• Organizations vary considerably in how they assign responsibility for QA and testing. Sometimes they're the combined responsibility of one group or individual. Also common are project teams that include a mix of testers and developers who work closely together, with overall QA processes monitored by project managers. It will depend on what best fits an organization's size and business structure.

• Media reports in January of 2005 detailed severe problems with a $170 million high-profile U.S. government IT systems project. Software testing was one of the five major problem areas according to a report of the commission reviewing the project. In March of 2005 it was decided to scrap the entire project.
• In July 2004 newspapers reported that a new government welfare management system in Canada costing several hundred million dollars was unable to handle a simple benefits rate increase after being put into live operation. Reportedly the original contract allowed for only 6 weeks of acceptance testing and the system was never tested for its ability to handle a rate increase.
• Millions of bank accounts were impacted by errors due to installation of inadequately tested software code in the transaction processing system of a major North American bank, according to mid-2004 news reports. Articles about the incident stated that it took two weeks to fix all the resulting errors, that additional problems resulted when the incident drew a large number of e-mail phishing attacks against the bank's customers, and that the total cost of the incident could exceed $100 million.
• A bug in site management software utilized by companies with a significant percentage of worldwide web traffic was reported in May of 2004. The bug resulted in performance problems for many of the sites simultaneously and required disabling of the software until the bug was fixed.
• According to news reports in April of 2004, a software bug was determined to be a major contributor to the 2003 Northeast blackout, the worst power system failure in North American history. The failure involved loss of electrical power to 50 million customers, forced shutdown of 100 power plants, and economic losses estimated at $6 billion. The bug was reportedly in one utility company's vendor-supplied power monitoring and management system, which was unable to correctly handle and report on an unusual confluence of initially localized events. The error was found and corrected after examining millions of lines of code.
• In early 2004, news reports revealed the intentional use of a software bug as a counter-espionage tool. According to the report, in the early 1980's one nation surreptitiously allowed a hostile nation's espionage service to steal a version of sophisticated industrial software that had intentionally-added flaws. This eventually resulted in major industrial disruption in the country that used the stolen flawed software.
• A major U.S. retailer was reportedly hit with a large government fine in October of 2003 due to web site errors that enabled customers to view one anothers' online orders.
• News stories in the fall of 2003 stated that a manufacturing company recalled all their transportation products in order to fix a software problem causing instability in certain circumstances. The company found and reported the bug itself and initiated the recall procedure in which a software upgrade fixed the problems.
• In August of 2003 a U.S. court ruled that a lawsuit against a large online brokerage company could proceed; the lawsuit reportedly involved claims that the company was not fixing system problems that sometimes resulted in failed stock trades, based on the experiences of 4 plaintiffs during an 8-month period. A previous lower court's ruling that "...six miscues out of more than 400 trades does not indicate negligence." was invalidated.
• In April of 2003 it was announced that a large student loan company in the U.S. made a software error in calculating the monthly payments on 800,000 loans. Although borrowers were to be notified of an increase in their required payments, the company will still reportedly lose $8 million in interest. The error was uncovered when borrowers began reporting inconsistencies in their bills.
• News reports in February of 2003 revealed that the U.S. Treasury Department mailed 50,000 Social Security checks without any beneficiary names. A spokesperson indicated that the missing names were due to an error in a software change. Replacement checks were subsequently mailed out with the problem corrected, and recipients were then able to cash their Social Security checks.
• In March of 2002 it was reported that software bugs in Britain's national tax system resulted in more than 100,000 erroneous tax overcharges. The problem was partly attributed to the difficulty of testing the integration of multiple systems.
• A newspaper columnist reported in July 2001 that a serious flaw was found in off-the-shelf software that had long been used in systems for tracking certain U.S. nuclear materials. The same software had been recently donated to another country to be used in tracking their own nuclear materials, and it was not until scientists in that country discovered the problem, and shared the information, that U.S. officials became aware of the problems.
• According to newspaper stories in mid-2001, a major systems development contractor was fired and sued over problems with a large retirement plan management system. According to the reports, the client claimed that system deliveries were late, the software had excessive defects, and it caused other systems to crash.
• In January of 2001 newspapers reported that a major European railroad was hit by the aftereffects of the Y2K bug. The company found that many of their newer trains would not run due to their inability to recognize the date '31/12/2000'; the trains were started by altering the control system's date settings.
• News reports in September of 2000 told of a software vendor settling a lawsuit with a large mortgage lender; the vendor had reportedly delivered an online mortgage processing system that did not meet specifications, was delivered late, and didn't work.
