In engineering, debugging is the process of finding the root cause of and workarounds and possible fixes for bugs.

For software, debugging tactics can involve interactive debugging, control flow analysis, log file analysis, monitoring at the application or system level, memory dumps, and profiling. Many programming languages and software development tools also offer programs to aid in debugging, known as debuggers.


See also: Bug (engineering) § History

A computer log entry from the Mark II, with a moth taped to the page

The term bug, in the sense of defect, dates back at least to 1878 when Thomas Edison wrote "little faults and difficulties" in his inventions as "Bugs".

A popular story from the 1940s is from Admiral Grace Hopper.[1] While she was working on a Mark II computer at Harvard University, her associates discovered a moth stuck in a relay that impeded operation and wrote in a log book "First actual case of a bug being found". Although probably a joke, conflating the two meanings of bug (biological and defect), the story indicates that the term was used in the computer field at that time.

Similarly, the term debugging was used in aeronautics before entering the world of computers. A letter from J. Robert Oppenheimer, director of the WWII atomic bomb Manhattan Project at Los Alamos, used the term in a letter to Dr. Ernest Lawrence at UC Berkeley, dated October 27, 1944,[2] regarding the recruitment of additional technical staff. The Oxford English Dictionary entry for debug uses the term debugging in reference to airplane engine testing in a 1945 article in the Journal of the Royal Aeronautical Society. An article in "Airforce" (June 1945 p. 50) refers to debugging aircraft cameras.

The seminal article by Gill[3] in 1951 is the earliest in-depth discussion of programming errors, but it does not use the term bug or debugging.

In the ACM's digital library, the term debugging is first used in three papers from 1952 ACM National Meetings.[4][5][6] Two of the three use the term in quotation marks.

By 1963 debugging was a common-enough term to be mentioned in passing without explanation on page 1 of the CTSS manual.[7]


As software and electronic systems have become generally more complex, the various common debugging techniques have expanded with more methods to detect anomalies, assess impact, and schedule software patches or full updates to a system. The words "anomaly" and "discrepancy" can be used, as being more neutral terms, to avoid the words "error" and "defect" or "bug" where there might be an implication that all so-called errors, defects or bugs must be fixed (at all costs). Instead, an impact assessment can be made to determine if changes to remove an anomaly (or discrepancy) would be cost-effective for the system, or perhaps a scheduled new release might render the change(s) unnecessary. Not all issues are safety-critical or mission-critical in a system. Also, it is important to avoid the situation where a change might be more upsetting to users, long-term, than living with the known problem(s) (where the "cure would be worse than the disease"). Basing decisions of the acceptability of some anomalies can avoid a culture of a "zero-defects" mandate, where people might be tempted to deny the existence of problems so that the result would appear as zero defects. Considering the collateral issues, such as the cost-versus-benefit impact assessment, then broader debugging techniques will expand to determine the frequency of anomalies (how often the same "bugs" occur) to help assess their impact to the overall system.


Main article: Debugger

Debugging on video game consoles is usually done with special hardware such as this Xbox debug unit intended for developers.

Debugging ranges in complexity from fixing simple errors to performing lengthy and tiresome tasks of data collection, analysis, and scheduling updates. The debugging skill of the programmer can be a major factor in the ability to debug a problem, but the difficulty of software debugging varies greatly with the complexity of the system, and also depends, to some extent, on the programming language(s) used and the available tools, such as debuggers. Debuggers are software tools which enable the programmer to monitor the execution of a program, stop it, restart it, set breakpoints, and change values in memory. The term debugger can also refer to the person who is doing the debugging.

Generally, high-level programming languages, such as Java, make debugging easier, because they have features such as exception handling and type checking that make real sources of erratic behaviour easier to spot. In programming languages such as C or assembly, bugs may cause silent problems such as memory corruption, and it is often difficult to see where the initial problem happened. In those cases, memory debugger tools may be needed.

In certain situations, general purpose software tools that are language specific in nature can be very useful. These take the form of static code analysis tools. These tools look for a very specific set of known problems, some common and some rare, within the source code, concentrating more on the semantics (e.g. data flow) rather than the syntax, as compilers and interpreters do.

Both commercial and free tools exist for various languages; some claim to be able to detect hundreds of different problems. These tools can be extremely useful when checking very large source trees, where it is impractical to do code walk-throughs. A typical example of a problem detected would be a variable dereference that occurs before the variable is assigned a value. As another example, some such tools perform strong type checking when the language does not require it. Thus, they are better at locating likely errors in code that is syntactically correct. But these tools have a reputation of false positives, where correct code is flagged as dubious. The old Unix lint program is an early example.

