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A software bug is the common term used to describe an error, flaw, mistake, failure, or fault in a computer program or system that produces an incorrect or unexpected result, or causes it to behave in unintended ways. Most bugs arise from mistakes and errors made by people in either a program's source code or its design, and a few are caused by compilers producing incorrect code. A program that contains a large number of bugs, and/or bugs that seriously interfere with its functionality, is said to be buggy. Reports detailing bugs in a program are commonly known as bug reports, fault reports, problem reports, trouble reports, change requests, and so forth.

Bugs trigger errors that can in turn have a wide variety of ripple effects, with varying levels of inconvenience to the user of the program. Some bugs have only a subtle effect on the program's functionality, and may thus lie undetected for a long time. More serious bugs may cause the program to crash or freeze. Others qualify as security bugs and might for example enable a malicious user to bypass access controls in order to obtain unauthorized privileges.

The results of bugs may be extremely serious. Bugs in the code controlling the Therac-25 radiation therapy machine were directly responsible for some patient deaths in the 1980s. In 1996, the European Space Agency's US$1 billion prototype Ariane 5 rocket was destroyed less than a minute after launch, due to a bug in the on-board guidance computer program. In June 1994, a Royal Air Force Chinook crashed into the Mull of Kintyre, killing 29. This was initially dismissed as pilot error, but an investigation by Computer Weekly uncovered sufficient evidence to convince a House of Lords inquiry that it may have been caused by a software bug in the aircraft's engine control computer.^[1]

In 2002, a study commissioned by the US Department of Commerce' 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".^[2]

Etymology[link]

The concept that software might contain errors dates back to 1843 in Ada Byron's notes on the analytical engine in which she speaks of the difficulty of preparing program "cards" for Charles Babbage's Analytical engine:

... an analyzing 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.

Use of the term "bug" to describe inexplicable defects has been a part of engineering jargon for many decades and predates 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.^[3]

Baffle Ball, the first mechanical pinball game, was advertised as being "free of bugs" in 1931.^[4] Problems with military gear during World War II were referred to as bugs (or glitches).^[5]

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.^[6] A typical version of the story is given by this quote:^[7]

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 glitch's [sic] in a program a bug.

Hopper was not actually the one who found the insect, as she readily acknowledged. The date in the log book was 9 September 1947,^[8][9] although sometimes erroneously reported as 1945.^[10] The operators who did find it, including William "Bill" Burke, later of the Naval Weapons Laboratory, Dahlgren, Virginia,^[11] were familiar with the engineering term and, amused, kept the insect with the notation "First actual case of bug being found." Hopper loved to recount the story.^[12] This log book is on display in the Smithsonian National Museum of American History, complete with moth attached.^[9]

While it is certain that the Harvard Mark II operators did not coin the term "bug", it has been suggested that the incident contributed to the widespread use and acceptance of the term within the computer software lexicon. It was thought that they did coin the related term, "debug" though this is unlikely, since the Oxford English Dictionary entry for "debug" contains a use of "debugging" in the context of airplane engines in 1945. See: debugging.

How bugs get into software[link]

In software development projects, a "mistake" or "fault" can be committed at any stage during development. Bugs are a consequence of the nature of human factors in the programming task. They arise from oversights or mutual misunderstandings made by a software team during specification, design, coding, data entry and documentation. For example, in creating a relatively simple program to sort a list of words into alphabetical order, one's design might fail to consider what should happen when a word contains a hyphen. Perhaps, when converting the abstract design into the chosen programming language, one might inadvertently create an off-by-one error and fail to sort the last word in the list. Finally, when typing the resulting program into the computer, one might accidentally type a "<" where a ">" was intended, perhaps resulting in the words being sorted into reverse alphabetical order. More complex bugs can arise from unintended interactions between different parts of a computer program. This frequently occurs because computer programs can be complex — millions of lines long in some cases — often having been programmed by many people over a great length of time, so that programmers are unable to mentally track every possible way in which parts can interact. Another category of bug called a race condition.

