A software bug
is an error, flaw or fault
in a computer program
that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. The process of finding and fixing bugs is termed "debugging
" and often uses formal techniques or tools to pinpoint bugs, and since the 1950s, some computer systems have been designed to also deter, detect or auto-correct various computer bugs during operations.
The Middle English word bugge
is the basis for the terms "bugbear
" and "bugaboo
" as terms used for a monster.
The term "bug" to describe defects has been a part of engineering jargon since the 1870s and predates electronic computers and computer software; it may have originally been used in hardware engineering to describe mechanical malfunctions. For instance, Thomas Edison
wrote the following words in a letter to an associate in 1878:
It has been just so in all of my inventions. The first step is an intuition, and comes with a burst, then difficulties arise—this thing gives out and [it is] then that "Bugs"—as such little faults and difficulties are called—show themselves and months of intense watching, study and labor are requisite before commercial success or failure is certainly reached.
, the first mechanical pinball
game, was advertised as being "free of bugs" in 1931.
Problems with military gear during World War II
were referred to as bugs (or glitches
In a book published in 1942, Louise Dickinson Rich
, speaking of a powered ice cutting
machine, said, "Ice sawing was suspended until the creator could be brought in to take the bugs out of his darling."
A page from the Harvard Mark II
electromechanical computer's log, featuring a dead moth that was removed from the device.
The term "bug" was used in an account by computer pioneer Grace Hopper
, who publicized the cause of a malfunction in an early electromechanical computer.
A typical version of the story is:
In 1946, when Hopper was released from active duty, she joined the Harvard Faculty at the Computation Laboratory where she continued her work on the Mark II
and Mark III
. Operators traced an error in the Mark II to a moth
trapped in a relay, coining the term bug
. This bug was carefully removed and taped to the log book. Stemming from the first bug, today we call errors or glitches in a program a bug
Hopper did not find the bug, as she readily acknowledged. The date in the log book was September 9, 1947.
The operators who found it, including William "Bill" Burke, later of the Naval Weapons Laboratory
, Dahlgren, Virginia
were familiar with the engineering term and amusedly kept the insect with the notation "First actual case of bug being found." Hopper loved to recount the story.
This log book, complete with attached moth, is part of the collection of the Smithsonian National Museum of American History
The related term "debug
" also appears to predate its usage in computing: the Oxford English Dictionary'
s etymology of the word contains an attestation from 1945, in the context of aircraft engines.
... an analysing process must equally have been performed in order to furnish the Analytical Engine with the necessary operative data; and that herein may also lie a possible source of error. Granted that the actual mechanism is unerring in its processes, the cards may give it wrong orders.
"Bugs in the System" report
The Open Technology Institute, run by the group, New America,
released a report "Bugs in the System" in August 2016 stating that U.S. policymakers should make reforms to help researchers identify and address software bugs. The report "highlights the need for reform in the field of software vulnerability discovery and disclosure."
One of the report's authors said that Congress has not done enough to address cyber software vulnerability, even though Congress has passed a number of bills to combat the larger issue of cyber security.
Government researchers, companies, and cyber security experts are the people who typically discover software flaws. The report calls for reforming computer crime and copyright laws.
The Computer Fraud and Abuse Act, the Digital Millennium Copyright Act and the Electronic Communications Privacy Act criminalize and create civil penalties for actions that security researchers routinely engage in while conducting legitimate security research, the report said.
While the use of the term "bug" to describe software errors is common, many have suggested that it should be abandoned. One argument is that the word "bug" is divorced from a sense that a human being caused the problem, and instead implies that the defect arose on its own, leading to a push to abandon the term "bug" in favor of terms such as "defect", with limited success.
Since the 1970s Gary Kildall
somewhat humorously suggested to use the term "blunder".
In software engineering, mistake metamorphism
(from Greek meta
= "change", morph
= "form") refers to the evolution of a defect in the final stage of software deployment. Transformation of a "mistake" committed by an analyst in the early stages of the software development lifecycle, which leads to a "defect" in the final stage of the cycle has been called 'mistake metamorphism'.
Different stages of a "mistake" in the entire cycle may be described as "mistakes", "anomalies", "faults", "failures", "errors", "exceptions", "crashes", " glitches", "bugs", "defects", "incidents", or "side effects".
The software industry has put much effort into reducing bug counts.
