Software Test estimation

What's the best approach to software test estimation?
There is no simple answer for this. The 'best approach' is highly dependent on the particular organization and project and the experience of the personnel involved.

For example, given two software projects of similar complexity and size, the appropriate test effort for one project might be very large if it was for life-critical medical equipment software, but might be much smaller for the other project if it was for a low-cost computer game. A test estimation approach that only considered size and complexity might be appropriate for one project but not for the other.
Following are some approaches to consider:

Implicit Risk Context Approach:
A typical approach to test estimation is for a project manager or QA manager to implicitly use risk context, in combination with past personal experiences in the organization, to choose a level of resources to allocate to testing. In many organizations, the 'risk context' is assumed to be similar from one project to the next, so there is no explicit consideration of risk context. (Risk context might include factors such as the organization's typical software quality levels, the software's intended use, the experience level of developers and testers, etc.) This is essentially an intuitive guess based on experience.

Metrics-Based Approach:
A useful approach is to track past experience of an organization's various projects and the associated test effort that worked well for projects. Once there is a set of data covering characteristics for a reasonable number of projects, then this 'past experience' information can be used for future test project planning. (Determining and collecting useful project metrics over time can be an extremely difficult task.) For each particular new project, the 'expected' required test time can be adjusted based on whatever metrics or other information is available, such as function point count, number of external system interfaces, unit testing done by developers, risk levels of the project, etc. In the end, this is essentially 'judgement based on documented experience', and is not easy to do successfully.

Test Work Breakdown Approach:
Another common approach is to decompose the expected testing tasks into a collection of small tasks for which estimates can, at least in theory, be made with reasonable accuracy. This of course assumes that an accurate and predictable breakdown of testing tasks and their estimated effort is feasible. In many large projects, this is not the case. For example, if a large number of bugs are being found in a project, this will add to the time required for testing, retesting, bug analysis and reporting. It will also add to the time required for development, and if development schedules and efforts do not go as planned, this will further impact testing.

Iterative Approach:
In this approach for large test efforts, an initial rough testing estimate is made. Once testing begins, a more refined estimate is made after a small percentage (eg, 1%) of the first estimate's work is done. At this point testers have obtained additional test project knowledge and a better understanding of issues, general software quality, and risk. Test plans and schedules can be refactored if necessary and a new estimate provided. Then a yet-more-refined estimate is made after a somewhat larger percentage (eg, 2%) of the new work estimate is done. Repeat the cycle as necessary/appropriate.

Percentage-of-Development Approach:
Some organizations utilize a quick estimation method for testing based on the estimated programming effort. For example, if a project is estimated to require 1000 hours of programming effort, and the organization normally finds that a 40% ratio for testing is appropriate, then an estimate of 400 hours for testing would be used. This approach may or may not be useful depending on the project-to-project variations in risk, personnel, types of applications, levels of complexity, etc.
Successful test estimation is a challenge for most organizations, since few can accurately estimate software project development efforts, much less the testing effort of a project. It is also difficult to attempt testing estimates without first having detailed information about a project, including detailed requirements, the organization's experience with similar projects in the past, and an understanding of what should be included in a 'testing' estimation for a project (functional testing? unit testing? reviews? inspections? load testing? security testing?)
With agile software development approaches, test effort estimations may be unnecessary if pure test-driven development is utilized. However, it is not uncommon to have a mix of some automated positive-type unit tests, along with some type of separate manual or automated functional testing. In general, agile-based projects by their nature will not be heavily dependent on large one-shot testing efforts, since they emphasize the construction of releasable software in very short iteration cycles. These smaller multiple test effort estimates may not be as difficult to estimate and the impact of inaccurate estimates will be less severe.

Types of testing(in short)

What kinds of testing should be considered?

• 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 approaches 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.

Recent sofware bugs

What are some recent major computer system failures caused by software bugs?