• In early 2000, major problems were reported with a new computer system in a large suburban U.S. public school district with 100,000+ students; problems included 10,000 erroneous report cards and students left stranded by failed class registration systems; the district's CIO was fired. The school district decided to reinstate it's original 25-year old system for at least a year until the bugs were worked out of the new system by the software vendors.
• In October of 1999 the $125 million NASA Mars Climate Orbiter spacecraft was believed to be lost in space due to a simple data conversion error. It was determined that spacecraft software used certain data in English units that should have been in metric units. Among other tasks, the orbiter was to serve as a communications relay for the Mars Polar Lander mission, which failed for unknown reasons in December 1999. Several investigating panels were convened to determine the process failures that allowed the error to go undetected.
• Bugs in software supporting a large commercial high-speed data network affected 70,000 business customers over a period of 8 days in August of 1999. Among those affected was the electronic trading system of the largest U.S. futures exchange, which was shut down for most of a week as a result of the outages.
• In April of 1999 a software bug caused the failure of a $1.2 billion U.S. military satellite launch, the costliest unmanned accident in the history of Cape Canaveral launches. The failure was the latest in a string of launch failures, triggering a complete military and industry review of U.S. space launch programs, including software integration and testing processes. Congressional oversight hearings were requested.
• A small town in Illinois in the U.S. received an unusually large monthly electric bill of $7 million in March of 1999. This was about 700 times larger than its normal bill. It turned out to be due to bugs in new software that had been purchased by the local power company to deal with Y2K software issues.
• In early 1999 a major computer game company recalled all copies of a popular new product due to software problems. The company made a public apology for releasing a product before it was ready.
• The computer system of a major online U.S. stock trading service failed during trading hours several times over a period of days in February of 1999 according to nationwide news reports. The problem was reportedly due to bugs in a software upgrade intended to speed online trade confirmations.
• In April of 1998 a major U.S. data communications network failed for 24 hours, crippling a large part of some U.S. credit card transaction authorization systems as well as other large U.S. bank, retail, and government data systems. The cause was eventually traced to a software bug.
• January 1998 news reports told of software problems at a major U.S. telecommunications company that resulted in no charges for long distance calls for a month for 400,000 customers. The problem went undetected until customers called up with questions about their bills.
• In November of 1997 the stock of a major health industry company dropped 60% due to reports of failures in computer billing systems, problems with a large database conversion, and inadequate software testing. It was reported that more than $100,000,000 in receivables had to be written off and that multi-million dollar fines were levied on the company by government agencies.
• A retail store chain filed suit in August of 1997 against a transaction processing system vendor (not a credit card company) due to the software's inability to handle credit cards with year 2000 expiration dates.
• In August of 1997 one of the leading consumer credit reporting companies reportedly shut down their new public web site after less than two days of operation due to software problems. The new site allowed web site visitors instant access, for a small fee, to their personal credit reports. However, a number of initial users ended up viewing each others' reports instead of their own, resulting in irate customers and nationwide publicity. The problem was attributed to "...unexpectedly high demand from consumers and faulty software that routed the files to the wrong computers."
• In November of 1996, newspapers reported that software bugs caused the 411 telephone information system of one of the U.S. RBOC's to fail for most of a day. Most of the 2000 operators had to search through phone books instead of using their 13,000,000-listing database. The bugs were introduced by new software modifications and the problem software had been installed on both the production and backup systems. A spokesman for the software vendor reportedly stated that 'It had nothing to do with the integrity of the software. It was human error.'
• On June 4 1996 the first flight of the European Space Agency's new Ariane 5 rocket failed shortly after launching, resulting in an estimated uninsured loss of a half billion dollars. It was reportedly due to the lack of exception handling of a floating-point error in a conversion from a 64-bit integer to a 16-bit signed integer.
• Software bugs caused the bank accounts of 823 customers of a major U.S. bank to be credited with $924,844,208.32 each in May of 1996, according to newspaper reports. The American Bankers Association claimed it was the largest such error in banking history. A bank spokesman said the programming errors were corrected and all funds were recovered.
• Software bugs in a Soviet early-warning monitoring system nearly brought on nuclear war in 1983, according to news reports in early 1999. The software was supposed to filter out false missile detections caused by Soviet satellites picking up sunlight reflections off cloud-tops, but failed to do so. Disaster was averted when a Soviet commander, based on what he said was a '...funny feeling in my gut', decided the apparent missile attack was a false alarm. The filtering software code was rewritten.