Mistake metamorphism[link]

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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.^{[clarification needed]} 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'.^[13]

Different stages of a "mistake" in the entire cycle may be described by using the following terms:^[13]

• Mistake
• Anomaly
• Fault
• Failure
• Error
• Exception
• Crash
• Bug
• Defect
• Incident
• Side Effect

Prevention[link]

The software industry has put much effort into finding methods for preventing programmers from inadvertently introducing bugs while writing software.^[14][15] These include:

Programming style

While typos in the program code are often caught by the compiler, a bug usually appears 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. In some programming languages, so-called typos, especially of symbols or logical/mathematical operators, actually represent logic errors, since the mistyped constructs are accepted by the compiler with a meaning other than that which the programmer intended.

Programming techniques

Bugs often create inconsistencies in the internal data of a running program. Programs can be written to check the consistency of their own internal data while running. If an inconsistency is encountered, the program can immediately halt, so that the bug can be located and fixed. Alternatively, the program can simply inform the user, attempt to correct the inconsistency, and continue running.

Development methodologies

There are several schemes for managing programmer activity, so that fewer bugs are produced. Many of these fall under the discipline of software engineering (which addresses software design issues as well). For example, formal program specifications are used to state the exact behavior of programs, so that design bugs can be eliminated. Unfortunately, formal specifications are impractical or impossible^{[citation needed]} for anything but the shortest programs, because of problems of combinatorial explosion and indeterminacy^{[disambiguation needed ]}.

Programming language support

Programming languages often include features which help programmers prevent bugs, such as static type systems, restricted name spaces and modular programming, among others. 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. Depending on the language and implementation, this may be caught by the compiler or at run-time. In addition, many recently-invented languages have deliberately excluded features which can easily lead to bugs, at the expense of making code slower than it need be: the general principle being that, because of Moore's law, computers get faster and software engineers get slower; it is almost always better to write simpler, slower code than "clever", inscrutable code, especially considering that maintenance cost is considerable. 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.

Code analysis

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 the same kinds of mistakes 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.

Debugging[link]

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", has always been 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.^[16] As computer programs grow more complex, bugs become more common and difficult to fix. Often programmers spend more time and effort finding and fixing bugs than writing new code. Software testers are professionals whose primary task is to find bugs, or write code to support testing. On some projects, more resources can be spent on testing than in developing the program.

Usually, the most difficult part of debugging is finding the bug in the source code. Once it is found, correcting it is usually relatively easy. Programs known as debuggers exist to help programmers locate bugs by executing code line by line, watching variable values, and other features to observe program behavior. Without a debugger, code can be added so that messages or values can be written to a console (for example with printf in the C programming language) 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 modelling the execution process in one's head or on paper can often find these errors without ever needing to reproduce the bug as such, if it can be shown there is some faulty logic in its implementation.

But more typically, the first step in locating a bug is to reproduce it reliably. Once the bug is reproduced, the programmer can use a debugger or some other tool to monitor the execution of the program in the faulty region, and find the point at which the program went astray.

It is not always easy to reproduce bugs. Some are triggered by inputs to the program which 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 disappear when the program is run with a debugger; these are heisenbugs (humorously named after the Heisenberg uncertainty principle.)

Debugging is still a tedious task requiring considerable effort. Since the 1990s, particularly following the Ariane 5 Flight 501 disaster, there has been a renewed interest in the development of effective automated aids to debugging. For instance, methods of static code analysis by abstract interpretation have already made significant achievements, while still remaining much of a work in progress.

As with any creative act, sometimes a flash of inspiration will show a solution, but this is rare and, by definition, cannot be relied on.

There are also classes of bugs that have nothing to do with the code itself. If, for example, one relies on faulty documentation or hardware, the code may be written perfectly properly to what the documentation says, but the bug truly lies in the documentation or hardware, not the code. However, it is common to change the code instead of the other parts of the system, as the cost and time to change it is generally less. Embedded systems frequently have workarounds for hardware bugs, since to make a new version of a ROM is much cheaper than remanufacturing the hardware, especially if they are commodity items.

