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• ProcessBuilder is not called when trying to start a process

  15 juin 2022, par xnok

  I am trying to understand more about the ffmpeg usage in JavaCV for android studio and for said task I am trying to use ProcessBuilder. I tried writting a simple program to debug the pb.start(); Although, I am not getting a response. What I did was to start a default/empty activity and pasted the following program :

  


  package com.example.myapplication;

import androidx.annotation.RequiresApi;
import androidx.appcompat.app.AppCompatActivity;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.io.OutputStream;

import org.bytedeco.javacpp.Loader;

import android.os.Build;
import android.os.Bundle;
import android.util.Log;

public class MainActivity extends AppCompatActivity {
    static final int cols = 192;
    static final int rows = 108;
    static final String ffmpeg = Loader.load(org.bytedeco.ffmpeg.ffmpeg.class);
    static final String rtmp_url = "test.flv";
    static final String[] command = {ffmpeg,
            "-y",
            "-f", "rawvideo",
            "-vcodec", "rawvideo",
            "-pix_fmt", "bgr24",
            "-s", (Integer.toString(cols) + "x" + Integer.toString(rows)),
            "-r", "10",
            "-i", "pipe:",
            "-c:v", "libx264",
            "-pix_fmt", "yuv420p",
            "-preset", "ultrafast",
            "-f", "flv",
            rtmp_url};
    @RequiresApi(api = Build.VERSION_CODES.O)
    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);
        new Thread(t1).start();

    }
    private static Runnable t1 = () -> {
        Log.e("TAG", "void OnCreate called successfully!");
        ProcessBuilder pb = new ProcessBuilder(command).redirectErrorStream(true);
        pb.redirectErrorStream(true);
        try {
            Process process = pb.start();
            BufferedReader reader = new BufferedReader(new InputStreamReader(process.getInputStream()));
            OutputStream writer = process.getOutputStream();
            Log.e("TAG", "Something good happened here");
        } catch (IOException e) {
            e.printStackTrace();
            Log.e("TAG", "Nothing good happened here");
        }
    };


}


  


  My current problem is that I can't seem to start properly the processBuilder process via pb.start() ;

  


  I get the following logs from the logcat panel :

  


  2022-06-14 17:24:46.328 13371-13371/com.example.myapplication E/TAG: void OnCreate called successfully!
2022-06-14 17:24:46.333 13371-13371/com.example.myapplication E/TAG: Nothing good happened here


  


  I'd like to understand why is it skipping the try/catch block and not starting the process ?

  


  EDIT : I made some changes as per @g00se's suggestions and I got the following stack trace from the code above :

  


  2022-06-15 00:32:26.700 29787-29787/? E/USNET: USNET: appName: com.example.myapplication
2022-06-15 00:32:29.328 29787-29828/com.example.myapplication E/TAG: void OnCreate called successfully!
2022-06-15 00:32:29.330 29787-29828/com.example.myapplication E/AndroidRuntime: FATAL EXCEPTION: Thread-4
    Process: com.example.myapplication, PID: 29787
    java.lang.NullPointerException
        at java.lang.ProcessBuilder.start(ProcessBuilder.java:1012)
        at com.example.myapplication.MainActivity.lambda$static$0(MainActivity.java:48)
        at com.example.myapplication.MainActivity$$ExternalSyntheticLambda0.run(Unknown Source:0)
        at java.lang.Thread.run(Thread.java:920)


  


• Parsing The Clue Chronicles

  30 décembre 2018, par Multimedia Mike — Game Hacking

  A long time ago, I procured a 1999 game called Clue Chronicles : Fatal Illusion, based on the classic board game Clue, a.k.a. Cluedo. At the time, I was big into collecting old, unloved PC games so that I could research obscure multimedia formats.

  
  
  

  Surveying the 3 CD-ROMs contained in the box packaging revealed only Smacker (SMK) videos for full motion video which was nothing new to me or the multimedia hacking community at the time. Studying the mix of data formats present on the discs, I found a selection of straightforward formats such as WAV for audio and BMP for still images. I generally find myself more fascinated by how computer games are constructed rather than by playing them, and this mix of files has always triggered a strong “I could implement a new engine for this !” feeling in me, perhaps as part of the ScummVM project which already provides the core infrastructure for reimplementing engines for 2D adventure games.

  Tying all of the assets together is a custom high-level programming language. I have touched on this before in a blog post over a decade ago. The scripts are in a series of files bearing the extension .ini (usually reserved for configuration scripts, but we’ll let that slide). A representative sample of such a script can be found here :

  clue-chronicles-scarlet-1.txt

  What Is This Language ?
  At the time I first analyzed this language, I was still primarily a C/C++-minded programmer, with a decent amount of Perl experience as a high level language, and had just started to explore Python. I assessed this language to be “mildly object oriented with C++-type comments (‘//’) and reliant upon a number of implicit library functions”. Other people saw other properties. When I look at it nowadays, it reminds me a bit more of JavaScript than C++. I think it’s sort of a Rorschach test for programming languages.