Bugs usually appear when the programmer makes a logic error
. Various innovations in programming style
and defensive programming
are designed to make these bugs less likely, or easier to spot. Some typos, especially of symbols or logical/mathematical operators
, allow the program to operate incorrectly, while others such as a missing symbol or misspelled name may prevent the program from operating. Compiled languages can reveal some typos when the source code is compiled.
Several schemes assist managing programmer activity so that fewer bugs are produced. Software engineering
(which addresses software design issues as well) applies many techniques to prevent defects. For example, formal program specifications
state the exact behavior of programs so that design bugs may be eliminated. Unfortunately, formal specifications are impractical for anything but the shortest programs, because of problems of combinatorial explosion
involves writing a test for every function (unit) that a program is to perform.
In test-driven development
unit tests are written before the code and the code is not considered complete until all tests complete successfully.
Agile software development
involves frequent software releases with relatively small changes. Defects are revealed by user feedback.
Open source development allows anyone to examine source code. A school of thought popularized by Eric S. Raymond
as Linus's law
says that popular open-source software
has more chance of having few or no bugs than other software, because "given enough eyeballs, all bugs are shallow".
This assertion has been disputed, however: computer security specialist Elias Levy
wrote that "it is easy to hide vulnerabilities in complex, little understood and undocumented source code," because, "even if people are reviewing the code, that doesn't mean they're qualified to do so."
An example of this actually happening, accidentally, was the 2008 OpenSSL vulnerability in Debian
Programming language support
include features to help prevent bugs, such as static type systems
, restricted namespaces
and modular programming
. For example, when a programmer writes (pseudocode) LET REAL_VALUE PI = "THREE AND A BIT"
, although this may be syntactically correct, the code fails a type check
. Compiled languages catch this without having to run the program. Interpreted languages catch such errors at runtime. Some languages deliberately exclude features that easily lead to bugs, at the expense of slower performance: the general principle being that, it is almost always better to write simpler, slower code than inscrutable code that runs slightly faster, especially considering that maintenance cost
is substantial. For example, the Java programming language
does not support pointer
arithmetic; implementations of some languages such as Pascal
and scripting languages
often have runtime bounds checking
of arrays, at least in a debugging build.
Tools for code analysis
help developers by inspecting the program text beyond the compiler's capabilities to spot potential problems. Although in general the problem of finding all programming errors given a specification is not solvable (see halting problem
), these tools exploit the fact that human programmers tend to make certain kinds of simple mistakes often when writing software.
Tools to monitor the performance of the software as it is running, either specifically to find problems such as bottlenecks
or to give assurance as to correct working, may be embedded in the code explicitly (perhaps as simple as a statement saying PRINT "I AM HERE"
), or provided as tools. It is often a surprise to find where most of the time is taken by a piece of code, and this removal of assumptions might cause the code to be rewritten.
are people whose primary task is to find bugs, or write code to support testing. On some projects, more resources may be spent on testing than in developing the program.
Measurements during testing can provide an estimate of the number of likely bugs remaining; this becomes more reliable the longer a product is tested and developed.
The typical bug history (GNU Classpath
project data). A new bug submitted by the user is unconfirmed.
Once it has been reproduced by a developer, it is a confirmed
bug. The confirmed bugs are later fixed
. Bugs belonging to other categories (unreproducible, will not be fixed, etc.) are usually in the minority
Finding and fixing bugs, or debugging
, is a major part of computer programming
. Maurice Wilkes
, an early computing pioneer, described his realization in the late 1940s that much of the rest of his life would be spent finding mistakes in his own programs.
Usually, the most difficult part of debugging is finding the bug. Once it is found, correcting it is usually relatively easy. Programs known as debuggers
help programmers locate bugs by executing code line by line, watching variable values, and other features to observe program behavior. Without a debugger, code may be added so that messages or values may be written to a console or to a window or log file to trace program execution or show values.
However, even with the aid of a debugger, locating bugs is something of an art. It is not uncommon for a bug in one section of a program to cause failures in a completely different section,
thus making it especially difficult to track (for example, an error in a graphics rendering
routine causing a file I/O
routine to fail), in an apparently unrelated part of the system.
Sometimes, a bug is not an isolated flaw, but represents an error of thinking or planning on the part of the programmer. Such logic errors
require a section of the program to be overhauled or rewritten. As a part of code review
, stepping through the code and imagining or transcribing the execution process may often find errors without ever reproducing the bug as such.
