Meet Sputnik – static code analyser for Gerrit

Sputnik runs Checkstyle, PMD and FindBugs for your Gerrit patchsets I am happy to announce a first release of Sputnik! It is a static code analyzer that runs Checkstyle, PMD and FindBugs for your Gerrit patchsets. Its main advantage over my previous pr…

Sputnik runs Checkstyle, PMD and FindBugs for your Gerrit patchsets

I am happy to announce a first release of Sputnik! It is a static code analyzer that runs Checkstyle, PMD and FindBugs for your Gerrit patchsets. Its main advantage over my previous project Sonar Gerrit plugin is that Sputnik is a small, lightweight and standalone Java application. You don’t need any other software to run it. It bundles Checkstyle, PMD and FindBugs jars within distribution zip.

Workflow

Sputnik is intended to use with Gerrit and Continous Integration server, i. e. Jenkins. It works like this:

Your CI server is updated by ssh that a new patch is submitted to Gerrit. CI fetches this patch and builds a while project. After a build, CI server reports its result to Gerrit. It’s time for Sputnik now.

Sputnik runs regardless of build result (you can change that in your CI configuration). Sputnik fetches patchset’s file list from Gerrit over HTTP REST API. Then it runs an analysis only on these files! Even if your project is huge, analysis on several files takes only seconds. Sputnik collects comments from all three analysers: Checkstyle, PMD and FindBugs. It sends back all comments to Gerrit via HTTP REST API back. It’s very simple and very fast!

Installation and configuration

First, you need to build https://github.com/TouK/sputnik master or download distribution zip from here: sputnik-1.0.zip. Go to you CI server and extract it to a directory of your choice. Remember that a user you run CI builds needs to have an access rights to this directory (in my case it’s simply a jenkins user). Then you need to prepare your configuration file and write this file to the same directory as unzipped distribution. It is a simple Java properties file, which is pretty self-explanatory. Here is an example:

gerrit.host=gerrit.yourcompany.com
gerrit.port=8080
gerrit.username=sputnik
gerrit.password=Pa$$wo4d
checkstyle.enabled=true
checkstyle.configurationFile=/opt/jenkins/sputnik/checkstyle.xml
checkstyle.propertiesFile=
pmd.enabled=true
pmd.ruleSets=/opt/jenkins/sputnik/pmd.xml
findbugs.enabled=true
findbugs.includeFilter=/opt/jenkins/sputnik/findbugs.xml
findbugs.excludeFilter=

Now you need to configure you CI server to actually run Sputnik after a build. It is very simple for Jenkins, just add a Post-Build Step. You can adjust if Sputnik runs only on successful build or for every build – use radio buttons for this:

Last line with exit 0 is a workaround for a clean exit, even if Sputnik fails for some reason. Exit 0 guarantees you that result of this step doesn’t affect overall build result.

Summary

This is an example screenshot of Sputnik’s comments:

Sputnik always reports +1 as a result. It can be lacking in some network and authorisation configuration. But it’s open source so please submit issues and patches to its github page: https://github.com/TouK/sputnik.

Your feedback and pull requests are heartly welcome!

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During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.

Motivation

From time to time our sprints scope is changing. It is not a big deal because we are trying to be agile :-) but Jira's burndowchart in this situation draw a peek. Because in fact that chart shows scope changes not a real burndown. It means, that chart cannot break down an x-axis if we really do more than we were planned – it always stop on at most zero.

Also for better progress monitoring we've started to split our user stories to technical tasks and estimating them. Original burndowchart doesn't show points from technical tasks. I can find motivation of this – user story almost finished isn't finished at all until user can use it. But in the other hand, if we know which tasks is problematic we can do some teamwork to move it on.

So I realize that it is a good opportunity to try some new approaches and tools.

Tools

I've started with lift framework. In the World of Single Page Applications, this framework has more than simple interface for serving REST services. It comes with awesome Comet support. Comet is a replacement for WebSockets that run on all browsers. It supports long polling and transparent fallback to short polling if limit of client connections exceed. In backend you can handle pushes in CometActor. For further reading take a look at Roundtrip promises

But lift framework is also a kind of framework of frameworks. You can handle own abstraction of CometActors and push to client javascript that shorten up your way from server to client. So it was the trigger for author of lift-ng to make a lift with Angular integration that is build on top of lift. It provides AngularActors from which you can emit/broadcast events to scope of controller. NgModelBinders that synchronize your backend model with client scope in a few lines! I've used them to send project state (all sprints and thier details) to client and notify him about scrum board changes. My actor doing all of this hard work looks pretty small:

Lift-ng also provides factories for creating of Angular services. Services could respond with futures that are transformed to Angular promises in-fly. This is all what was need to serve sprint history:

And on the client side - use of service:


In my opinion this two frameworks gives a huge boost in developing of web applications. You have the power of strongly typing with Scala, you can design your domain on Actors and all of this with simplicity of node.js – lack of json trasforming boilerplate and dynamic application reload.

DDD + Event Sourcing

I've also tried a few fresh approaches to DDD. I've organize domain objects in actors. There are SprintActors with encapsulate sprint aggregate root. Task changes are stored as events which are computed as a difference between two boards states. When it should be provided a history of sprint, next board states are computed from initial state and sequence of events. So I realize that the best way to keep this kind of event sourcing approach tested is to make random tests. This is a test doing random changes at board, calculating events and checking if initial state + events is equals to previously created state:



First look

Screenshot of first version:


If you want to look at this closer, check the source code or download ready to run fatjar on github.During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.