Which projects may not need independent test staff? The answer depends on the size and context of the project, the risks, the development methodology, the skill and experience of the developers, and other factors. For instance, if the project is a short-term, small, low risk project, with highly experienced programmers utilizing thorough unit testing or test-first development, then test engineers may not be required for the project to succeed.

In some cases an IT organization may be too small or new to have a testing staff even if the situation calls for it. In these circumstances it may be appropriate to instead use contractors or outsourcing, or adjust the project management and development approach (by switching to more senior developers and agile test-first development, for example). Inexperienced managers sometimes gamble on the success of a project by skipping thorough testing or having programmers do post-development functional testing of their own work, a decidedly high risk gamble.

For non-trivial-size projects or projects with non-trivial risks, a testing staff is usually necessary. As in any business, the use of personnel with specialized skills enhances an organization's ability to be successful in large, complex, or difficult tasks. It allows for both a) deeper and stronger skills and b) the contribution of differing perspectives. For example, programmers typically have the perspective of 'what are the technical issues in making this functionality work?'. A test engineer typically has the perspective of 'what might go wrong with this functionality, and how can we ensure it meets expectations?'. Technical people who can be highly effective in approaching tasks from both of those perspectives are rare, which is why, sooner or later, organizations bring in test specialists.

• Where the risk is lower, management and organizational buy-in and QA implementation may be a slower, step-at-a-time process. QA processes should be balanced with productivity so as to keep bureaucracy from getting out of hand.
• For small groups or projects, a more ad-hoc process may be appropriate, depending on the type of customers and projects. A lot will depend on team leads or managers, feedback to developers, and ensuring adequate communications among customers, managers, developers, and testers.
• The most value for effort will often be in (a) requirements management processes, with a goal of clear, complete, testable requirement specifications embodied in requirements or design documentation, or in 'agile'-type environments extensive continuous coordination with end-users, (b) design inspections and code inspections, and (c) post-mortems/retrospectives.
• Other possibilities include incremental self-managed team approaches such as 'Kaizen' methods of continuous process improvement, the Deming-Shewhart Plan-Do-Check-Act cycle, and others.

• Black box testing - not based on any knowledge of internal design or code. Tests are based on requirements and functionality.
• White box testing - based on knowledge of the internal logic of an application's code. Tests are based on coverage of code statements, branches, paths, conditions.
• unit testing - the most 'micro' scale of testing; to test particular functions or code modules. Typically done by the programmer and not by testers, as it requires detailed knowledge of the internal program design and code. Not always easily done unless the application has a well-designed architecture with tight code; may require developing test driver modules or test harnesses.
• incremental integration testing - continuous testing of an application as new functionality is added; requires that various aspects of an application's functionality be independent enough to work separately before all parts of the program are completed, or that test drivers be developed as needed; done by programmers or by testers.
• integration testing - testing of combined parts of an application to determine if they function together correctly. The 'parts' can be code modules, individual applications, client and server applications on a network, etc. This type of testing is especially relevant to client/server and distributed systems.
• functional testing - black-box type testing geared to functional requirements of an application; this type of testing should be done by testers. This doesn't mean that the programmers shouldn't check that their code works before releasing it (which of course applies to any stage of testing.)
• system testing - black-box type testing that is based on overall requirements specifications; covers all combined parts of a system.
• end-to-end testing - similar to system testing; the 'macro' end of the test scale; involves testing of a complete application environment in a situation that mimics real-world use, such as interacting with a database, using network communications, or interacting with other hardware, applications, or systems if appropriate.
• sanity testing or smoke testing - typically an initial testing effort to determine if a new software version is performing well enough to accept it for a major testing effort. For example, if the new software is crashing systems every 5 minutes, bogging down systems to a crawl, or corrupting databases, the software may not be in a 'sane' enough condition to warrant further testing in its current state.
• regression testing - re-testing after fixes or modifications of the software or its environment. It can be difficult to determine how much re-testing is needed, especially near the end of the development cycle. Automated testing tools can be especially useful for this type of testing.
• acceptance testing - final testing based on specifications of the end-user or customer, or based on use by end-users/customers over some limited period of time.
• load testing - testing an application under heavy loads, such as testing of a web site under a range of loads to determine at what point the system's response time degrades or fails.
• stress testing - term often used interchangeably with 'load' and 'performance' testing. Also used to describe such tests as system functional testing while under unusually heavy loads, heavy repetition of certain actions or inputs, input of large numerical values, large complex queries to a database system, etc.
• performance testing - term often used interchangeably with 'stress' and 'load' testing. Ideally 'performance' testing (and any other 'type' of testing) is defined in requirements documentation or QA or Test Plans.
• usability testing - testing for 'user-friendliness'. Clearly this is subjective, and will depend on the targeted end-user or customer. User interviews, surveys, video recording of user sessions, and other techniques can be used. Programmers and testers are usually not appropriate as usability testers.
• install/uninstall testing - testing of full, partial, or upgrade install/uninstall processes.
• recovery testing - testing how well a system recovers from crashes, hardware failures, or other catastrophic problems.
• failover testing - typically used interchangeably with 'recovery testing'
• security testing - testing how well the system protects against unauthorized internal or external access, willful damage, etc; may require sophisticated testing techniques.
• compatability testing - testing how well software performs in a particular hardware/software/operating system/network/etc. environment.
• exploratory testing - often taken to mean a creative, informal software test that is not based on formal test plans or test cases; testers may be learning the software as they test it.
• ad-hoc testing - similar to exploratory testing, but often taken to mean that the testers have significant understanding of the software before testing it.
• context-driven testing - testing driven by an understanding of the environment, culture, and intended use of software. For example, the testing approach for life-critical medical equipment software would be completely different than that for a low-cost computer game.
• user acceptance testing - determining if software is satisfactory to an end-user or customer.
• comparison testing - comparing software weaknesses and strengths to competing products.
• alpha testing - testing of an application when development is nearing completion; minor design changes may still be made as a result of such testing. Typically done by end-users or others, not by programmers or testers.
• beta testing - testing when development and testing are essentially completed and final bugs and problems need to be found before final release. Typically done by end-users or others, not by programmers or testers.
• mutation testing - a method for determining if a set of test data or test cases is useful, by deliberately introducing various code changes ('bugs') and retesting with the original test data/cases to determine if the 'bugs' are detected. Proper implementation requires large computational resources.