More typically, the first step in locating a bug is to reproduce it reliably. Once the bug is reproducible, the programmer may use a debugger or other tool while reproducing the error to find the point at which the program went astray.
Some bugs are revealed by inputs that may be difficult for the programmer to re-create. One cause of the Therac-25
radiation machine deaths was a bug (specifically, a race condition
) that occurred only when the machine operator very rapidly entered a treatment plan; it took days of practice to become able to do this, so the bug did not manifest in testing or when the manufacturer attempted to duplicate it. Other bugs may stop occurring whenever the setup is augmented to help find the bug, such as running the program with a debugger; these are called heisenbugs
(humorously named after the Heisenberg uncertainty principle
Some classes of bugs have nothing to do with the code. Faulty documentation or hardware may lead to problems in system use, even though the code matches the documentation. In some cases, changes to the code eliminate the problem even though the code then no longer matches the documentation. Embedded systems
frequently work around
hardware bugs, since to make a new version of a ROM
is much cheaper than remanufacturing the hardware, especially if they are commodity items
Benchmark of bugs
To facilitate reproducible research on testing and debugging, researchers use curated benchmarks of bugs:
- the Siemens benchmark
- ManyBugs is a benchmark of 185 C bugs in nine open-source programs.
- Defects4J is a benchmark of 341 Java bugs from 5 open-source projects. It contains the corresponding patches, which cover a variety of patch type.
- BEARS is a benchmark of continuous integration build failures focusing on test failures. It has been created by monitoring builds from open-source projects on Travis CI.
Bug management includes the process of documenting, categorizing, assigning, reproducing, correcting and releasing the corrected code. Proposed changes to software – bugs as well as enhancement requests and even entire releases – are commonly tracked and managed using bug tracking systems
or issue tracking systems
The items added may be called defects, tickets, issues, or, following the agile development
paradigm, stories and epics. Categories may be objective, subjective or a combination, such as version number
, area of the software, severity and priority, as well as what type of issue it is, such as a feature request or a bug.
is the impact the bug has on system operation. This impact may be data loss, financial, loss of goodwill and wasted effort. Severity levels are not standardized. Impacts differ across industry. A crash in a video game has a totally different impact than a crash in a web browser, or real time monitoring system. For example, bug severity levels might be "crash or hang", "no workaround" (meaning there is no way the customer can accomplish a given task), "has workaround" (meaning the user can still accomplish the task), "visual defect" (for example, a missing image or displaced button or form element), or "documentation error". Some software publishers use more qualified severities such as "critical", "high", "low", "blocker" or "trivial".
The severity of a bug may be a separate category to its priority for fixing, and the two may be quantified and managed separately.
Priority controls where a bug falls on the list of planned changes. The priority is decided by each software producer. Priorities may be numerical, such as 1 through 5, or named, such as "critical", "high", "low", or "deferred". These rating scales may be similar or even identical to severity ratings, but are evaluated as a combination of the bug's severity with its estimated effort to fix; a bug with low severity but easy to fix may get a higher priority than a bug with moderate severity that requires excessive effort to fix. Priority ratings may be aligned with product releases, such as "critical" priority indicating all the bugs that must be fixed before the next software release.
It is common practice to release software with known, low-priority bugs. Most big software projects maintain two lists of "known bugs" – those known to the software team, and those to be told to users.
The second list informs users about bugs that are not fixed in a specific release and workarounds
may be offered. Releases are of different kinds. Bugs of sufficiently high priority may warrant a special release of part of the code containing only modules with those fixes. These are known as patches
. Most releases include a mixture of behavior changes and multiple bug fixes. Releases that emphasize bug fixes are known as maintenance
releases. Releases that emphasize feature additions/changes are known as major releases and often have names to distinguish the new features from the old.
Reasons that a software publisher opts not to patch or even fix a particular bug include:
- A deadline must be met and resources are insufficient to fix all bugs by the deadline.
- The bug is already fixed in an upcoming release, and it is not of high priority.
- The changes required to fix the bug are too costly or affect too many other components, requiring a major testing activity.
- It may be suspected, or known, that some users are relying on the existing buggy behavior; a proposed fix may introduce a breaking change.
- The problem is in an area that will be obsolete with an upcoming release; fixing it is unnecessary.