  Strangely, I sort of had this fear that I would put a lot of effort into figuring out how to parse out the language only for someone to come along and point out that it’s a well-known yet academic language that already has a great deal of supporting code and libraries available as open source. Google for “spanish dolphins far side comic” for an illustration of the feeling this would leave me with.

  It doesn’t matter in the end. Even if such libraries exist, how easy would they be to integrate into something like ScummVM ? Time to focus on a workable approach to understanding and processing the format.

  Problem Scope
  So I set about to see if I can write a program to parse the language seen in these INI files. Some questions :

  1. How large is the corpus of data that I need to be sure to support ?
  2. What parsing approach should I take ?
  3. What is the exact language format ?
  4. Other hidden challenges ?

  To figure out how large the data corpus is, I counted all of the INI files on all of the discs. There are 138 unique INI files between the 3 discs. However, there are 146 unique INI files after installation. This leads to a hidden challenge described a bit later.

  What parsing approach should I take ? I worried a bit too much that I might not be doing this the “right” way. I’m trying to ignore doubts like this, like how “SQL Shame” blocked me on a task for a little while a few years ago as I concerned myself that I might not be using the purest, most elegant approach to the problem. I know I covered language parsing a lot time ago in university computer science education and there is a lot of academic literature to the matter. But sometimes, you just have to charge in and experiment and prototype and see what falls out. In doing so, I expect to have a better understanding of the problems that need to solved and the right questions to ask, not unlike that time that I wrote a continuous integration system from scratch because I didn’t actually know that “continuous integration” was the keyword I needed.

  Next, what is the exact language format ? I realized that parsing the language isn’t the first and foremost problem here– I need to know exactly what the language is. I need to know what the grammar are keywords are. In essence, I need to reverse engineer the language before I write a proper parser for it. I guess that fits in nicely with the historical aim of this blog (reverse engineering).

  Now, about the hidden challenges– I mentioned that there are 8 more INI files after the game installs itself. Okay, so what’s the big deal ? For some reason, all of the INI files are in plaintext on the CD-ROM but get compressed (apparently, according to file size ratios) when installed to the hard drive. This includes those 8 extra INI files. I thought to look inside the CAB installation archive file on the CD-ROM and the files were there… but all in compressed form. I suspect that one of the files forms the “root” of the program and is the launching point for the game.

  Parsing Approach
  I took a stab at parsing an INI file. My approach was to first perform lexical analysis on the file and create a list of 4 types : symbols, numbers, strings, and language elements ([]{}()=., :). Apparently, this is the kind of thing that Lex/Flex are good at. This prototyping tool is written in Python, but when I port this to ScummVM, it might be useful to call upon the services of Lex/Flex, or another lexical analyzer, for there are many. I have a feeling it will be easier to use better tools when I understand the full structure of the language based on the data available.
  
  The purpose of this tool is to explore all the possibilities of the existing corpus of INI files. To that end, I ran all 138 of the plaintext files through it, collected all of the symbols, and massaged the results, assuming that the symbols that occurred most frequently are probably core language features. These are all the symbols which occur more than 1000 times among all the scripts :

     6248 false
     5734 looping
     4390 scripts
     3877 layer
     3423 sequentialscript
     3408 setactive
     3360 file
     3257 thescreen
     3239 true
     3008 autoplay
     2914 offset
     2599 transparent
     2441 text
     2361 caption
     2276 add
     2205 ge
     2197 smackanimation
     2196 graphicscript
     2196 graphic
     1977 setstate
     1642 state
     1611 skippable
     1576 desc
     1413 delayscript
     1298 script
     1267 seconds
     1019 rect
  

  About That Compression
  I have sorted out at least these few details of the compression :

  bytes 0-3    "COMP" (a pretty strong sign that this is, in fact, compressed data)
  bytes 4-11   unknown
  bytes 12-15  size of uncompressed data
  bytes 16-19  size of compressed data (filesize - 20)
  bytes 20-    compressed payload
  

  The compression ratios are on the same order of gzip. I was hoping that it was stock zlib data. However, I have been unable to prove this. I wrote a Python script that scrubbed through the first 100 bytes of payload data and tried to get Python’s zlib.decompress to initialize– no luck. It’s frustrating to know that I’ll have to reverse engineer a compression algorithm that deals with just 8 total text files if I want to see this effort through to fruition.

  Update, January 15, 2019
  Some folks expressed interest in trying to sort out the details of the compression format. So I have posted a followup in which I post some samples and go into deeper details about things I have tried :

  Reverse Engineering Clue Chronicles Compression

  The post Parsing The Clue Chronicles first appeared on Breaking Eggs And Making Omelettes.

• Visualizing Call Graphs Using Gephi

  1er septembre 2014, par Multimedia Mike — General

  When I was at university studying computer science, I took a basic chemistry course. During an accompanying lab, the teaching assistant chatted me up and asked about my major. He then said, “Computer science ? Well, that’s just typing stuff, right ?”

