A few months ago, I started to migrate some of my websites to DigitalOcean because the cost of a virtual server is $5/mo. So, I moved CodingGorilla.com to the new host. (Note, a long story, but the name came from an old boss, who saw I have the patience of a saint and attention to minute details, the traits of any good programmer.)
Unfortunately, the website has been painfully slow because I was told that you should keep your database and web server on separate hardware. This may be fine for large corps which have their servers on a fast LAN, but this was the wrong advice for a blog. I moved the MySQL database to the web server, and now the website works ~100x faster. Adage for the day: Believe half of what you see and nothing of what you hear.
Incidentally, the tool which I used to find this problem is Query Monitor by John Blackbourn (plugin page, website). I flags the slow queries, places the runtime for each query in a table, which you can then copy and paste into Excel to compute the total time required for the queries.
For the last two weeks, I’ve trying to write Piggy patterns to construct a symbol table from a Java AST. Patch after patch, I’d “fixed” the pattern matching code to fix something that wasn’t working. Unfortunately, I finally wrote a pattern that broke the camel’s back, “< classBodyDeclaration < modifier >* < memberDeclaration < methodDeclaration > >”, which looks for methods within a class.
So, I decided to rewrite the engine the way it should have been done: using an NFA. It’s so far taken a week or so, but it turns that the pattern matcher is much cleaner, and likely faster. In addition, the output engine–which executes the code blocks in the pattern–is also much cleaner. I’ll try to see if I can combine the patterns together in one automaton.
I really should have known better than to approach the tree regular expression matching problem following what other people did, using a top-down recursive recognizer. Live and learn. Always follow a clean, clear theory instead of just hacking.
Due to my work on Piggy, I’m starting to do a thorough review of the literature on program transformation systems, how Piggy relates to prior research, and what improvements I can make to Piggy. Note, a good list to start from is in Wikipedia: ASF+SDF, CIL (for C), Coccinelle (for C), DMS, Fermat, Spoon (for Java), Stratego/XT, TXL). This is the first entry in the series, on Coccinelle, a system that modifies C source code.
No ifs, ands, or buts, news about Net Standard may be old and stale, but one thing still applies: As Steve Martin would say, “What the hell is that?” Believe it or not, I started writing this entry years ago, a few months after Net Standard first came out. I had hoped that if I just write about it, I’d somehow stumble across what the hell it is. But, I didn’t get anywhere because most people don’t know what the hell they’re talking about. Fast forward to now.
One further refinement to Piggy is required before I make a release of the tool: a wrapper to get the tool under MSBuild. Like the Antlr4BuildTasks wrapper I forked from Antlr4cs, I want Piggy to work seamlessly during the build of a C# project that uses a native library. My plan is for C# projects to contain the Piggy templates required to generate the declarations for C# of the interface needed by the project. Required by the user would be a template for Piggy and C++ file for the Clang compiler. During a build, the Piggy tool would run and produce C# output in the build directory, compiled and linked with the project. So, instead of users writing the DllImport decls to work with a native library, just indicate what you want and let Piggy do the rest. The build tool would be released to NuGet, and would contain the Clang serializer, the Piggy tool, the assembly wrapper for the Clang serializer and Piggy, and all the build rules.
It never ceases to amaze me how people can write a huge API and never bother to document how to use it. But, it’s been that way for as long as I can remember, going back 35 years. In my latest adventures, I’ve been trying to compile, link, and run C# code dynamically using Roslyn for Piggy, my transformational system. If you’ve ever used Roslyn in C#, you’ve probably discovered that it can be such a pain in the arse to use because Microsoft gives doc for the API, does give some tutorials, but I can’t find a simple example for compiling, linking, and running C#. I don’t need to know all the details yet, just a starting point framework. Unfortunately, the solution is quite sensitive to whether you use Net Core or Net Framework.
In order to better support Piggy, which uses Antlr4, I’ve added a NuGet package called Antlr4BuildTasks. This package is a pared-down derivative of the excellent work of Sam HartwellAntlr4cs code generator package, and includes just the rules and code needed to do builds in MSBuild, Dotnet, or Visual Studio 2017 IDE–just no Antlr4 tool itself. This package decouples the build rules from the Antlr4 tool and runtime, so you can build Antlr programs using the latest Java-based Antlr tool and runtime release. To use this package, make a reference to this package as if you would to any NuGet package; make sure to also reference the Antlr4.Runtime.Standard package, install Java, the Java-based Antler tool, and set JAVA_HOME and Antlr4ToolPath. The tool works with Net Core, Net Framework, or Net Standard code, and on Windows or Linux.
With a bit of hacking for the last month or two, and I can finally see that I am making progress on Piggy, a new kind of p/invoke generator. Some might say “Why in the world are you wasting time writing a p/invoke generator? Aren’t there tools already that do this?” Well, yeah, there are other generators, but they all…how should I say…suck! I need a p/invoke generator for Campy, a compiler and runtime for C# for GPUs, which I am still working on, but had to place on the back burner to work on this. Campy uses LLVM and CUDA. Because these libraries are large and constantly changing, I have to have an automated way of handling new releases.