Bug management[link]

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It is common practice for software to be released with known bugs that are considered non-critical, that is, that do not affect most users' main experience with the product. While software products may, by definition, contain any number of unknown bugs, 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 ("if we had 200 bugs last week, we should have 100 this week"). Most big software projects maintain two lists of "known bugs"— those known to the software team, and those to be told to users. This is not dissimulation, but users are not concerned with the internal workings of the product. The second list informs users about bugs that are not fixed in the current release, or not fixed at all, and a workaround may be offered.

There are various reasons for not fixing bugs:

• The developers often don't have time or it is not economical to fix all non-severe bugs.
• The bug could be fixed in a new version or patch that is not yet released.
• The changes to the code required to fix the bug could be large, expensive, or delay finishing the project.
• Even seemingly simple fixes bring the chance of introducing new unknown bugs into the system. At the end of a test/fix cycle some managers may only allow the most critical bugs to be fixed.
• Users may be relying on the undocumented, buggy behavior, especially if scripts or macros rely on a behavior; it may introduce a breaking change.
• It's "not a bug". A misunderstanding has arisen between expected and provided behavior

Bugs are categorized by severity, and some companies tolerate low-severity non-critical bugs because they do not affect the proper operation of the system for most users. NASA's SATC managed to reduce the number of errors to fewer than 0.1 per 1000 lines of code (SLOC)^{[citation needed]} but this was not felt to be feasible for any real world projects.

The severity of a bug is not the same as its importance for fixing, and the two should be measured and managed separately. On a Microsoft Windows system a blue screen of death is rather severe, but if it only occurs in extreme circumstances, especially if they are well diagnosed and avoidable, it may be less important to fix than an icon not representing its function well, which though purely aesthetic may confuse thousands of users every single day. This balance, of course, depends on many factors; expert users have different expectations from novices, a niche market is different from a general consumer market, and so on. To better achieve this balance, some software developers use a formalized bug triage process (borrowing the medical term), in which each new bug is assigned a priority based on its severity, frequency, risk, and other predetermined factors.^{[citation needed]}

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".^[17] 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."^[18]

Like any other part of engineering management, bug management must be conducted carefully and intelligently because "what gets measured gets done"^[19] and managing purely by bug counts can have unintended consequences. If, for example, developers are rewarded by the number of bugs they fix, they will naturally fix the easiest bugs first— leaving the hardest, and probably most risky or critical, to the last possible moment. For example, a bug that allows a cracker to compromise a system may be neglected if it's difficult to fix. If the management ethos is to reward the number of bugs fixed, then some developers may quickly write sloppy code knowing they can fix the bugs later and be rewarded for it, whereas careful, perhaps "slower" developers do not get rewarded for the bugs that were never there.^{[citation needed]}

Security vulnerabilities[link]

Malicious software may attempt to exploit known vulnerabilities in a system – which may or may not be bugs. Viruses are not bugs in themselves – they are typically programs that are doing precisely what they were designed to do. However, viruses are occasionally referred to as such in the popular press.^{[citation needed]} In addition, it is often a security bug in a software program that allows viruses to work in the first place.

Common types of computer bugs[link]

• Conceptual error (code is syntactically correct, but the programmer or designer intended it to do something else)

Arithmetic bugs[link]

• Division by zero
• Arithmetic overflow or underflow
• Loss of arithmetic precision due to rounding or numerically unstable algorithms

Logic bugs[link]

• Infinite loops and infinite recursion
• Off by one error, counting one too many or too few when looping

Syntax bugs[link]

• 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. In simple cases often warned by the compiler; in many languages, deliberately guarded against by language syntax

Resource bugs[link]

• Null pointer dereference
• Using an uninitialized variable
• Using an otherwise valid instruction on the wrong data type (see packed decimal/binary coded decimal)
• Access violations
• Resource leaks, where a finite system resource such as memory or file handles are 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 bugs can form a security vulnerability.
• Excessive recursion which though logically valid causes stack overflow

Multi-threading programming bugs[link]

• Deadlock, where task A can't continue until task B finished, but at the same time, task B can't continue until task A finishes.
• Race condition, where the computer does not perform tasks in the order the programmer intended.
• Concurrency errors in critical sections, mutual exclusions and other features of concurrent processing. Time-of-check-to-time-of-use (TOCTOU) is a form of unprotected critical section.