- It's "not a bug". A misunderstanding has arisen between expected and perceived behavior, when such misunderstanding is not due to confusion arising from design flaws, or faulty documentation.
This section contains embedded lists
that may be poorly defined, unverified or indiscriminate
. Please help to clean it up
to meet Wikipedia's quality standards. Where appropriate, incorporate items into the main body of the article. (August 2015)
In software development projects, a "mistake" or "fault" may be introduced at any stage. Bugs arise from oversights or misunderstandings made by a software team during specification, design, coding, data entry or documentation. For example, a relatively simple program to alphabetize a list of words, the design might fail to consider what should happen when a word contains a hyphen
. Or when converting an abstract design into code, the coder might inadvertently create an off-by-one error
and fail to sort the last word in a list. Errors may be as simple as a typing error: a "<" where a ">" was intended.
Another category of bug is called a race condition
that may occur when programs have multiple components executing at the same time. If the components interact in a different order than the developer intended, they could interfere with each other and stop the program from completing its tasks. These bugs may be difficult to detect or anticipate, since they may not occur during every execution of a program.
Conceptual errors are a developer's misunderstanding of what the software must do. The resulting software may perform according to the developer's understanding, but not what is really needed. Other types:
Use of the wrong operator, such as performing assignment instead of equality test
. For example, in some languages x=5 will set the value of x to 5 while x==5 will check whether x is currently 5 or some other number. Interpreted languages allow such code to fail. Compiled languages can catch such errors before testing begins.
- Incorrect API usage.
- Incorrect protocol implementation.
- Incorrect hardware handling.
- Incorrect assumptions of a particular platform.
- Incompatible systems. A new API or communications protocol may seem to work when two systems use different versions, but errors may occur when a function or feature implemented in one version is changed or missing in another. In production systems which must run continually, shutting down the entire system for a major update may not be possible, such as in the telecommunication industry or the internet. In this case, smaller segments of a large system are upgraded individually, to minimize disruption to a large network. However, some sections could be overlooked and not upgraded, and cause compatibility errors which may be difficult to find and repair.
- Incorrect code annotations
- Unpropagated updates; e.g. programmer changes "myAdd" but forgets to change "mySubtract", which uses the same algorithm. These errors are mitigated by the Don't Repeat Yourself philosophy.
- Comments out of date or incorrect: many programmers assume the comments accurately describe the code.
- Differences between documentation and product.
The amount and type of damage a software bug may cause naturally affects decision-making, processes and policy regarding software quality. In applications such as manned space travel
or automotive safety
, since software flaws have the potential to cause human injury or even death, such software will have far more scrutiny and quality control than, for example, an online shopping website. In applications such as banking, where software flaws have the potential to cause serious financial damage to a bank or its customers, quality control is also more important than, say, a photo editing application. NASA's Software Assurance Technology Center
managed to reduce the number of errors to fewer than 0.1 per 1000 lines of code (SLOC
but this was not felt to be feasible for projects in the business world.
According to a NASA study on "Flight Software Complexity
", "an exceptionally good software development process can keep defects down to as low as 1 defect per 10,000 lines of code."
Other than the damage caused by bugs, some of their cost is due to the effort invested in fixing them. In 1978, Lientz and al. showed that the median of projects invest 17 per cent of the development effort in bug fixing.
In research in 2020 on GitHub
repositories showed the median is 20%.
A number of software bugs have become well-known, usually due to their severity: examples include various space and military aircraft crashes. Possibly the most famous bug is the Year 2000 problem
, also known as the Y2K bug, in which it was feared that worldwide economic collapse would happen at the start of the year 2000 as a result of computers thinking it was 1900. (In the end, no major problems occurred.) The 2012 stock trading disruption
involved one such incompatibility between the old API and a new API.
In popular culture
- In both the 1968 novel 2001: A Space Odyssey and the corresponding 1968 film 2001: A Space Odyssey, a spaceship's onboard computer, HAL 9000, attempts to kill all its crew members. In the follow-up 1982 novel, 2010: Odyssey Two, and the accompanying 1984 film, 2010, it is revealed that this action was caused by the computer having been programmed with two conflicting objectives: to fully disclose all its information, and to keep the true purpose of the flight secret from the crew; this conflict caused HAL to become paranoid and eventually homicidal.