For debugging electronic hardware (e.g., computer hardware) as well as low-level software (e.g., BIOSes, device drivers) and firmware, instruments such as oscilloscopes, logic analyzers, or in-circuit emulators (ICEs) are often used, alone or in combination. An ICE may perform many of the typical software debugger's tasks on low-level software and firmware.

Debugging process

The debugging process normally begins with identifying the steps to reproduce the problem. This can be a non-trivial task, particularly with parallel processes and some Heisenbugs for example. The specific user environment and usage history can also make it difficult to reproduce the problem.

After the bug is reproduced, the input of the program may need to be simplified to make it easier to debug. For example, a bug in a compiler can make it crash when parsing a large source file. However, after simplification of the test case, only few lines from the original source file can be sufficient to reproduce the same crash. Simplification may be done manually using a divide-and-conquer approach, in which the programmer attempts to remove some parts of original test case then checks if the problem still occurs. When debugging in a GUI, the programmer can try skipping some user interaction from the original problem description to check if the remaining actions are sufficient for causing the bug to occur.

After the test case is sufficiently simplified, a programmer can use a debugger tool to examine program states (values of variables, plus the call stack) and track down the origin of the problem(s). Alternatively, tracing can be used. In simple cases, tracing is just a few print statements which output the values of variables at particular points during the execution of the program.[citation needed]


Automatic bug fixing

Automatic bug-fixing is the automatic repair of software bugs without the intervention of a human programmer.[15][16][17] It is also commonly referred to as automatic patch generation, automatic bug repair, or automatic program repair.[17] The typical goal of such techniques is to automatically generate correct patches to eliminate bugs in software programs without causing software regression.[18]

Debugging for embedded systems

In contrast to the general purpose computer software design environment, a primary characteristic of embedded environments is the sheer number of different platforms available to the developers (CPU architectures, vendors, operating systems, and their variants). Embedded systems are, by definition, not general-purpose designs: they are typically developed for a single task (or small range of tasks), and the platform is chosen specifically to optimize that application. Not only does this fact make life tough for embedded system developers, it also makes debugging and testing of these systems harder as well, since different debugging tools are needed for different platforms.

Despite the challenge of heterogeneity mentioned above, some debuggers have been developed commercially as well as research prototypes. Examples of commercial solutions come from Green Hills Software,[19] Lauterbach GmbH[20] and Microchip's MPLAB-ICD (for in-circuit debugger). Two examples of research prototype tools are Aveksha[21] and Flocklab.[22] They all leverage a functionality available on low-cost embedded processors, an On-Chip Debug Module (OCDM), whose signals are exposed through a standard JTAG interface. They are benchmarked based on how much change to the application is needed and the rate of events that they can keep up with.

In addition to the typical task of identifying bugs in the system, embedded system debugging also seeks to collect information about the operating states of the system that may then be used to analyze the system: to find ways to boost its performance or to optimize other important characteristics (e.g. energy consumption, reliability, real-time response, etc.).


Anti-debugging is "the implementation of one or more techniques within computer code that hinders attempts at reverse engineering or debugging a target process".[23] It is actively used by recognized publishers in copy-protection schemas, but is also used by malware to complicate its detection and elimination.[24] Techniques used in anti-debugging include:

An early example of anti-debugging existed in early versions of Microsoft Word which, if a debugger was detected, produced a message that said, "The tree of evil bears bitter fruit. Now trashing program disk.", after which it caused the floppy disk drive to emit alarming noises with the intent of scaring the user away from attempting it again.[25][26]