• Email services of a major smartphone system were interrupted or unavailable for nine hours in December 2009, the second service interruption within a week, according to news reports. The problems were believed to be due to bugs in new versions of the email system software.
• It was reported in August 2009 that a large suburban school district introduced a new computer system that was 'plagued with bugs' and resulted in many students starting the school year without schedules or with incorrect schedules, and many problems with grades. Upset students and parents started a social networking site for sharing complaints.
• In February of 2009 users of a major search engine site were prevented from clicking through to sites listed in search results for part of a day. It was reportedly due to software that did not effectively handle a mistakenly-placed "/" in an internal ancillary reference file that was frequently updated for use by the search engine. Users, instead of being able to click thru to listed sites, were instead redirected to an intermediary site which, as a result of the suddenly enormous load, was rendered unusable.
• A large health insurance company was reportedly banned by regulators from selling certain types of insurance policies in January of 2009 due to ongoing computer system problems that resulted in denial of coverage for needed medications and mistaken overcharging or cancelation of benefits. The regulatory agency was quoted as stating that the problems were posing "a serious threat to the health and safety" of beneficiaries.
• A news report in January 2009 indicated that a major IT and management consulting company was still battling years of problems in implementing its own internal accounting systems, including a 2005 implementation that reportedly "was attempted without adequate testing".
• In August of 2008 it was reported that more than 600 U.S. airline flights were significantly delayed due to a software glitch in the U.S. FAA air traffic control system. The problem was claimed to be a 'packet switch' that 'failed due to a database mismatch', and occurred in the part of the system that handles required flight plans.
• Software system problems at a large health insurance company in August 2008 were the cause of a privacy breach of personal health information for several hundred thousand customers, according to news reports. It was claimed that the problem was due to software that 'was not comprehensively tested'.
• A major clothing retailer was reportedly hit with significant software and system problems when attempting to upgrade their online retailing systems in June 2008. Problems remained ongoing for some time. When the company made their public quarterly financial report, the software and system problems were claimed as the cause of the poor financial results.
• Software problems in the automated baggage sorting system of a major airport in February 2008 prevented thousands of passengers from checking baggage for their flights. It was reported that the breakdown occurred during a software upgrade, despite pre-testing of the software. The system continued to have problems in subsequent months.
• News reports in December of 2007 indicated that significant software problems were continuing to occur in a new ERP payroll system for a large urban school system. It was believed that more than one third of employees had received incorrect paychecks at various times since the new system went live the preceding January, resulting in overpayments of $53 million, as well as underpayments. An employees' union brought a lawsuit against the school system, the cost of the ERP system was expected to rise by 40%, and the non-payroll part of the ERP system was delayed. Inadequate testing reportedly contributed to the problems. The school system was still working on cleaning up the aftermath of the problems in December 2009, going so far as to bring lawsuits against some employees to get them to return overpayments.
• In November of 2007 a regional government reportedly brought a multi-million dollar lawsuit against a software services vendor, claiming that the vendor 'minimized quality' in delivering software for a large criminal justice information system and the system did not meet requirements. The vendor also sued its subcontractor on the project.
• In June of 2007 news reports claimed that software flaws in a popular online stock-picking contest could be used to gain an unfair advantage in pursuit of the game's large cash prizes. Outside investigators were called in and in July the contest winner was announced. Reportedly the winner had previously been in 6th place, indicating that the top 5 contestants may have been disqualified.
• A software problem contributed to a rail car fire in a major underground metro system in April of 2007 according to newspaper accounts. The software reportedly failed to perform as expected in detecting and preventing excess power usage in equipment on new passenger rail cars, resulting in overheating and fire in the rail car, and evacuation and shutdown of part of the system.
• Tens of thousands of medical devices were recalled in March of 2007 to correct a software bug. According to news reports, the software would not reliably indicate when available power to the device was too low.
• A September 2006 news report indicated problems with software utilized in a state government's primary election, resulting in periodic unexpected rebooting of voter checkin machines, which were separate from the electronic voting machines, and resulted in confusion and delays at voting sites. The problem was reportedly due to insufficient testing.
• In August of 2006 a U.S. government student loan service erroneously made public the personal data of as many as 21,000 borrowers on it's web site, due to a software error. The bug was fixed and the government department subsequently offered to arrange for free credit monitoring services for those affected.
• A software error reportedly resulted in overbilling of up to several thousand dollars to each of 11,000 customers of a major telecommunications company in June of 2006. It was reported that the software bug was fixed within days, but that correcting the billing errors would take much longer.
• News reports in May of 2006 described a multi-million dollar lawsuit settlement paid by a healthcare software vendor to one of its customers. It was reported that the customer claimed there were problems with the software they had contracted for, including poor integration of software modules, and problems that resulted in missing or incorrect data used by medical personnel.
• In early 2006 problems in a government's financial monitoring software resulted in incorrect election candidate financial reports being made available to the public. The government's election finance reporting web site had to be shut down until the software was repaired.
• Trading on a major Asian stock exchange was brought to a halt in November of 2005, reportedly due to an error in a system software upgrade. The problem was rectified and trading resumed later the same day.
• A May 2005 newspaper article reported that a major hybrid car manufacturer had to install a software fix on 20,000 vehicles due to problems with invalid engine warning lights and occasional stalling. In the article, an automotive software specialist indicated that the automobile industry spends $2 billion to $3 billion per year fixing software problems.
• 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.
• A review board concluded that the NASA Mars Polar Lander failed in December 1999 due to software problems that caused improper functioning of retro rockets utilized by the Lander as it entered the Martian atmosphere.
• 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.
• In August 1991 the concrete base structure for a North Sea oil platform imploded and sank off the coast of Norway, reportedly due to errors in initially-used design software. The enormous structure, on hitting the seabed, reportedly was detected as a magnitude 3.0 seismic event and resulted in a loss of $700 million. The base structure was eventually redesigned and the full platform was completed two years later, and was still in use as of 2008.
• On January 1 1984 all computers produced by one of the leading minicomputer makers of the time reportedly failed worldwide. The cause was claimed to be a leap year bug in a date handling function utilized in deletion of temporary operating system files. Technicians throughout the world worked for several days to clear up the problem. It was also reported that the same bug affected many of the same computers four years later.
• 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.

Interview Questions in Software testing part 1

What makes a good Software Test engineer?
A good test engineer has a 'test to break' attitude, an ability to take the point of view of the customer, a strong desire for quality, and an attention to detail. Tact and diplomacy are useful in maintaining a cooperative relationship with developers, and an ability to communicate with both technical (developers) and non-technical (customers, management) people is useful. Previous software development experience can be helpful as it provides a deeper understanding of the software development process, gives the tester an appreciation for the developers' point of view, and reduce the learning curve in automated test tool programming. Judgement skills are needed to assess high-risk or critical areas of an application on which to focus testing efforts when time is limited.

What makes a good Software QA engineer?
The same qualities a good tester has are useful for a QA engineer. Additionally, they must be able to understand the entire software development process and how it can fit into the business approach and goals of the organization. Communication skills and the ability to understand various sides of issues are important. In organizations in the early stages of implementing QA processes, patience and diplomacy are especially needed. An ability to find problems as well as to see 'what's missing' is important for inspections and reviews.

What makes a good QA or Test manager?
A good QA, test, or QA/Test(combined) manager should:

• be familiar with the software development process
• be able to maintain enthusiasm of their team and promote a positive atmosphere, despite what is a somewhat 'negative' process (e.g., looking for or preventing problems)
• be able to promote teamwork to increase productivity
• be able to promote cooperation between software, test, and QA engineers
• have the diplomatic skills needed to promote improvements in QA processes
• have the ability to withstand pressures and say 'no' to other managers when quality is insufficient or QA processes are not being adhered to
• have people judgement skills for hiring and keeping skilled personnel
• be able to communicate with technical and non-technical people, engineers, managers, and customers.
• be able to run meetings and keep them focused

What's the role of documentation in QA?
Generally, the larger the team/organization, the more useful it will be to stress documentation, in order to manage and communicate more efficiently. (Note that documentation may be electronic, not necessarily in printable form, and may be embedded in code comments, may be embodied in well-written test cases, user stories, etc.) QA practices may be documented to enhance their repeatability. Specifications, designs, business rules, configurations, code changes, test plans, test cases, bug reports, user manuals, etc. may be documented in some form. There would ideally be a system for easily finding and obtaining information and determining what documentation will have a particular piece of information. Change management for documentation can be used where appropriate. For agile software projects, it should be kept in mind that one of the agile values is "Working software over comprehensive documentation", which does not mean 'no' documentation. Agile projects tend to stress the short term view of project needs; documentation often becomes more important in a project's long-term context.

What's the big deal about 'requirements'?
One of the most reliable methods of ensuring problems, or failure, in a large, complex software project is to have poorly documented requirements specifications. (Note that requirements documentation can be electronic, not necessarily in the form of printable documents, and may be embedded in code comments, may be embodied in well-written test cases, etc.) Requirements are the details describing an application's externally-perceived functionality and properties. Requirements should be clear, complete, reasonably detailed, cohesive, attainable, and testable. A non-testable requirement would be, for example, 'user-friendly' (too subjective). A more testable requirement would be something like 'the user must enter their previously-assigned password to access the application'. Determining and organizing requirements details in a useful and efficient way can be a difficult effort; different methods are available depending on the particular project. Many books are available that describe various approaches to this task. (See the Softwareqatest.com Bookstore section's 'Software Requirements Engineering' category for books on Software Requirements.)

Care should be taken to involve ALL of a project's significant 'customers' in the requirements process. 'Customers' could be in-house personnel or outside personnel, and could include end-users, customer acceptance testers, customer contract officers, customer management, future software maintenance engineers, salespeople, etc. Anyone who could later derail the project if their expectations aren't met should be included if possible.
Organizations vary considerably in their handling of requirements specifications. Often the requirements are spelled out in a document with statements such as 'The product shall.....'. 'Design' specifications should not be confused with 'requirements'; design specifications are ideally traceable back to the requirements.
In some organizations requirements may end up in high level project plans, functional specification documents, in design documents, or in other documents at various levels of detail. No matter what they are called, some type of documentation with detailed requirements will be needed by testers in order to properly plan and execute tests. Without such documentation, there will be no clear-cut way to determine if a software application is performing correctly.
'Agile' approaches use methods requiring close interaction and cooperation between programmers and customers/end-users to iteratively develop requirements, user stories, etc. In the XP 'test first' approach developers create automated unit testing code before the application code, and these automated unit tests essentially embody the requirements.

