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Description
Having the most skilled developers isn't enough if testing processes are hindering their progress; in fact, a staggering 80% of your software tests may be ineffective. The challenge lies in identifying which 80% is truly unnecessary. We utilize your data to pinpoint the essential 20%, enabling you to accelerate your release process. Our predictive test selection tool, inspired by machine learning techniques employed by leading companies like Facebook, is designed for easy adoption by any organization. We accommodate a variety of programming languages, test frameworks, and continuous integration systems—just integrate Git into your workflow. Launchable employs machine learning to evaluate your test failures alongside your source code, sidestepping traditional code syntax analysis. This flexibility allows Launchable to effortlessly extend its support to nearly any file-based programming language, ensuring it can adapt to various teams and projects with differing languages and tools. Currently, we provide out-of-the-box support for languages including Python, Ruby, Java, JavaScript, Go, C, and C++, with a commitment to continually expand our offerings as new languages emerge. In this way, we help organizations streamline their testing process and enhance overall efficiency.
Description
RKTracer is a sophisticated tool designed for code coverage and test analysis, allowing development teams to evaluate the thoroughness and effectiveness of their testing efforts across various stages, including unit, integration, functional, and system-level testing, all without needing to modify any existing application code or build process. This versatile tool is capable of instrumenting a wide range of environments, including host machines, simulators, emulators, embedded systems, and servers, while supporting a diverse set of programming languages such as C, C++, CUDA, C#, Java, Kotlin, JavaScript/TypeScript, Golang, Python, and Swift. RKTracer offers comprehensive coverage metrics, providing insights into function, statement, branch/decision, condition, MC/DC, and multi-condition coverage, along with the capability to generate delta-coverage reports that highlight newly added or altered code segments that are already under test. The integration of RKTracer into development workflows is straightforward; by simply prefixing the build or test command with “rktracer,” users can execute their tests and subsequently produce detailed HTML or XML reports suitable for CI/CD systems or integration with dashboards like SonarQube. Ultimately, RKTracer empowers teams to enhance their testing practices and improve overall software quality effectively.
API Access
Has API
API Access
Has API
Integrations
Android
Apple iOS
Bitbucket
C++
Cucumber
Cypress
GitHub
GitLab
HTML
JUnit
Integrations
Android
Apple iOS
Bitbucket
C++
Cucumber
Cypress
GitHub
GitLab
HTML
JUnit
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Launchable
Country
United States
Website
www.launchableinc.com
Vendor Details
Company Name
RKVALIDATE
Founded
2020
Country
India
Website
www.rkvalidate.com/code-coverage-tool
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Software Testing
Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing
