The effects of a software bug range from minor (such as a misspelled word in the user interface) to severe (such as frequent crashing).
In 2002, a study commissioned by the US Department of Commerce's National Institute of Standards and Technology concluded that "software bugs, or errors, are so prevalent and so detrimental that they cost the US economy an estimated $59 billion annually, or about 0.6 percent of the gross domestic product".[1]
Since the 1950s, some computer systems have been designed to detect or auto-correct various software errors during operations.
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'.[2]
Different stages of a mistake in the development cycle may be described as mistake,[3]: 31
anomaly,[3]: 10
fault,[3]: 31
failure,[3]: 31
error,[3]: 31
exception,[3]: 31
crash,[3]: 22
glitch,
bug,[3]: 14
defect,
incident,[3]: 39
or side effect.
Sometimes the use of bug to describe the behavior of software is contentious due to perception. Some suggest that the term should be abandoned; replaced with defect or error.
Some contend that bug implies that the defect arose on its own and push to use defect instead since it more clearly connotates caused by a human.[8]
Some contend that bug may be used to coverup an intentional design decision. In 2011, after receiving scrutiny from US Senator Al Franken for recording and storing users' locations in unencrypted files,[9]
Apple called the behavior a bug. However, Justin Brookman of the Center for Democracy and Technology directly challenged that portrayal, stating "I'm glad that they are fixing what they call bugs, but I take exception with their strong denial that they track users."[10]
Newer programming languages tend to be designed to prevent common bugs based on vulnerabilities of existing languages. Lessons learned from older languages such as BASIC and C are used to inform the design of later languages such as C# and Rust.
is syntactically correct, but fails type checking since the right side, a string, cannot be assigned to a float variable. Compilation fails – forcing this defect to be fixed before development progress can resume. With an interpreted language, a failure would not occur until later at runtime.
Some languages exclude features that easily lead to bugs, at the expense of slower performance – the principle being that it is usually better to write simpler, slower correct code than complicated, buggy code. For example, the Java does not support pointer arithmetic which is generally fast, but is considered dangerous; relatively easy to cause a major bug.
Some languages include features that add runtime overhead in order to prevent some bugs. For example, many languages include runtime bounds checking and a way to handle out-of-bounds conditions instead of crashing.
For example, a bug may be caused by a relatively minor, typographical error (typo) in the code. For example, this code executes function foo only if conditionis true.
if (condition) foo();
But this code always executes foo:
if (condition); foo();
A convention that tends to prevent this particular issue is to require braces for a block even if it has just one line.
if (condition) {
foo();
}
Enforcement of conventions may be manual (i.e. via code review) or via automated tools.
Specification
Some contend that writing a program specification which states the behavior of a program, can prevent bugs.
Some contend that formal specifications are impractical for anything but the shortest programs, because of problems of combinatorial explosion and indeterminacy.
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.[citation needed]
Agile practices
Agile software development may involve frequent software releases with relatively small changes. Defects are revealed by user feedback.
With test-driven development (TDD), unit tests are written while writing the production code, and the production code is not considered complete until all tests complete successfully.
Static analysis
Tools for static 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.
Instrumentation
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.
Open source
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".[13] 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."[14] An example of an open-source software bug was the 2008 OpenSSL vulnerability in Debian.
Debugging can be a significant part of the software development lifecycle. Maurice Wilkes, an early computing pioneer, described his realization in the late 1940s that
“a good part of the remainder of my life was going to be spent in finding errors in my own programs”.[15]
A program known as a debugger can help a programmer find faulty code by examining the inner workings of a program such as executing code line-by-line and viewing variable values.
As an alternative to using a debugger, code may be instrumented with logic to output debug information to trace program execution and view values. Output is typically to console, window, log file or a hardware output (i.e. LED).
Some contend that locating a bug is something of an art.
It is not uncommon for a bug in one section of a program to cause failures in a different section,[citation needed] thus making it difficult to track, in an apparently unrelated part of the system. For example, an error in a graphics rendering routine causing a file I/O routine to fail.
Sometimes, the most difficult part of debugging is finding the cause of the bug. Once found, correcting the problem is sometimes easy if not trivial.
Sometimes, a bug is not an isolated flaw, but represents an error of thinking or planning on the part of the programmers. Often, such a logic error requires a section of the program to be overhauled or rewritten.
Some contend that 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.
Typically, the first step in locating a bug is to reproduce it reliably. If unable to reproduce the issue, a programmer cannot find the cause of the bug and therefore cannot fix it.
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).
Often, bugs come about during coding, but faulty design documentation may cause a bug.
In some cases, changes to the code may eliminate the problem even though the code then no longer matches the documentation.
In an embedded system, the software is often modified to work around a hardware bug since it's cheaper than modifying the hardware.
Management
Example bug history (GNU Classpath project data). A new bug is initially unconfirmed. Once reproducibility is confirmed, it is changed to confirmed. Once the issue is resolved, it is changed to fixed.
Bugs are managed via activities like documenting, categorizing, assigning, reproducing, correcting and releasing the corrected code.
A tracked item is often called bug, defect, ticket, issue, feature, or for agile software development, story or epic. Items are often categorized by aspects such as severity, priority and version number.
In a process sometimes called triage, choices are made for each bug about whether and when to fix it based on information such as the bug's severity and priority and external factors such as development schedules. Triage generally does not include investigation into cause. Triage may occur regularly. Triage generally consists of reviewing new bugs since the previous triage and maybe all open bugs. Attendees may include project manager, development manager, test manager, build manager, and technical experts.[18][19]
Severity
Severity is a measure of impact the bug has.[20] This impact may be data loss, financial, loss of goodwill and wasted effort. Severity levels are not standardized, but differ by context such as industry and tracking tool. For example, a crash in a video game has a different impact than a crash in a bank server. Severity levels might be crash or hang, no workaround (user cannot accomplish a task), has workaround (user can still accomplish the task), visual defect (a misspelling for example), or documentation error. Another example set of severities: critical, high, low, blocker, trivial.[21] The severity of a bug may be a separate category to its priority for fixing, or the two may be quantified and managed separately.
A bug severe enough to delay the release of the product is called a show stopper.[22][23]
Priority
Priority describes the importance of resolving the bug in relation to other bugs. Priorities might be numerical, such as 1 through 5, or named, such as critical, high, low, and deferred. The values might be similar or identical to severity ratings, even though priority is a different aspect.
Priority may be a combination of the bug's severity with the level of 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 significantly more effort to fix.
Patch
Bugs of sufficiently high priority may warrant a special release which is sometimes called a patch.
Maintenance release
A software release that emphasizes bug fixes may be called a maintenance release – to differentiate it from a release that emphasizes new features or other changes.
Known issue
It is common practice to release software with known, low-priority bugs or other issues. Possible reasons include but are not limited to:
A deadline must be met and resources are insufficient to fix all bugs by the deadline[24]
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, it's a feature"[25] A misunderstanding exists between expected and actual behavior or undocumented feature
Implications
The amount and type of damage a software bug may cause affects decision-making, processes and policy regarding software quality. In applications such as human spaceflight, aviation, nuclear power, health care, public transport 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.
Other than the damage caused by bugs, some of their cost is due to the effort invested in fixing them. In 1978, Lientz et al. showed that the median of projects invest 17 percent of the development effort in bug fixing.[26] In 2020, research on GitHub repositories showed the median is 20%.[27]
Cost
In 1994, NASA's Goddard Space Flight Center managed to reduce their average number of errors from 4.5 per 1000 lines of code (SLOC) down to 1 per 1000 SLOC.[28]
Another study in 1990 reported that exceptionally good software development processes can achieve deployment failure rates as low as 0.1 per 1000 SLOC.[29] This figure is iterated in literature such as Code Complete by Steve McConnell,[30] and the NASA study on Flight Software Complexity.[31]
Some projects even attained zero defects: the firmware in the IBM Wheelwriter typewriter which consists of 63,000 SLOC, and the Space Shuttle software with 500,000 SLOC.[29]
Benchmark
To facilitate reproducible research on testing and debugging, researchers use curated benchmarks of bugs:
the Siemens benchmark
ManyBugs[32] is a benchmark of 185 C bugs in nine open-source programs.
Defects4J[33] is a benchmark of 341 Java bugs from 5 open-source projects. It contains the corresponding patches, which cover a variety of patch type.
Types
Some notable types of bugs:
Design error
A bug can be caused by insufficient or incorrect design based on the specification. For example, given that the specification is to alphabetize a list of words, a design bug might occur if the design does not account for symbols; resulting in incorrect alphabetization of words with symbols.
Arithmetic
Numerical operations can result in unexpected output, slow processing, or crashing.[34]
Such a bug can be from a lack of awareness of the qualities of the data storage such as a loss of precision due to rounding, numerically unstable algorithms, arithmetic overflow and underflow, or from lack of awareness of how calculations are handled by different software coding languages such as division by zero which in some languages may throw an exception, and in others may return a special value such as NaN or infinity.
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[35] or the internet.[36][37][38] 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.
Concurrency
Deadlock – a task cannot continue until a second finishes, but at the same time, the second cannot continue until the first finishes.
Race condition – multiple simultaneous tasks compete for resources.
Resource leaks, where a finite system resource (such as memory or file handles) become exhausted by repeated allocation without release.
Buffer overflow, in which a program tries to store data past the end of allocated storage. This may or may not lead to an access violation or storage violation. These are frequently security bugs.
Use of the wrong token, 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.
Teamwork
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.
In politics
"Bugs in the System" report
The Open Technology Institute, run by the group, New America,[39] 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."[40] 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.[40]
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.[40]
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.[40]
In both the 1968 novel 2001: A Space Odyssey and the corresponding film of the same name, the 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: The Year We Make Contact, 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 and resulting in catastrophe.
In the 1999 American comedy Office Space, three employees attempt (unsuccessfully) to exploit their company's preoccupation with the Y2K computer bug using a computer virus that sends rounded-off fractions of a penny to their bank account—a long-known technique described as salami slicing.
The 2004 novel The Bug, by Ellen Ullman, is about a programmer's attempt to find an elusive bug in a database application.[41]
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.
^"Testing experience : te : the magazine for professional testers". Testing Experience. Germany: testingexperience: 42. March 2012. ISSN1866-5705. (subscription required)
^Gerard Holzmann (March 5, 2009). "Appendix D – Software Complexity"(PDF). Final Report: NASA Study on Flight Software Complexity (Daniel L. Dvorak (Ed.)). NASA Office of Chief Engineer Technical Excellence Program.
^Just, René; Jalali, Darioush; Ernst, Michael D. (2014). "Defects4J: a database of existing faults to enable controlled testing studies for Java programs". Proceedings of the 2014 International Symposium on Software Testing and Analysis – ISSTA 2014. pp. 437–440. CiteSeerX10.1.1.646.3086. doi:10.1145/2610384.2628055. ISBN9781450326452. S2CID12796895.
^Anthony Di Franco; Hui Guo; Cindy Rubio-González (November 23, 2017). A comprehensive study of real-world numerical bug characteristics. 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE. doi:10.1109/ASE.2017.8115662.
^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."
^Wilson, Andi; Schulman, Ross; Bankston, Kevin; Herr, Trey. "Bugs in the System"(PDF). Open Policy Institute. Archived(PDF) from the original on September 21, 2016. Retrieved August 22, 2016.