What steps are needed to develop and run software tests?
The following are some of the steps to consider:

• Obtain requirements, functional design, and internal design specifications, user stories, and other available/necessary information
• Obtain budget and schedule requirements
• Determine project-related personnel and their responsibilities, reporting requirements, required standards and processes (such as release processes, change processes, etc.)
• Determine project context, relative to the existing quality culture of the product/organization/business, and how it might impact testing scope, aproaches, and methods.
• Identify application's higher-risk and mor important aspects, set priorities, and determine scope and limitations of tests.
• Determine test approaches and methods - unit, integration, functional, system, security, load, usability tests, etc.
• Determine test environment requirements (hardware, software, configuration, versions, communications, etc.)
• Determine testware requirements (automation tools, coverage analyzers, test tracking, problem/bug tracking, etc.)
• Determine test input data requirements
• Identify tasks, those responsible for tasks, and labor requirements
• Set schedule estimates, timelines, milestones
• Determine, where apprapriate, input equivalence classes, boundary value analyses, error classes
• Prepare test plan document(s) and have needed reviews/approvals
• Write test cases
• Have needed reviews/inspections/approvals of test cases
• Prepare test environment and testware, obtain needed user manuals/reference documents/configuration guides/installation guides, set up test tracking processes, set up logging and archiving processes, set up or obtain test input data
• Obtain and install software releases
• Perform tests
• Evaluate and report results
• Track problems/bugs and fixes
• Retest as needed
• Maintain and update test plans, test cases, test environment, and testware through life cycle

Return to top of this page's FAQ list

What's a 'test plan'?
A software project test plan is a document that describes the objectives, scope, approach, and focus of a software testing effort. The process of preparing a test plan is a useful way to think through the efforts needed to validate the acceptability of a software product. The completed document will help people outside the test group understand the 'why' and 'how' of product validation. It should be thorough enough to be useful but not so thorough that no one outside the test group will read it. The following are some of the items that might be included in a test plan, depending on the particular project:

• Title
• Identification of software including version/release numbers
• Revision history of document including authors, dates, approvals
• Table of Contents
• Purpose of document, intended audience
• Objective of testing effort
• Software product overview
• Relevant related document list, such as requirements, design documents, other test plans, etc.
• Relevant standards or legal requirements
• Traceability requirements
• Relevant naming conventions and identifier conventions
• Overall software project organization and personnel/contact-info/responsibilties
• Test organization and personnel/contact-info/responsibilities
• Assumptions and dependencies
• Project risk analysis
• Testing priorities and focus
• Scope and limitations of testing
• Test outline - a decomposition of the test approach by test type, feature, functionality, process, system, module, etc. as applicable
• Outline of data input equivalence classes, boundary value analysis, error classes
• Test environment - hardware, operating systems, other required software, data configurations, interfaces to other systems
• Test environment validity analysis - differences between the test and production systems and their impact on test validity.
• Test environment setup and configuration issues
• Software migration processes
• Software CM processes
• Test data setup requirements
• Database setup requirements
• Outline of system-logging/error-logging/other capabilities, and tools such as screen capture software, that will be used to help describe and report bugs
• Discussion of any specialized software or hardware tools that will be used by testers to help track the cause or source of bugs
• Test automation - justification and overview
• Test tools to be used, including versions, patches, etc.
• Test script/test code maintenance processes and version control
• Problem tracking and resolution - tools and processes
• Project test metrics to be used
• Reporting requirements and testing deliverables
• Software entrance and exit criteria
• Initial sanity testing period and criteria
• Test suspension and restart criteria
• Personnel allocation
• Personnel pre-training needs
• Test site/location
• Outside test organizations to be utilized and their purpose, responsibilties, deliverables, contact persons, and coordination issues
• Relevant proprietary, classified, security, and licensing issues.
• Open issues
• Appendix - glossary, acronyms, etc.

What's a 'test case'?

A test case describes an input, action, or event and an expected response, to determine if a feature of a software application is working correctly. A test case may contain particulars such as test case identifier, test case name, objective, test conditions/setup, input data requirements, steps, and expected results. The level of detail may vary significantly depending on the organization and project context.

Note that the process of developing test cases can help find problems in the requirements or design of an application, since it requires completely thinking through the operation of the application. For this reason, it's useful to prepare test cases early in the development cycle if possible.

What should be done after a bug is found?
The bug needs to be communicated and assigned to developers that can fix it. After the problem is resolved, fixes should be re-tested, and determinations made regarding requirements for regression testing to check that fixes didn't create problems elsewhere. If a problem-tracking system is in place, it should encapsulate these processes. A variety of commercial problem-tracking/management software tools are available (see the 'Tools' section for web resources with listings of such tools). The following are items to consider in the tracking process:

• Complete information such that developers can understand the bug, get an idea of it's severity, and reproduce it if necessary.
• Bug identifier (number, ID, etc.)
• Current bug status (e.g., 'Released for Retest', 'New', etc.)
• The application name or identifier and version
• The function, module, feature, object, screen, etc. where the bug occurred
• Environment specifics, system, platform, relevant hardware specifics
• Test case name/number/identifier
• One-line bug description
• Full bug description
• Description of steps needed to reproduce the bug if not covered by a test case or if the developer doesn't have easy access to the test case/test script/test tool
• Names and/or descriptions of file/data/messages/etc. used in test
• File excerpts/error messages/log file excerpts/screen shots/test tool logs that would be helpful in finding the cause of the problem
• Severity estimate (a 5-level range such as 1-5 or 'critical'-to-'low' is common)
• Was the bug reproducible?
• Tester name
• Test date
• Bug reporting date
• Name of developer/group/organization the problem is assigned to
• Description of problem cause
• Description of fix
• Code section/file/module/class/method that was fixed
• Date of fix
• Application version that contains the fix
• Tester responsible for retest
• Retest date
• Retest results
• Regression testing requirements
• Tester responsible for regression tests
• Regression testing results

A reporting or tracking process should enable notification of appropriate personnel at various stages. For instance, testers need to know when retesting is needed, developers need to know when bugs are found and how to get the needed information, and reporting/summary capabilities are needed for managers.

What is 'configuration management'?
Configuration management covers the processes used to control, coordinate, and track: code, requirements, documentation, problems, change requests, designs, tools/compilers/libraries/patches, changes made to them, and who makes the changes. (See the 'Tools' section for web resources with listings of configuration management tools.

What if the software is so buggy it can't really be tested at all?
The best bet in this situation is for the testers to go through the process of reporting whatever bugs or blocking-type problems initially show up, with the focus being on critical bugs. Since this type of problem can severely affect schedules, and indicates deeper problems in the software development process (such as insufficient unit testing or insufficient integration testing, poor design, improper build or release procedures, etc.) managers should be notified, and provided with some documentation as evidence of the problem.

How can it be known when to stop testing?
This can be difficult to determine. Most modern software applications are so complex, and run in such an interdependent environment, that complete testing can never be done. Common factors in deciding when to stop are:

• Deadlines (release deadlines, testing deadlines, etc.)
• Test cases completed with certain percentage passed
• Test budget depleted
• Coverage of code/functionality/requirements reaches a specified point
• Bug rate falls below a certain level
• Beta or alpha testing period ends

What if there isn't enough time for thorough testing?
Use risk analysis, along with discussion with project stakeholders, to determine where testing should be focused.
Since it's rarely possible to test every possible aspect of an application, every possible combination of events, every dependency, or everything that could go wrong, risk analysis is appropriate to most software development projects. This requires judgement skills, common sense, and experience. (If warranted, formal methods are also available.) Considerations can include:

• Which functionality is most important to the project's intended purpose?
• Which functionality is most visible to the user?
• Which functionality has the largest safety impact?
• Which functionality has the largest financial impact on users?
• Which aspects of the application are most important to the customer?
• Which aspects of the application can be tested early in the development cycle?
• Which parts of the code are most complex, and thus most subject to errors?
• Which parts of the application were developed in rush or panic mode?
• Which aspects of similar/related previous projects caused problems?
• Which aspects of similar/related previous projects had large maintenance expenses?
• Which parts of the requirements and design are unclear or poorly thought out?
• What do the developers think are the highest-risk aspects of the application?
• What kinds of problems would cause the worst publicity?
• What kinds of problems would cause the most customer service complaints?
• What kinds of tests could easily cover multiple functionalities?
• Which tests will have the best high-risk-coverage to time-required ratio?

What if the project isn't big enough to justify extensive testing?
Consider the impact of project errors, not the size of the project. However, if extensive testing is still not justified, risk analysis is again needed and the same considerations as described previously in 'What if there isn't enough time for thorough testing?' apply. The tester might then do ad hoc testing, or write up a limited test plan based on the risk analysis.

How does a client/server environment affect testing?
Client/server applications can be quite complex due to the multiple dependencies among clients, data communications, hardware, and servers, especially in multi-tier systems. Thus testing requirements can be extensive. When time is limited (as it usually is) the focus should be on integration and system testing. Additionally, load/stress/performance testing may be useful in determining client/server application limitations and capabilities. There are commercial tools to assist with such testing.

How can World Wide Web sites be tested?
Web sites are essentially client/server applications - with web servers and 'browser' clients. Consideration should be given to the interactions between html pages, web services, encrypted communications, Internet connections, firewalls, applications that run in web pages (such as javascript, flash, other plug-in applications), the wide variety of applications that could run on the server side, etc. Additionally, there are a wide variety of servers and browsers, various versions of each, small but sometimes significant differences between them, variations in connection speeds, rapidly changing technologies, and multiple standards and protocols. The end result is that testing for web sites can become a major ongoing effort. Other considerations might include:

