prioritize their efforts effectively. Furthermore, Mayhem aids in remediation by providing comprehensive system-level insights, including backtraces, memory logs, and register states, which expedite the diagnosis and resolution of issues. Its ability to generate custom test cases in real-time, based on target feedback, eliminates the need for any manual test case creation. Additionally, Mayhem ensures that all generated test cases are readily accessible, making regression testing not only effortless but also a continuous and integral part of the development process. This seamless integration of automated testing and intelligent feedback sets Mayhem apart in the realm of software quality assurance.

NCrunch provides real-time tracking of your code coverage, displaying markers alongside your code for easy identification of areas with high or low coverage. This feature simplifies the process of recognizing coverage distribution across your project. Designed specifically for large and intricate projects, NCrunch has been refined over the past 12 years to accommodate the demands of extensive systems that include millions of lines of code and thousands of tests. It captures a wide array of test-related data, leveraging this information to deliver essential feedback as promptly as possible. The system prioritizes tests that have been affected by your recent code modifications, utilizing advanced IL-based change mapping for optimal performance. Additionally, NCrunch allows for offloading build and testing tasks to other machines, enabling you to distribute the workload across connected systems or even scale up to cloud resources. This collaborative approach facilitates resource sharing among developers, empowering teams to combine their testing capabilities effectively. Ultimately, this innovative functionality enhances the efficiency and productivity of the software development process.

Our platform uses a variety of security techniques, including feedback-based fuzz testing and coverage-guided fuzz testing, in order to generate millions upon millions of test cases that trigger difficult-to-find bugs deep in your application. This white-box approach helps to prevent edge cases and speed up development. Advanced fuzzing engines produce inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Only uncover true vulnerabilities. You will need the stack trace and input to prove that you can reproduce errors reliably every time. AI white-box testing is based on data from all previous tests and can continuously learn the inner workings of your application. This allows you to trigger security-critical bugs with increasing precision.

PHPUnit necessitates the activation of the dom and json extensions, which are typically enabled by default, alongside the pcre, reflection, and spl extensions that are also standard and cannot be disabled without modifying PHP's build system or source code. Additionally, to generate code coverage reports, the Xdebug extension (version 2.7.0 or newer) and the tokenizer extension must be present, while the ability to create XML reports relies on the xmlwriter extension. Writing unit tests is fundamentally a best practice for developers to detect and resolve bugs, refactor code, and provide documentation for a unit of software being tested. Ideally, unit tests should encompass all potential execution paths within a program to maximize effectiveness. Generally, a single unit test is aligned with one specific path in a particular function or method. Nonetheless, it is important to recognize that a test method may not function as a completely isolated or independent unit, as there can often be subtle dependencies between various test methods that stem from the underlying implementation of a test scenario. This interconnectedness can sometimes lead to challenges in maintaining test integrity and reliability.

You can save time and money by finding and fixing problems earlier. You can reduce the time and expense of delivering high quality software by avoiding costly and more complex problems later. Ensure that your C# and VB.NET codes comply with a wide variety of safety and security industry standards. This includes the requirement traceability required and the documentation required for verification. Parasoft's C# tool, Parasoft dotTEST automates a wide range of software quality practices to support your C# or VB.NET development activities. Deep code analysis uncovers reliability issues and security problems. Automated compliance reporting, traceability of requirements, code coverage and code coverage are all key factors in achieving compliance for safety-critical industries and security standards.

Blanket.js is a user-friendly JavaScript code coverage library designed to simplify the installation, usage, and understanding of code coverage metrics. This tool allows for seamless operation or tailored customization to suit specific requirements. By providing code coverage statistics, Blanket.js enhances your current JavaScript tests by indicating which lines of your source code are being tested. It achieves this by parsing the code with Esprima and node-falafel, then adding tracking lines for analysis. The library integrates with test runners to produce coverage reports after test execution. Additionally, a Grunt plugin enables Blanket to function as a traditional code coverage tool, producing instrumented versions of files rather than applying live instrumentation. Blanket.js can also execute QUnit-based reports in a headless manner using PhantomJS, with results shown in the console. Notably, if any predefined coverage thresholds are not satisfied, the Grunt task will fail, ensuring that developers adhere to their quality standards. Overall, Blanket.js serves as an effective solution for developers seeking to maintain high test coverage in their JavaScript applications.

Simplifying JavaScript test coverage is achievable with Istanbul, which enhances your ES5 and ES2015+ code by adding line counters, allowing you to measure how thoroughly your unit tests cover your codebase. The nyc command-line interface complements various JavaScript testing frameworks like tap, mocha, and AVA with ease. By utilizing babel-plugin-Istanbul, first-class support for ES6/ES2015+ is ensured, making it compatible with the most widely used JavaScript testing tools. Additionally, nyc facilitates the instrumentation of subprocesses through its command-line capabilities. Integrating coverage into your mocha tests is a breeze; just prefix your test command with nyc. Furthermore, the instrument command from nyc can be employed to prepare source files outside the scope of your unit tests. When executing a test script, nyc conveniently displays all Node processes that are created during the run. Although nyc defaults to Istanbul's text reporter, you have the flexibility to choose an alternative reporting option that suits your needs. Overall, nyc streamlines the process of achieving comprehensive test coverage for JavaScript applications, allowing developers to ensure higher code quality with minimal effort.

Codase offers a vast repository of open-source code, significantly enhancing accessibility by reaching code that is often tucked away in compressed archives and version control systems, areas where typical search engines struggle to operate efficiently. Moreover, Codase prioritizes high-quality code by ensuring that every single line is meticulously validated and compiled through an advanced source code analysis engine. This company, privately owned and situated in Silicon Valley, was established by Dr. Huihong Luo alongside other industry veterans. Our team consists of forward-thinking and enthusiastic experts with varied technological and business expertise, all boasting impressive track records. We strive to position Codase as the premier search engine for source code, excelling in features, quality, performance, and comprehensive code coverage. Developers may discover Codase to be an invaluable resource, as our principal aim is to enhance your coding efficiency and productivity. Ultimately, we believe that by providing such a robust platform, we can empower developers to achieve more in their coding endeavors.

