SonarQube vs. Choreo by WSO2

SonarQube is excellent if you start using it at the beginning when developing a new system, in this situation you will be able to fix things before they become spread and expensive to correct. It’s a bit less suitable to use on existing code with bad design as it’s usually too expensive to fix everything and only allows you to ensure the situation doesn’t get worse.

Incentivized

While you are developing your code, my case is codes for bots, you'll have more power and if you have an API ally that shows forecasts of latencies and throughputs: Choreo by WS02 is that friend. It is very ideal in giving insights on intelligent data mapping, code anomalies as you develop the codes or applications.

Incentivized

• Detecting bugs and vulnerabilities: SonarQube can identify a wide range of bugs and vulnerabilities in code, such as null pointer exceptions, SQL injection, and cross-site scripting (XSS) attacks. It uses static analysis to analyze the code and identify potential issues, and it can also integrate with dynamic analysis tools to provide even more detailed analysis.
• Measuring code quality: SonarQube can measure a wide range of code quality metrics, such as cyclomatic complexity, duplicated code, and code coverage. This can help teams understand the quality of their code and identify areas that need improvement.
• Providing actionable insights: SonarQube provides detailed information about issues in the code, including the file and line number where the issue occurs and the severity of the issue. This makes it easy for developers to understand and address issues in the code.
• Integrating with other tools: SonarQube can be integrated with a wide range of development tools and programming languages, such as Git, Maven, and Java. This allows teams to use SonarQube in their existing development workflow and take advantage of its powerful code analysis capabilities.
• Managing technical debt: SonarQube provides metrics and insights on the technical debt on the codebase, enabling teams to better prioritize issues to improve the quality of the code.
• Compliance with coding standards: SonarQube can check the code against industry standards like OWASP, CWE and more, making sure the code is compliant with security and coding standards.

Incentivized

• Provides feedback in real time which sorts most of the API performance challenges.
• Displays the estimated application performance as you compose your code.

Incentivized

• Importing a new custom quality profile on SonarQube is a bit tricky, it can be made easier
• Every second time when we want to rerun the server, we have to restart the whole system, otherwise, the server stops and closes automatically
• When we generate a new report a second time and try to access the report, it shows details of the old report only and takes a lot of time to get updated with the details of the new and fresh report generated

Incentivized

• Latency curves may be inaccurate sometimes or provide over/under estimates

Incentivized

It can improve in some user experience and usability parts, like the code view and the way we assign issues it's a bit hidden and not highlighted

Incentivized

We we easily able to integrate the SonarQube steps into our TFS process via the Microsoft Marektplace, we didn't have the need to call SonarQube support. We've used their online documentation and community forum if we ran into any issues.

Incentivized

SonarQube is an open-source. It's a scalable product. The costs for this application, for the kind of job it does, are pretty descent. Pipeline scan is more secured in SonarQube. Its a very good tool and its support multiple languages. Its main core competency is of static code analysis and that is why SonarQube exists and it does it exceedingly well. The quality of scan on code convention, best practices, coding standards, unit test coverage etc makes them one of the best competent tool in the market

Incentivized

• Positive ROI from the standpoint of flagging several issues that would have otherwise likely been unaddressed and caused more time to be spent closer to launch
• Slightly positive ROI from time-saving perspective (it's an automated check which is nice, but depending on the issues it finds, can take developers time to investigate and resolve)

• over 90 percent accuracy in performance prediction of bots under development
• It's possible to trace on faulty codes, down to the machine-level details.

Incentivized