Open Source Go Source Code Analysis Tools

Pulumi's Infrastructure as Code SDK is the easiest way to create and deploy cloud software that use containers, serverless functions, hosted services, and infrastructure, on any cloud. Simply write code in your favorite language and Pulumi automatically provisions and manages your AWS, Azure, Google Cloud Platform, and/or Kubernetes resources, using an infrastructure-as-code approach. Skip the YAML, and use standard language features like loops, functions, classes, and package management that you already know and love. Pulumi is open source under the Apache 2.0 license, supports many languages and clouds, and is easy to extend. This repo contains the pulumi CLI, language SDKs, and core Pulumi engine, and individual libraries are in their own repos. Walk through end-to-end workflows for creating containers, serverless functions, and other cloud services and infrastructure.

Sloc, Cloc and Code: scc is a very fast accurate code counter with complexity calculations and COCOMO estimates written in pure Go. The tool is similar to cloc, sloccount and tokei. For counting the lines of code, blank lines, comment lines, and physical lines of source code in many programming languages. The goal is to be the fastest code counter possible, but also perform COCOMO calculations like sloccount, estimate code complexity similar to cyclomatic complexity calculators, and produce unique lines of code or DRYness metrics. In short one tool to rule them all.

BuildKit is a toolkit for converting source code to build artifacts in an efficient, expressive and repeatable manner. BuildKit is a new project under the Moby umbrella for building and packaging software using containers. It’s a new codebase meant to replace the internals of the current build features in the Moby Engine. BuildKit emerged from the discussions about improving the build features in Moby Engine. We received a lot of positive feedback for the multi-stage build feature introduced in April and had proposals and user requests for many similar additions. But before that, we needed to make sure that we have capabilities to continue adding such features in the future and a solid foundation to extend on. Quite soon it was clear that we would need to redefine most of the fundamentals about how we even define a build operation and needed a clean break from the current codebase. A proposal was written, and development started in the open under the new repository.

I’d like to introduce reviewdog! An automated code review tool working with any lint tools and supports local run as well. “reviewdog” provides a way to post review comments to code hosting services, such as GitHub, automatically by integrating with any linter tools with ease. It uses any output of lint tools, with translation if required, and posts them as a comment if the file and line are in diff of patches to review. reviewdog also supports running in a local environment to filter the output of lint tools by diff. We can use various linters and static code analysis tools to detect such problems in local machines, editors, CI services. However, here is the problem. Static analysis tools may report false-positive results. Reporting false-positive results itself is ok, but due to the false-positive results we cannot make build fail and it becomes difficult for us to find true positive results from messed up analysis results.