Garbage Collection in C Programs
The first word that came to mind when I heard about introducing Garbage Collection techniques into a C or C++ program was “nonsense”. As with any other decent C programmer who loves this language, the thought of leaving the management of my own memory to others seemed nearly offensive. I had a similar feeling 15 years ago, when I first heard about compilers that would generate assembly code on my behalf. I was used to writing my code directly in 6510 opcodes, but that was Commodore 64—and a totally different story.
Garbage Collection (GC) is a mechanism that provides automatic memory reclamation for unused memory blocks. Programmers dynamically allocate memory, but when a block is no longer needed, they do not have to return it to the system explicitly with a free() call. The GC engine takes care of recognizing that a particular block of allocated memory (heap) is not used anymore and puts it back into the free memory area. GC was introduced by John McCarthy in 1958, as the memory management mechanism of the LISP language. Since then, GC algorithms have evolved and now can compete with explicit memory management. Several languages are natively based on GC. Java probably is the most popular one, and others include LISP, Scheme, Smalltalk, Perl and Python. C and C++, in the tradition of a respectable, low-level approach to system resources management, are the most notable exceptions to this list.
Many different approaches to garbage collection exist, resulting in some families of algorithms that include reference counting, mark and sweep and copying GCs. Hybrid algorithms, as well as generational and conservative variants, complete the picture. Choosing a particular GC algorithm usually is not a programmer's task, as the memory management system is imposed by the adopted programming language. An exception to this rule is the Boehm-Demers-Weiser (BDW) GC library, a popular package that allows C and C++ programmers to include automatic memory management into their programs. The question is: Why would they want to do a thing like this?
The BDW library is a freely available library that provides C and C++ programs with garbage collection capabilities. The algorithm it employs belongs to the family of mark and sweep collectors, where GC is split into two phases. First, a scan of all the live memory is done in order to mark unused blocks. Then, a sweep phase takes care of putting the marked blocks in the free blocks list. The two phases can be, and usually are, performed separately to increase the general response time of the library. The BDW algorithm also is generational; it concentrates free space searches on newer blocks. This is based on the idea that older blocks statistically live longer. To put it another way, most allocated blocks have short lifetimes. Finally, the BDW algorithm is conservative in that it needs to make assumptions on which variables are actually pointers to dynamic data and which ones only look that way. This is a consequence of C and C++ being weakly typed languages.
The BDW collector comes as a static or dynamic library and is installed easily by downloading the corresponding package (see Resources) and running the traditional configure, make and make install commands. Some Linux distributions also come with an already-made package. For example, with Gentoo you need to type only emerge boehm-gc to install it. The installed files include both a shared object (libgc.o) and a static library (libgc.a).
Using the library is a fairly straightforward task; for newly developed programs, you simply call GC_alloc() to get memory and then forget about it when you do not need it anymore. “Forget about it” means setting all the pointers that reference it to NULL. For already existing sources, substitute all allocation calls (malloc, calloc, realloc) with the GC-endowed ones. All free() calls are replaced with nothing at all, but do set any relevant pointers to NULL.
GC_alloc() actually sets the allocated memory to zero to minimize the risk that preexisting values are misinterpreted as valid pointers by the GC engine. Hence, GC_alloc() behaves more like calloc() than malloc().
If you want to try GC in an existing application, manually editing the source code to change mallocs and frees is not necessary. In order to redirect those calls to the GC version, you basically have three options: using a macro, modifying the malloc hooks and overriding glibc's malloc() with libgc's malloc(). The first approach is the easiest one; you simply need to insert something like:
#define malloc(x) GC_malloc(x) #define calloc(n,x) GC_malloc((n)*(x)) #define realloc(p,x) GC_realloc((p),(x)) #define free(x) (x) = NULL
Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.
Sponsored by AMD
Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6
Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.
Learn more about catching the bad guy in this free white paper.
Sponsored by DLT Solutions
| Making Linux and Android Get Along (It's Not as Hard as It Sounds) | May 16, 2013 |
| Drupal Is a Framework: Why Everyone Needs to Understand This | May 15, 2013 |
| Home, My Backup Data Center | May 13, 2013 |
| Non-Linux FOSS: Seashore | May 10, 2013 |
| Trying to Tame the Tablet | May 08, 2013 |
| Dart: a New Web Programming Experience | May 07, 2013 |
- RSS Feeds
- New Products
- Making Linux and Android Get Along (It's Not as Hard as It Sounds)
- Drupal Is a Framework: Why Everyone Needs to Understand This
- A Topic for Discussion - Open Source Feature-Richness?
- Home, My Backup Data Center
- Dart: a New Web Programming Experience
- Developer Poll
- What's the tweeting protocol?
- May 2013 Issue of Linux Journal: Raspberry Pi
Enter to Win an Adafruit Prototyping Pi Plate Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Prototyping Pi Plate Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- Next winner announced on 5-21-13!
Free Webinar: Linux Backup and Recovery
Most companies incorporate backup procedures for critical data, which can be restored quickly if a loss occurs. However, fewer companies are prepared for catastrophic system failures, in which they lose all data, the entire operating system, applications, settings, patches and more, reducing their system(s) to “bare metal.” After all, before data can be restored to a system, there must be a system to restore it to.
In this one hour webinar, learn how to enhance your existing backup strategies for better disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible bare-metal recovery solution for UNIX and Linux systems.




3 hours 23 min ago
4 hours 10 min ago
5 hours 43 min ago
7 hours 20 min ago
9 hours 18 min ago
9 hours 35 min ago
10 hours 5 min ago
10 hours 6 min ago
10 hours 6 min ago
13 hours 7 min ago