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QualityGate 2.2 to be released in September
As per the development roadmap, the next release of QualityGate will contain the following new features...
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QualityGate 2.1.0 is in the tube
QualityGate 2.1.0 coming soon with AI-based CodeAdvisor, Github integration, and JavaScript support!
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QualityGate is live!
QualityGate went live during the holidays!
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Beta testing
QualityGate 2.0 is in the beta testing phase.
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What is QualityGate?

QualityGate is software that continuously measures and monitors the quality of the source code of your systems as-well-as the performance of the development team. Source code is analyzed onsite, by our static analyzer tools, without ever getting out of your infrastructure. Only the final results of the analysis (metrics, list of coding issues and duplications, etc.) are uploaded to our servers for having them evaluated against our benchmarks by using sophisticated quality models. You can browse and further analyze the results any time on our dashboards.

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Our static analyzers support Java, C#, and Javascript at the moment. We are working on integrating C/C++ and Python languages.

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The analyzer handles code stored in Git or TFS. All the analysis results can be queried through a well-defined REST API, making any necessary integration easy to do.

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The expressive and fancy visualization provided by our dashboards lets you see the big picture easily, or you can dive into the details with a few clicks if you wish.

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Our metric categories include size, complexity, inheritance, coupling, cohesion, documentation and code duplication metrics.

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Our analyzers can find several hundreds of types of coding issues, including security vulnerabilities and possible runtime exceptions.

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We wont't not just give you the code duplications in your source code, but we'll show you when they change inconsistently.

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By means of dataflow analysis and symbolic code execution, our analyzers are capable of finding security vulnerabilities listed on OWASP Top Ten.

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Our algorithms qualify your source code maintainability on a ten grade scale, against benchmarks including quality attributes of our other customers' systems. You can learn where you stand with the quality compared to others.

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Our system breaks down your systems' qualifications for each developers' performance in your team. This information helps you in making decisions about trainings, gratifications, etc.

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Need to know how maintainable your source code is? You'd like to have an expert's opinion on that? Having doubts about your system's maintainability? Want to know how to improve your code quality? We'll be happy to help you find the answers!
Want to improve your source code quality management capabilities? Got stuck in an unmaintainable code's development? Being provident about the foreseeable future of quality importance? We'll be happy to help you develop being capable to proactively manage your development's quality!
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Case studies
"Which software development company should I choose?"

The following case study shows how QualityGate gives an objective, important quality characteristic which was somehow rarely calculated in the past. This characteristic helps the client choose the development company suitable for his needs. The case study also shows how this newly introduced attribute affected a client’s decision. We recommend it to anyone who thinks to find the best developers is of key importance.

QualityGate as an SLA monitor in banking environment

The following case study shows how the QualityGate source code analyzing and management system has been introduced into a bank environment as an SLA measurement tool – as well as the installation process and the most important experiences of the introduction and pilot period.

Let's calculate maintenance costs with QualityGate

In this case study, we demonstrate how Qualysoft – a software development company present on the international market – determined the future development and maintenance costs of a software project using QualityGate.

Attack of the clones

Source code cloning, also known as copy and paste programming is believed to be a major threat to software systems, mostly the ones currently in their implementation phase. The problem is often overlooked due to the true danger lies in the clones' long-term existence, specifically in their unmonitored evolution – hence the immediate negative impact cannot be observed. When a clone instance of a given method needs maintenance (bug fixing) or further code development (enhancement), usually the tasks would require to be performed on the other clone instances as well for the consistency to remain.

Code clones - Good, bad or ugly?

Code clones (the products of code cloning or copy and paste programming) can be a menace when it comes to long-term source code maintainability. While they seem harmless at first, they will do their damage after a few development iterations – exactly when it is too late for an easy fix. Neglecting to manage clone instances along with each other during a bug fix or a feature development of any of them will likely result in the inconsistency of the source code.

Cost of software development

Estimating development costs could be a problematic task. There are a huge number of details that should be taken into account for the calculation, the most important of which probably is the maintainability of the source code. It is axiomatic that maintainability has an immediate effect on development cost, because the less maintainable the software system is, the more expense is needed to develop it.

Different definitions of lines of code

Lines of Code is one of the most controversial source code metrics in software engineering practice. It is relatively easy to calculate, understand and use by the different stakeholders for a variety of purposes – that is why it is the most frequently applied measure in software estimation, quality assurance and many other fields. Yet, there is a high level of variability in the definition and calculation methods of the metric which makes it difficult to use it as a base for important decisions. Furthermore, there are cases when its usage is highly questionable – such as direct programmer productivity assessment.

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