LuaCov serves as a straightforward coverage analysis tool for Lua scripts. By running a Lua script with the luacov module activated, it produces a statistics file detailing the execution count for each line within the script and its associated modules. This statistics file is then processed by the luacov command-line tool to create a report, enabling users to identify untraversed code paths, which is essential for assessing the thoroughness of a test suite. The tool offers a variety of configuration options, with the default settings found in src/luacov/defaults.lua, representing the global defaults. For those needing project-specific configurations, they can create a Lua script that either sets options as global variables or returns a table containing specific options, saving this file as .luacov in the project directory where luacov is executed. For instance, such a configuration could specify that only the foo module and its associated submodules should be included in the coverage analysis, indicating that these are located within the src directory. This flexibility allows developers to fine-tune their coverage analysis to better align with their project needs.

SimpleCov is a Ruby tool designed for code coverage analysis, leveraging Ruby's native Coverage library to collect data, while offering a user-friendly API that simplifies the processing of results by allowing you to filter, group, merge, format, and display them effectively. Although it excels in tracking the covered Ruby code, it does not support coverage for popular templating systems like erb, slim, and haml. For most projects, obtaining a comprehensive overview of coverage results across various types of tests, including Cucumber features, is essential. SimpleCov simplifies this task by automatically caching and merging results for report generation, ensuring that your final report reflects coverage from all your test suites, thus providing a clearer picture of any areas that need improvement. It is important to ensure that SimpleCov is executed in the same process as the code for which you wish to analyze coverage, as this is crucial for accurate results. Additionally, utilizing SimpleCov can significantly enhance your development workflow by identifying untested code segments, ultimately leading to more robust applications.

Rookout is a live data collection platform and debugging platform that allows software engineers to understand any application, no matter where it is running. This includes monolithic applications to cloud native ones. Rookout enables engineers to reduce debugging time and log time by 80%. This allows them to solve customer problems 5x faster. Software engineers can access the data they need instantly with Non-Breaking Breakpoints. This is without any additional coding, restarts or redeployment. Developers can extract the data they need from any line of code. This makes it easier to collaborate and facilitate handoffs.

DeepSource streamlines the process of identifying and resolving code issues during reviews, including risks of bugs, anti-patterns, performance bottlenecks, and security vulnerabilities. Setting it up with your Bitbucket, GitHub, or GitLab account takes under five minutes, making it incredibly convenient. It supports various programming languages such as Python, Go, Ruby, and JavaScript. Additionally, DeepSource encompasses all essential programming languages, Infrastructure-as-Code capabilities, secret detection, code coverage, and much more. This means you can rely solely on DeepSource for code protection. Initiate your development with the most advanced static analysis platform, ensuring that you catch bugs before they make their way into production. It boasts the largest array of static analysis rules available in the market. Your team will benefit from having a centralized location to monitor and address code health effectively. With DeepSource, code formatting can be automated, ensuring your CI pipeline remains intact without style violations disrupting the process. Furthermore, it can automatically generate and implement fixes for detected issues with just a few clicks, enhancing your team's productivity and efficiency.

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.

Inspector is a powerful tool designed for monitoring code execution, assisting software developers in the automatic detection of errors and performance bottlenecks. It efficiently traces applications regardless of their scale, allowing developers to address issues proactively before they impact customers, all while maintaining predictable and low debugging costs. By using Inspector, teams can enhance their development process and ensure a smoother user experience.

Create dependable and optimized code that delivers accurate results across various Server and HPC architectures, utilizing the latest compilers and C++ standards tailored for Intel, 64-bit Arm, AMD, OpenPOWER, and Nvidia GPU platforms. Arm Forge integrates Arm DDT, a premier debugger designed to streamline the debugging process of high-performance applications, with Arm MAP, a respected performance profiler offering essential optimization insights for both native and Python HPC applications, along with Arm Performance Reports that provide sophisticated reporting features. Both Arm DDT and Arm MAP can also be used as independent products, allowing flexibility in application development. This package ensures efficient Linux Server and HPC development while offering comprehensive technical support from Arm specialists. Arm DDT stands out as the preferred debugger for C++, C, or Fortran applications that are parallel or threaded, whether they run on CPUs or GPUs. With its powerful and user-friendly graphical interface, Arm DDT enables users to swiftly identify memory errors and divergent behaviors at any scale, solidifying its reputation as the leading debugger in the realms of research, industry, and academia, making it an invaluable tool for developers. Additionally, its rich feature set fosters an environment conducive to innovation and performance enhancement.

Thanks to a comprehensive array of tools and APIs available from leading cloud providers, developing services in Go has never been more accessible. The language's extensive open-source libraries, combined with its powerful standard library, make it ideal for crafting swift and sophisticated command-line interfaces. Go's exceptional memory management and compatibility with multiple integrated development environments enhance its capability to drive rapid and scalable web applications. With quick compilation times and a clean syntax, along with built-in formatting and documentation tools, Go is tailored to meet the needs of both DevOps professionals and site reliability engineers. This is a deep dive into everything related to Go. Whether you are embarking on a fresh project or looking to refine your existing Go skills, there’s a structured interactive introduction that is divided into three parts. Each part offers practical exercises to reinforce your understanding, and the Playground feature allows users to write Go code directly in a browser, which is then compiled, linked, and executed on our servers instantly. This hands-on approach makes learning Go not only effective but also enjoyable.