• poor requirements - if requirements are unclear, incomplete, too general, and not testable, there will be problems.
• unrealistic schedule - if too much work is crammed in too little time, problems are inevitable.
• inadequate testing - no one will know whether or not the program is any good until the customer complains or systems crash.
• featuritis - requests to pile on new features after development is underway; extremely common.
• miscommunication - if developers don't know what's needed or customer's have erroneous expectations, problems are guaranteed.

• solid requirements - clear, complete, detailed, cohesive, attainable, testable requirements that are agreed to by all players. Use prototypes to help nail down requirements. In 'agile'-type environments, continuous close coordination with customers/end-users is necessary.
• realistic schedules - allow adequate time for planning, design, testing, bug fixing, re-testing, changes, and documentation; personnel should be able to complete the project without burning out.
• adequate testing - start testing early on, re-test after fixes or changes, plan for adequate time for testing and bug-fixing. 'Early' testing ideally includes unit testing by developers and built-in testing and diagnostic capabilities.
• stick to initial requirements as much as possible - be prepared to defend against excessive changes and additions once development has begun, and be prepared to explain consequences. If changes are necessary, they should be adequately reflected in related schedule changes. If possible, work closely with customers/end-users to manage expectations. This will provide them a higher comfort level with their requirements decisions and minimize excessive changes later on.
• communication - require walkthroughs and inspections when appropriate; make extensive use of group communication tools - groupware, wiki's, bug-tracking tools and change management tools, intranet capabilities, etc.; insure that information/documentation is available and up-to-date - preferably electronic, not paper; promote teamwork and cooperation; use protoypes and/or continuous communication with end-users if possible to clarify expectations.

• minimize or eliminate use of global variables.
• use descriptive function and method names - use both upper and lower case, avoid abbreviations, use as many characters as necessary to be adequately descriptive (use of more than 20 characters is not out of line); be consistent in naming conventions.
• use descriptive variable names - use both upper and lower case, avoid abbreviations, use as many characters as necessary to be adequately descriptive (use of more than 20 characters is not out of line); be consistent in naming conventions.
• function and method sizes should be minimized; less than 100 lines of code is good, less than 50 lines is preferable.
• function descriptions should be clearly spelled out in comments preceding a function's code.
• organize code for readability.
• use whitespace generously - vertically and horizontally
• each line of code should contain 70 characters max.
• one code statement per line.
• coding style should be consistent throught a program (eg, use of brackets, indentations, naming conventions, etc.)
• in adding comments, err on the side of too many rather than too few comments; a common rule of thumb is that there should be at least as many lines of comments (including header blocks) as lines of code.
• no matter how small, an application should include documentaion of the overall program function and flow (even a few paragraphs is better than nothing); or if possible a separate flow chart and detailed program documentation.
• make extensive use of error handling procedures and status and error logging.
• for C++, to minimize complexity and increase maintainability, avoid too many levels of inheritance in class heirarchies (relative to the size and complexity of the application). Minimize use of multiple inheritance, and minimize use of operator overloading (note that the Java programming language eliminates multiple inheritance and operator overloading.)
• for C++, keep class methods small, less than 50 lines of code per method is preferable.
• for C++, make liberal use of exception handlers