Interfacing bugs[link]

• Incorrect API usage
• Incorrect protocol implementation
• Incorrect hardware handling

Performance bugs[link]

• Too high computational complexity of algorithm
• Random disk or memory access

Teamworking bugs[link]

• 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 the actual product

Well-known bugs[link]

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.)

In popular culture[link]

• In Robert A. Heinlein's 1966 novel The Moon Is a Harsh Mistress, computer technician Manuel Davis blames a real bug for a (non-existent) failure of supercomputer Mike, presenting a dead fly as evidence.
• In the 1968 novel 2001: A Space Odyssey (and the corresponding 1968 film), a spaceship's onboard computer, HAL 9000, attempts to kill all its crew members. In the followup 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 1984 song "99 Red Balloons" (though not in the original German version), "bugs in the software" lead to a computer mistaking a group of balloons for a nuclear missile and starting a nuclear war.
• 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.

See also[link]

Software Testing portal

• Anti-pattern
• Bit rot
• Bug tracking system
• ISO/IEC 9126, which classifies a bug as either a defect or a nonconformity
• One-line fix
• Orthogonal Defect Classification
• Racetrack problem
• Software defect indicator
• Software regression
• Unusual software bugs (schroedinbug, heisenbug, Bohr bug, and mandelbug)
• RISKS Digest

Notes[link]

Further reading[link]

• Allen, Mitch, May/Jun 2002 "Bug Tracking Basics: A beginner’s guide to reporting and tracking defects" The Software Testing & Quality Engineering Magazine. Vol. 4, Issue 3, pp. 20–24.

External links[link]

• Collection of Software Bugs (Thomas Huckle, TU München)
• Computer-Related Incidents with Commercial Aircraft (Peter B. Ladkin et al., Universität Bielefeld)
• An Investigation of the Therac-25 Accidents (Nancy Leveson, University of Washington and Clark S. Turner, University of California at Irvine)
• Fatal Dose: Radiation Deaths linked to AECL Computer Errors (Barbara Wade Rose, Canadian Coalition for Nuclear Responsibility)
• Software Horror Stories (Nachum Dershowitz)
• Picture of the "first computer bug" The error of this term is elaborated above. (Naval Historical Center)
• Page from 1947 log book with "first actual case of bug being found" (moth) (National Museum of American History)
• The First Computer Bug! An email from 1981 about Adm. Hopper's bug
• How to Report Bugs Effectively (Simon G. Tatham)
• Rates of Design Failure
• History's Worst Software Bugs
• Open source bug search engine
• Bug Isolation Project – This project is to track bugs of popular open source software. (Packages for Fedora available)

Cash out refinancing (in the case of real property) occurs when a loan is taken out on property already owned, and the loan amount is above and beyond the cost of transaction, payoff of existing liens, and related expenses.

Definition[link]

Strictly speaking all refinancing of debt is "cash-out", when funds retrieved are utilized for anything other than repaying an existing lien.

In the case of common usage of the term, cash out refinancing refers to when equity is liquidated from a property above and beyond sum of the payoff of existing loans held in lien on the property, loan fees, costs associated with the loan, taxes, insurance, tax reserves, insurance reserves, and in the past any other non-lien debt held in the name of the owner being paid by loan proceeds.

Example of Cash Out Refinancing[link]

A homeowner who owes $80,000 on a home valued at $200,000 has $120,000 in equity. That equity can be liquidated with a cash out refinance loan providing the loan is larger than $80,000.

The total amount of equity that can be withdrawn with a cash-out refinance is dependent on the mortgage lender, the cash-out refinance program, and other relative factors, such as the value of the home.

Related topics[link]

The opposite, "Rate-and-term" refinancing occurs when a better note rate, better loan terms, or both become available to an owner which restructures their debt portfolio as it relates to liens held against a subject property. Consolidating multiple loans into one loan without extracting cash is also a rate-and-term.

Loan-to-value limits, and other factors in loan approval determine how much cash can be taken out from the equity of any one property.

See also[link]

• California Proposition 13 (1978), U.S.
• Real estate bubble
• Inflation
• Home equity

External links[link]

• FHA Cash Out Refinance Fact Sheet

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