See also


  1. ^ "InfoWorld Oct 5, 1981". 5 October 1981. Archived from the original on September 18, 2019. Retrieved July 17, 2019.
  2. ^ "Archived copy". Archived from the original on 2019-11-21. Retrieved 2019-12-17.((cite web)): CS1 maint: archived copy as title (link)
  3. ^ S. Gill, The Diagnosis of Mistakes in Programmes on the EDSAC Archived 2020-03-06 at the Wayback Machine, Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, Vol. 206, No. 1087 (May 22, 1951), pp. 538-554
  4. ^ Robert V. D. Campbell, Evolution of automatic computation Archived 2019-09-18 at the Wayback Machine, Proceedings of the 1952 ACM national meeting (Pittsburgh), p 29-32, 1952.
  5. ^ Alex Orden, Solution of systems of linear inequalities on a digital computer, Proceedings of the 1952 ACM national meeting (Pittsburgh), p. 91-95, 1952.
  6. ^ Howard B. Demuth, John B. Jackson, Edmund Klein, N. Metropolis, Walter Orvedahl, James H. Richardson, MANIAC doi=10.1145/800259.808982, Proceedings of the 1952 ACM national meeting (Toronto), p. 13-16
  7. ^ The Compatible Time-Sharing System Archived 2012-05-27 at the Wayback Machine, M.I.T. Press, 1963
  8. ^ "Postmortem Debugging". Archived from the original on 2019-12-17. Retrieved 2019-12-17.
  9. ^ E. J. Gauss (1982). "Pracniques: The 'Wolf Fence' Algorithm for Debugging". Communications of the ACM. 25 (11): 780. doi:10.1145/358690.358695. S2CID 672811.
  10. ^ Zeller, Andreas (2005). Why Programs Fail: A Guide to Systematic Debugging. Morgan Kaufmann. ISBN 1-55860-866-4.
  11. ^ "Kent Beck, Hit 'em High, Hit 'em Low: Regression Testing and the Saff Squeeze". Archived from the original on 2012-03-11.
  12. ^ Rainsberger, J.B. (28 March 2022). "The Saff Squeeze". The Code Whisperer. Retrieved 28 March 2022.
  13. ^ Zeller, Andreas (2002-11-01). "Isolating cause-effect chains from computer programs". ACM SIGSOFT Software Engineering Notes. 27 (6): 1–10. doi:10.1145/605466.605468. ISSN 0163-5948. S2CID 12098165.
  14. ^ Bond, Michael D.; Nethercote, Nicholas; Kent, Stephen W.; Guyer, Samuel Z.; McKinley, Kathryn S. (2007). "Tracking bad apples". Proceedings of the 22nd annual ACM SIGPLAN conference on Object oriented programming systems and applications - OOPSLA '07. p. 405. doi:10.1145/1297027.1297057. ISBN 9781595937865. S2CID 2832749.
  15. ^ Rinard, Martin C. (2008). "Technical perspective Patching program errors". Communications of the ACM. 51 (12): 86. doi:10.1145/1409360.1409381. S2CID 28629846.
  16. ^ Harman, Mark (2010). "Automated patching techniques". Communications of the ACM. 53 (5): 108. doi:10.1145/1735223.1735248. S2CID 9729944.
  17. ^ a b Gazzola, Luca; Micucci, Daniela; Mariani, Leonardo (2019). "Automatic Software Repair: A Survey" (PDF). IEEE Transactions on Software Engineering. 45 (1): 34–67. doi:10.1109/TSE.2017.2755013. hdl:10281/184798. S2CID 57764123.
  18. ^ Tan, Shin Hwei; Roychoudhury, Abhik (2015). "relifix: Automated repair of software regressions". 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering. IEEE. pp. 471–482. doi:10.1109/ICSE.2015.65. ISBN 978-1-4799-1934-5. S2CID 17125466.
  19. ^ "SuperTrace Probe hardware debugger". Archived from the original on 2017-12-01. Retrieved 2017-11-25.
  20. ^ "Debugger and real-time trace tools". Archived from the original on 2022-01-25. Retrieved 2020-06-05.
  21. ^ Tancreti, Matthew; Hossain, Mohammad Sajjad; Bagchi, Saurabh; Raghunathan, Vijay (2011). "Aveksha". Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems. SenSys '11. New York, NY, USA: ACM. pp. 288–301. doi:10.1145/2070942.2070972. ISBN 9781450307185. S2CID 14769602.
  22. ^ Lim, Roman; Ferrari, Federico; Zimmerling, Marco; Walser, Christoph; Sommer, Philipp; Beutel, Jan (2013). "FlockLab". Proceedings of the 12th international conference on Information processing in sensor networks. IPSN '13. New York, NY, USA: ACM. pp. 153–166. doi:10.1145/2461381.2461402. ISBN 9781450319591. S2CID 447045.
  23. ^ Shields, Tyler (2008-12-02). "Anti-Debugging Series – Part I". Veracode. Archived from the original on 2016-10-19. Retrieved 2009-03-17.
  24. ^ a b "Software Protection through Anti-Debugging Michael N Gagnon, Stephen Taylor, Anup Ghosh" (PDF). Archived from the original (PDF) on 2011-10-01. Retrieved 2010-10-25.
  25. ^ Ross J. Anderson (2001-03-23). Security Engineering. Wiley. p. 684. ISBN 0-471-38922-6.
  26. ^ "Microsoft Word for DOS 1.15". Archived from the original on 2013-05-14. Retrieved 2013-06-22.

Further reading