• the program should act in a way that least surprises the user
• it should always be evident to the user what can be done next and how to exit
• the program shouldn't let the users do something stupid without warning them.

• SEI = 'Software Engineering Institute' at Carnegie-Mellon University; initiated by the U.S. Defense Department to help improve software development processes.
• CMM = 'Capability Maturity Model', now called the CMMI ('Capability Maturity Model Integration'), developed by the SEI. It's a model of 5 levels of process 'maturity' that determine effectiveness in delivering quality software. It is geared to large organizations such as large U.S. Defense Department contractors. However, many of the QA processes involved are appropriate to any organization, and if reasonably applied can be helpful. Organizations can receive CMMI ratings by undergoing assessments by qualified auditors.

       Level 1 - characterized by chaos, periodic panics, and heroic
                 efforts required by individuals to successfully
                 complete projects.  Few if any processes in place;
                 successes may not be repeatable.

       Level 2 - software project tracking, requirements management,
                 realistic planning, and configuration management
                 processes are in place; successful practices can
                 be repeated.

       Level 3 - standard software development and maintenance processes
                 are integrated throughout an organization; a Software
                 Engineering Process Group is is in place to oversee
                 software processes, and training programs are used to
                 ensure understanding and compliance.

       Level 4 - metrics are used to track productivity, processes,
                 and products.  Project performance is predictable,
                 and quality is consistently high.

       Level 5 - the focus is on continouous process improvement. The
                 impact of new processes and technologies can be
                 predicted and effectively implemented when required.


      Perspective on CMM ratings:  During 1997-2001, 1018 organizations
      were assessed.  Of those, 27% were rated at Level 1, 39% at 2,
      23% at 3, 6% at 4, and  5% at 5.  (For ratings during the period 
      1992-96, 62% were at Level 1, 23% at 2, 13% at 3, 2% at 4, and 
      0.4% at 5.)  The median size of organizations was 100 software 
      engineering/maintenance personnel; 32% of organizations were 
      U.S. federal contractors or agencies.  For those rated at 
      Level 1, the most problematical key process area was in 
      Software Quality Assurance.

• ISO = 'International Organisation for Standardization' - The ISO 9001:2000 standard (which replaces the previous standard of 1994) concerns quality systems that are assessed by outside auditors, and it applies to many kinds of production and manufacturing organizations, not just software. It covers documentation, design, development, production, testing, installation, servicing, and other processes. The full set of standards consists of: (a)Q9001-2000 - Quality Management Systems: Requirements; (b)Q9000-2000 - Quality Management Systems: Fundamentals and Vocabulary; (c)Q9004-2000 - Quality Management Systems: Guidelines for Performance Improvements. To be ISO 9001 certified, a third-party auditor assesses an organization, and certification is typically good for about 3 years, after which a complete reassessment is required. Note that ISO certification does not necessarily indicate quality products - it indicates only that documented processes are followed.
• IEEE = 'Institute of Electrical and Electronics Engineers' - among other things, creates standards such as 'IEEE Standard for Software Test Documentation' (IEEE/ANSI Standard 829), 'IEEE Standard of Software Unit Testing (IEEE/ANSI Standard 1008), 'IEEE Standard for Software Quality Assurance Plans' (IEEE/ANSI Standard 730), and others.
• ANSI = 'American National Standards Institute', the primary industrial standards body in the U.S.; publishes some software-related standards in conjunction with the IEEE and ASQ (American Society for Quality).
• Other software development/IT management process assessment methods besides CMMI and ISO 9000 include SPICE, Trillium, TickIT, Bootstrap, ITIL, MOF, and CobiT.

The life cycle begins when an application is first conceived and ends when it is no longer in use. It includes aspects such as initial concept, requirements analysis, functional design, internal design, documentation planning, test planning, coding, document preparation, integration, testing, maintenance, updates, retesting, phase-out, and other aspects.