- In the English version of the Nena 1983 song 99 Luftballons (99 Red Balloons) as a result of "bugs in the software", a release of a group of 99 red balloons are mistaken for an enemy nuclear missile launch, requiring an equivalent launch response, resulting in catastrophe.
- In the 1999 American comedy Office Space, three employees attempt to exploit their company's preoccupation with fixing the Y2K computer bug by infecting the company's computer system with a virus that sends rounded off pennies to a separate bank account. The plan backfires as the virus itself has its own bug, which sends large amounts of money to the account prematurely.
- The 2004 novel The Bug, by Ellen Ullman, is about a programmer's attempt to find an elusive bug in a database application.
- The 2008 Canadian film Control Alt Delete is about a computer programmer at the end of 1999 struggling to fix bugs at his company related to the year 2000 problem.
- ^ Mittal, Varun; Aditya, Shivam (January 1, 2015). "Recent Developments in the Field of Bug Fixing". Procedia Computer Science. International Conference on Computer, Communication and Convergence (ICCC 2015). 48: 288–297. doi:10.1016/j.procs.2015.04.184. ISSN 1877-0509.
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- ^ Computerworld staff (September 3, 2011). "Moth in the machine: Debugging the origins of 'bug'". Computerworld. Archived from the original on August 25, 2015.
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- ^ a b "Log Book With Computer Bug Archived March 23, 2017, at the Wayback Machine", National Museum of American History, Smithsonian Institution.
- ^ "The First "Computer Bug", Naval Historical Center. But note the Harvard Mark II computer was not complete until the summer of 1947.
- ^ IEEE Annals of the History of Computing, Vol 22 Issue 1, 2000
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- ^ Kildall, Gary Arlen (August 2, 2016) . Kildall, Scott; Kildall, Kristin (eds.). "Computer Connections: People, Places, and Events in the Evolution of the Personal Computer Industry" (Manuscript, part 1). Kildall Family: 14–15. Archived from the original on November 17, 2016. Retrieved November 17, 2016.
- ^ a b "Testing experience : te : the magazine for professional testers". Testing Experience. Germany: testingexperience: 42. March 2012. ISSN 1866-5705. (subscription required)
- ^ Huizinga, Dorota; Kolawa, Adam (2007). Automated Defect Prevention: Best Practices in Software Management. Wiley-IEEE Computer Society Press. p. 426. ISBN 978-0-470-04212-0. Archived from the original on April 25, 2012.
- ^ McDonald, Marc; Musson, Robert; Smith, Ross (2007). The Practical Guide to Defect Prevention. Microsoft Press. p. 480. ISBN 978-0-7356-2253-1.
- ^ "Release Early, Release Often" Archived May 14, 2011, at the Wayback Machine, Eric S. Raymond, The Cathedral and the Bazaar
- ^ "Wide Open Source" Archived September 29, 2007, at the Wayback Machine, Elias Levy, SecurityFocus, April 17, 2000
- ^ Maurice Wilkes Quotes
- ^ "PolySpace Technologies history". christele.faure.pagesperso-orange.fr. Retrieved August 1, 2019.
- ^ Le Goues, Claire; Holtschulte, Neal; Smith, Edward K.; Brun, Yuriy; Devanbu, Premkumar; Forrest, Stephanie; Weimer, Westley (2015). "The ManyBugs and IntroClass Benchmarks for Automated Repair of C Programs". IEEE Transactions on Software Engineering. 41 (12): 1236–1256. doi:10.1109/TSE.2015.2454513. ISSN 0098-5589.
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- ^ "The Next Generation 1996 Lexicon A to Z: Slipstream Release". Next Generation. No. 15. Imagine Media. March 1996. p. 41.
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- ^ RFC 1263: "TCP Extensions Considered Harmful" quote: "the time to distribute the new version of the protocol to all hosts can be quite long (forever in fact). ... If there is the slightest incompatibly between old and new versions, chaos can result."
- ^ Yu, Zhongxing; Bai, Chenggang; Seinturier, Lionel; Monperrus, Martin (2019). "Characterizing the Usage, Evolution and Impact of Java Annotations in Practice". IEEE Transactions on Software Engineering: 1. arXiv:1805.01965. doi:10.1109/TSE.2019.2910516. S2CID 102351817.
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- ^ Ullman, Ellen (2004). The Bug. Picador. ISBN 978-1-250-00249-5.
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