• What are the expected loads on the server (e.g., number of hits per unit time?), and what kind of performance is required under such loads (such as web server response time, database query response times). What kinds of tools will be needed for performance testing (such as web load testing tools, other tools already in house that can be adapted, load generation appliances, etc.)?
• Who is the target audience? What kind and version of browsers will they be using, and how extensively should testing be for these variations? What kind of connection speeds will they by using? Are they intra- organization (thus with likely high connection speeds and similar browsers) or Internet-wide (thus with a wide variety of connection speeds and browser types)?
• What kind of performance is expected on the client side (e.g., how fast should pages appear, how fast should flash, applets, etc. load and run)?
• Will down time for server and content maintenance/upgrades be allowed? how much?
• What kinds of security (firewalls, encryption, passwords, functionality, etc.) will be required and what is it expected to do? How can it be tested?
• What internationilization/localization/language requirements are there, and how are they to be verified?
• How reliable are the site's Internet connections required to be? And how does that affect backup system or redundant connection requirements and testing?
• What processes will be required to manage updates to the web site's content, and what are the requirements for maintaining, tracking, and controlling page content, graphics, links, etc.?
• Which HTML and related specification will be adhered to? How strictly? What variations will be allowed for targeted browsers?
• Will there be any standards or requirements for page appearance and/or graphics throughout a site or parts of a site?
• Will there be any development practices/standards utilized for web page components and identifiers, which can significantly impact test automation.
• How will internal and external links be validated and updated? how often?
• Can testing be done on the production system, or will a separate test system be required? How are browser caching, variations in browser option settings, connection variabilities, and real-world internet 'traffic congestion' problems to be accounted for in testing?
• How extensive or customized are the server logging and reporting requirements; are they considered an integral part of the system and do they require testing?
• How are flash, applets, javascripts, ActiveX components, etc. to be maintained, tracked, controlled, and tested?

How is testing affected by object-oriented designs?
Well-engineered object-oriented design can make it easier to trace from code to internal design to functional design to requirements. While there will be little affect on black box testing (where an understanding of the internal design of the application is unnecessary), white-box testing can be oriented to the application's objects. If the application was well-designed this can simplify test design.

What is Extreme Programming and what's it got to do with testing?
Extreme Programming (XP) is a software development approach for small teams on risk-prone projects with unstable requirements. It was created by Kent Beck who described the approach in his book 'Extreme Programming Explained' . Testing ('extreme testing') is a core aspect of Extreme Programming. Programmers are expected to write unit and functional test code first - before writing the application code. Test code is under source control along with the rest of the code. Customers are expected to be an integral part of the project team and to help develope scenarios for acceptance/black box testing. Acceptance tests are preferably automated, and are modified and rerun for each of the frequent development iterations. QA and test personnel are also required to be an integral part of the project team. Detailed requirements documentation is not used, and frequent re-scheduling, re-estimating, and re-prioritizing is expected. For more info on XP and other 'agile' software development approaches (Scrum, Crystal, etc.)

Importance of CV

Hi Guys,
This blog reflects my experience of giving many interview.
I have given interview in "HEWITT ASSOCIATES" . There i came to know what is the importance of making a good resume and mentioning all the correct details which you can justify in front of interviewer.
First of all, your details should be precise. You should mention your current projects first  after that another projects done.
If you mention your role in the projects, then please be sure that you are able to define clearly what you have done correctly.
Dont fake anything , if you are showing then you must be able to justify it.
One thing most important , If you are mentioning about your strenghts , then you must have some examples and must be clearly shown by your example.
A good CV can make your selection half done.
Himanshu jain

UNIX vs LINUX

Unix vs Linux
Most of us think that Linux was created as a response to Windows which is the most popular operating system nowadays, but it is actually a response to UNIX. UNIX is a very old operating system that was intended to operate on large computers and mainframes. It is not cheap or easy to use, that is why only a very few people use it. Linux, which is developed by Linus Torvalds, is based on the UNIX system but does away with the complex mechanisms that make learning UNIX very steep.

Being the predecessor of most of the operating systems that is being used today, UNIX has existed for a very long time and has changed very little since it was created as a processing machine and very little processing power was used towards better interfaces and ease of use improvements. Linux was built with the common user in mind, therefore most Linux distributions provide users with a very capable GUI that also eats up a portion of the computer’s processing power. Owing to Linux’s flexibility, the GUI can be removed for server applications that don’t need fancy GUIs.

It was developed to maximize the productivity of high end computers that are used by big companies, and all of the releases for UNIX are built with the latest high end hardware in mind and it is not usable in the common desktop computer. Linux, on the other hand, can scale reliably across different hardware platforms making it a good choice for most people.

There is also the cost of these two operating systems. Linux is a free OS that is developed by the community and licensed under the GNU GPL. Unix, on the other hand, is a proprietary software and you would need to buy it if you want to use it.

Summary:
1. UNIX is very old and Linux is based on it
2. Linux is a good desktop OS while UNIX lacks the user friendliness needed for general computing
3. UNIX is intended for mainframes and high end computers and cannot run on mos PCs while Linux can go from mainframes down to low end personal computers
4. UNIX is proprietary while Linux is shared using the Licensing of the GNU

What is Hyper virtualization?