  My impulsive retort : “Sure, and chemistry is just about mixing together liquids and coming up with different colored liquids, as seen on the cover of my high school chemistry textbook, right ?”

  
  
  

  In fact, pure computer science has precious little to do with typing (as is joked in CS circles, computer science is about computers in the same way that astronomy is about telescopes). However, people who study computer science often pursue careers as programmers, or to put it in fancier professional language, software engineers.

  So, what’s a software engineer’s job ? Isn’t it just typing ? That’s where I’ve been going with this overly long setup. After thinking about it for long enough, I like to say that a software engineer’s trade is managing complexity.

  A few years ago, I discovered Gephi, an open source tool for graph and data visualization. It looked neat but I didn’t have much use for it at the time. Recently, however, I was trying to get a better handle on a large codebase. I.e., I was trying to manage the project’s complexity. And then I thought of Gephi again.

  Prior Work
  One way to get a grip on a large C codebase is to instrument it for profiling and extract details from the profiler. On Linux systems, this means compiling and linking the code using the -pg flag. After running the executable, there will be a gmon.out file which is post-processed using the gprof command.

  GNU software development tools have a reputation for being rather powerful and flexible, but also extremely raw. This first hit home when I was learning how to use the GNU tool for code coverage — gcov — and the way it outputs very raw data that you need to massage with other tools in order to get really useful intelligence.

  And so it is with gprof output. The output gives you a list of functions sorted by the amount of processing time spent in each. Then it gives you a flattened call tree. This is arranged as “during the profiled executions, function c was called by functions a and b and called functions d, e, and f ; function d was called by function c and called functions g and h”.

  How can this call tree data be represented in a more instructive manner that is easier to navigate ? My first impulse (and I don’t think I’m alone in this) is to convert the gprof call tree into a representation suitable for interpretation by Graphviz. Unfortunately, doing so tends to generate some enormous and unwieldy static images.

  Feeding gprof Data To Gephi
  I learned of Gephi a few years ago and recalled it when I developed an interest in gaining better perspective on a large base of alien C code. To understand what this codebase is doing for a particular use case, instrument it with gprof, gather execution data, and then study the code paths.

  How could I feed the gprof data into Gephi ? Gephi supports numerous graphing formats including an XML-based format named GEXF.

  Thus, the challenge becomes converting gprof output to GEXF.

  Which I did.

  Demonstration
  I have been absent from FFmpeg development for a long time, which is a pity because a lot of interesting development has occurred over the last 2-3 years after a troubling period of stagnation. I know that 2 big video codec developments have been HEVC (next in the line of MPEG codecs) and VP9 (heir to VP8’s throne). FFmpeg implements them both now.

  I decided I wanted to study the code flow of VP9. So I got the latest FFmpeg code from git and built it using the options "--extra-cflags=-pg --extra-ldflags=-pg". Annoyingly, I also needed to specify "--disable-asm" because gcc complains of some register allocation snafus when compiling inline ASM in profiling mode (and this is on x86_64). No matter ; ASM isn’t necessary for understanding overall code flow.

  After compiling, the binary ‘ffmpeg_g’ will have symbols and be instrumented for profiling. I grabbed a sample from this VP9 test vector set and went to work.

  ./ffmpeg_g -i vp90-2-00-quantizer-00.webm -f null /dev/null
  gprof ./ffmpeg_g > vp9decode.txt
  convert-gprof-to-gexf.py vp9decode.txt > /bigdisk/vp9decode.gexf
  

  Gephi loads vp9decode.gexf with no problem. Using Gephi, however, can be a bit challenging if one is not versed in any data exploration jargon. I recommend this Gephi getting starting guide in slide deck form. Here’s what the default graph looks like :

  
  
  

  Not very pretty or helpful. BTW, that beefy arrow running from mid-top to lower-right is the call from decode_coeffs_b -> iwht_iwht_4x4_add_c. There were 18774 from the former to the latter in this execution. Right now, the edge thicknesses correlate to number of calls between the nodes, which I’m not sure is the best representation.

  Following the tutorial slide deck, I at least learned how to enable the node labels (function symbols in this case) and apply a layout algorithm. The tutorial shows the force atlas layout. Here’s what the node neighborhood looks like for probing file type :

  
  
  

  Okay, so that’s not especially surprising– avprobe_input_format3 calls all of the *_probe functions in order to automatically determine input type. Let’s find that decode_coeffs_b function and see what its neighborhood looks like :

  
  
  

  That’s not very useful. Perhaps another algorithm might help. I select the Fruchterman–Reingold algorithm instead and get a slightly more coherent representation of the decoding node neighborhood :

  
  
  

  Further Work
  Obviously, I’m just getting started with this data exploration topic. One thing I would really appreciate in such a tool is the ability to interactively travel the graph since that’s what I’m really hoping to get out of this experiment– watching the code flows.

  Perhaps someone else can find better use cases for visualizing call graph data. Thus, I have published the source code for this tool at Github.