Hyper-V is Microsoft's answer to VMware ESX and other hypervisor based virtualization solutions. For those who are virtualizing Windows servers, Hyper-V presents a compelling Windows virtualization solution based on much lower cost and a feature set that's good enough for many Windows based IT shops.
Those who remember Microsoft Virtual Server should know that Hyper-V is a complete rewrite and is a different piece of software. Microsoft Virtual Server is a host based virtualization solution, which is too slow for a production enterprise environment. On the other hand, Hyper-V is a hypervisor based virtualization solution that's very well suited for high performance production environments.

Hyper-V CPU and I/O Performance

Hyper-V requires hardware assisted virtualization such as Intel VT-X or AMD-V which makes virtualization run fast. The consequence of requiring CPU based virtualization assistance also means Hyper-V will not run on old hardware and that it will only work on 64-bit Windows Server 2008.
I/O performance was independently tested by storage vendor Qlogic with results that show Hyper-V performed at 88% to 99% of native performance, depending on the storage subsystem used.

Hyper-V Quick Migration

With Hyper-V's Quick Migration, a virtual machine is suspended while it's being copied over the network to another physical server. The duration a virtual machine is down is short, but there is still downtime.

Guest Operating Systems Compatible With Hyper-V

The list of operating systems includes nearly all of the operating systems most IT shops are concerned about. Operating systems supported include:

• Windows Server 2008
• Windows Server 2003 SP2 R2
• Windows Server 2000 SP4 and Advanced Server
• Windows 7
• Windows Vista
• Windows XP Professional
• SuSE Linux 10
• Red Hat Enterprise Linux (RHEL) 5.2 and later

Hyper-V is Much Cheaper Than VMWare or Citrix XenServer

The reason to buy Hyper-V is due to cost, especially for a Windows shop. Windows Server 2008 Datacenter Edition costs $3,000 per CPU socket, regardless of the number of cores. With the Datacenter Edition, it allows for an unlimited number of virtual machines Windows Server 2008 and Windows Server 2003. If Microsoft Volume Licensing is included, the cost is essentially zero.
For an IT shop running Windows, the prime candidates for applications to use Hyper-V include Exchange, IIS, SQL Server, and Sharepoint. The virtualized environment would be supported by the same vendor as the applications. The cost of virtualization software cost is lumped in with Windows Server 2008, which would have been bought anyway.
Unless a Windows shop needs all of the features of VMware or Xen, the cost savings from buying a good, but not great solution is significant compared to the technically superior offerings from VMware or Citrix.

For more information refer:

www.microsoft.com/hyper-v-server/en/us/default.aspx

 

Black Box Testing

Black box is a test design method. It focuses on the functionality part of the module. There are some bugs that cannot be found using only black box or only white box. If the test cases are extensive and the test inputs are also from a large sample space then it is always possible to find majority of the bugs through black box testing.

Advantages of Black Box Testing
§    Tester can be non-technical.
§    This testing is most likely to find those bugs as the user would find.
§    Testing helps to identify the vagueness and contradiction in functional specifications.
§    Test cases can be designed as soon as the functional specifications are complete
Disadvantages of Black Box Testing
§    Chances of having repetition of tests that are already done by programmer.
§    The test inputs needs to be from large sample space.
§    It is difficult to identify all possible inputs in limited testing time. So writing test cases is slow and difficult
§    Chances of having unidentified paths during this testing


Types of BBT

§    Graph Based Testing Methods: Software testing begins by creating a graph of important objects and their relationships and then devising a series of tests that will cover the graph so that each objects and their relationships and then devising a series of tests that will cover the graph so that each object and relationship is exercised and error is uncovered.

§    Error Guessing: Error Guessing comes with experience with the technology and the project. Error Guessing is the art of guessing where errors can be hidden. There are no specific tools and techniques for this, but you can write test cases depending on the situation: Either when reading the functional documents or when you are testing and find an error that you have not documented.

§    Boundary Value Analysis: Boundary Value Analysis (BVA) is a test data selection technique (Functional Testing technique) where the extreme values are chosen. Boundary values include maximum, minimum, just inside/outside boundaries, typical values, and error values. The hope is that, if a system works correctly for these special values then it will work correctly for all values in between. Guidelines for boundary value analysis are:
o    If an input condition specifies a range bounded by value ‘a’ and value ‘b’, test cases should be designed with value a and b and just above and below the value a and b.
o    If an input condition specifies a number of value, test cases should be developed that exercise the minimum and the maximum numbers. Values just above and below the maximum numbers are also tested.
The advantages of boundary value analysis are:
o    Robustness Testing - Boundary Value Analysis plus values that go beyond the limits
o    Min - 1, Min, Min +1, Nom, Max -1, Max, Max +1
o    Forces attention to exception handling
o    For strongly typed languages robust testing results in run-time errors that abort normal execution
The limitations of Boundary value analysis are: BVA works best when the program is a function of several independent variables that represent bounded physical quantities
o    Independent Variables
§    Next Date test cases derived from BVA would be inadequate: focusing on the boundary would not leave emphasis on February or leap years
§    Dependencies exist with Next Date’s Day, Month and Year
§    Test cases derived without consideration of the function
o    Physical Quantities: An example of physical variables being tested, telephone numbers - what faults might be revealed by numbers of 000-0000, 000-0001, 555-5555, 999-9998, 999-9999?

§    Equivalence Partitioning: Equivalence partitioning is a black box testing method that divides the input domain of a program into classes of data from which test cases can be derived. EP can be defined according to the following guidelines:
o    If an input condition specifies a range, one valid and one two invalid classes are defined.
o    If an input condition requires a specific value, one valid and two invalid equivalence classes are defined.
o    If an input condition specifies a member of a set, one valid and one invalid equivalence class is defined.
o    If an input condition is Boolean, one valid and one invalid class is defined.

§    Comparison Testing:  There are situations where independent versions of software be developed for critical applications, even when only a single version will be used in the delivered computer based system. It is these independent versions, which form the basis of a black box testing technique called Comparison testing or back-to-back testing.

§    Orthogonal Array Testing: The Orthogonal Array Testing Strategy (OATS) is a systematic, statistical way of testing pair-wise interactions by deriving a suitable small set of test cases from a large number of possibilities. The theory -Orthogonal Array Testing (OAT) can be used to reduce the number of combinations and provide maximum coverage with a minimum number of test cases. OAT is an array of values in which each column represents a variable - factor that can take a certain set of values called levels. Each row represents a test case. In OAT, the factors are combined pair-wise rather than representing all possible combinations of factors and levels.

How Domain Knowledge is important for a tester?

First of all I would like to introduce three dimensional testing career .There are three categories of skill that need to be judged before hiring any software tester. What are those three skill categories?
1) Testing skill
2) Domain knowledge
3) Technical expertise.

No doubt that any tester should have the basic testing skills like Manual testing and Automation testing. Tester having the common sense can even find most of the obvious bugs in the software. Then would you say that this much testing is sufficient? Would you release the product on the basis of this much testing done? Certainly not.You will certainly have a product look by the domain expert before the product goes into the market.

While testing any application you should think like a end-user. But every human being has the limitations and one can’t be the expert in all of the three dimensions mentioned above. (If you are the experts in all of the above skills then please let me know ;-)) So you can’t assure that you can think 100% like how the end-user going to use your application. User who is going to use your application may be having a good understanding of the domain he is working on. You need to balance all these skill activities so that all product aspects will get addressed.

Nowadays you can see the professional being hired in different companies are more domain experts than having technical skills. Current software industry is also seeing a good trend that many professional developers and domain experts are moving into software testing.

We can observe one more reason why domain experts are most wanted! When you hire fresh engineers who are just out of college you cannot expect them to compete with the experienced professionals. Why? Because experienced professional certainly have the advantage of domain and testing experience and they have better understandings of different issues and can deliver the application better and faster.

Here are some of the examples where you can see the distinct edge of domain knowledge: 
1) Mobile application testing.
2) Wireless application testing
3) VoIP applications
4) Protocol testing
5) Banking applications
6) Network testing

How will you test such applications without knowledge of specific domain? Are you going to test the BFSI applications (Banking, Financial Services and Insurance) just for UI or functionality or security or load or stress? You should know what are the user requirements in banking, working procedures, commerce background, exposure to brokerage etc and should test application accordingly, then only you can say that your testing is enough - Here comes the need of subject-matter experts.

Let’s take example of my current project: I am currently working on a project based on E-learning and which is a complete LMS (Learning Management System). If a tester do not have the domain knowledge or if he doesn't know what is "assessments" , "standards" and "prescription" , then how can he test that application.

When I know the functional domain better I can better write and execute more test cases and can effectively simulate the end user actions which is distinctly a big advantage.

Here is the big list of the required testing knowledge:

• Testing skill
• Bug hunting skill
• Technical skill
• Domain knowledge
• Communication skill
• Automation skill
• Some programming skill
• Quick grasping
• Ability to Work under pressure …

That is going to be a huge list. So you will certainly say, do I need to have these many skills? Its’ depends on you. You can stick to one skill or can be expert in one skill and have good understanding of other skills or balanced approach of all the skills. This is the competitive market and you should definitely take advantage of it. Make sure to be expert in at least one domain before making any move.

What if you don’t have enough domain knowledge?
You will be posted on any project and company can assign any work to you. Then what if you don’t have enough domain knowledge of that project? You need to quickly grasp as many concepts as you can. Try to understand the product as if you are the customer and what customer will do with application. Visit the customer site if possible know how they work with the product, Read online resources about the domain you want to test the application, participate in events addressing on such domain, meet the domain experts. Or either company will provide all this in-house training before assigning any domain specific task to testers.

There is no specific stage where you need this domain knowledge. You need to apply your domain knowledge in each and every software testing life cycle.

Learn unix in interactive way

Hi Dear friends.
I am sharing a file with you with which you can become really champ of unix administration and you will love it.
Have a look what it contains in Day 5 tutorial.

Interactive unix 

Best of luck and do give me feedbacks at
jainhimanshu_1986@yahoo.co.in
9899180227