The document discusses software testing, which involves executing a program or application to evaluate properties like meeting requirements, responding correctly to inputs, performing functions in an acceptable time, usability, installability, and achieving stakeholder desires. Software testing aims to find bugs and provide information about quality and failure risk. It discusses roles, methods, and economics of software testing.
Design for Testability: A Tutorial for Devs and TestersTechWell
Testability is the degree to which a system can be effectively and efficiently tested. This key software attribute indicates whether testing (and subsequent maintenance) will be easy and cheap—or difficult and expensive. In the worst case, a lack of testability means that some components of the system cannot be tested at all. Testability is not free; it must be explicitly designed into the system through adequate design for testability. Peter Zimmerer describes influencing factors (controllability, visibility, operability, stability, simplicity) and constraints (conflicting nonfunctional requirements, legacy code), and shares his experiences implementing and testing highly-testable software. Peter offers practical guidance on the key actions: (1) designing well-defined control and observation points in the architecture, and (2) specifying testability needs for test automation early. He shares creative and innovative approaches to overcome failures caused by deficiencies in testability. Peter presents a new, comprehensive strategy for testability design that can be implemented to gain the benefits in a cost-efficient manner.
Design for Testability: A Tutorial for Devs and TestersTechWell
Testability is the degree to which a system can be effectively and efficiently tested. This key software attribute indicates whether testing (and subsequent maintenance) will be easy and cheap—or difficult and expensive. In the worst case, a lack of testability means that some components of the system cannot be tested at all. Testability is not free; it must be explicitly designed into the system through adequate design for testability. Peter Zimmerer describes influencing factors (controllability, visibility, operability, stability, simplicity) and constraints (conflicting nonfunctional requirements, legacy code), and shares his experiences implementing and testing highly-testable software. Peter offers practical guidance on the key actions: (1) designing well-defined control and observation points in the architecture, and (2) specifying testability needs for test automation early. He shares creative and innovative approaches to overcome failures caused by deficiencies in testability. Peter presents a new, comprehensive strategy for testability design that can be implemented to gain the benefits in a cost-efficient manner.
Software Testing and Quality Assurance Assignment 3Gurpreet singh
Short questions :
Que 1 : Define Software Testing.
Que 2 : What is risk identification ?
Que 3 : What is SCM ?
Que 4 : Define Debugging.
Que 5 : Explain Configuration audit.
Que 6 : Differentiate between white box testing & black box testing.
Que 7 : What do you mean by metrics ?
Que 8 : What do you mean by version control ?
Que 9 : Explain Object Oriented Software Engineering.
Que 10 : What are the advantages and disadvantages of manual testing tools ?
Long Questions:
Que 1 : What do you mean by baselines ? Explain their importance.
Que 2 : What do you mean by change control ? Explain the various steps in detail.
Que 3 : Explain various types of testing in detail.
Que 4 : Differentiate between automated testing and manual testing.
Que 5 : What is web engineering ? Explain in detail its model and features.
Software testing is an activity which is aimed for evaluating quality of a program and also for improving it, by identifying defects and problems. Software testing strives for achieving its goal (both implicit and explicit) but it has certain limitations, still testing can be done more effectively if certain established principles are to be followed. In spite of having limitations, software testing continues to dominate other verification techniques like static analysis, model checking and proofs. So it is indispensable to understand the goals, principles and limitations of software testing so that the effectiveness of software testing could be maximized.
Ομιλία της Κωνσταντίνας Αγγελέτου, συν ιδρύτριας της εταιρίας πολιτισμού Πλέγμα. Η ομίλια πραγματοποιήθηκε στο Hilton 06/02/2016 στο Xxviii Opentourism στην Αθήνα με θέμα: "Νησιωτικότητα και τουρισμός: το παρόν και το μέλλον"
Software Testing and Quality Assurance Assignment 3Gurpreet singh
Short questions :
Que 1 : Define Software Testing.
Que 2 : What is risk identification ?
Que 3 : What is SCM ?
Que 4 : Define Debugging.
Que 5 : Explain Configuration audit.
Que 6 : Differentiate between white box testing & black box testing.
Que 7 : What do you mean by metrics ?
Que 8 : What do you mean by version control ?
Que 9 : Explain Object Oriented Software Engineering.
Que 10 : What are the advantages and disadvantages of manual testing tools ?
Long Questions:
Que 1 : What do you mean by baselines ? Explain their importance.
Que 2 : What do you mean by change control ? Explain the various steps in detail.
Que 3 : Explain various types of testing in detail.
Que 4 : Differentiate between automated testing and manual testing.
Que 5 : What is web engineering ? Explain in detail its model and features.
Software testing is an activity which is aimed for evaluating quality of a program and also for improving it, by identifying defects and problems. Software testing strives for achieving its goal (both implicit and explicit) but it has certain limitations, still testing can be done more effectively if certain established principles are to be followed. In spite of having limitations, software testing continues to dominate other verification techniques like static analysis, model checking and proofs. So it is indispensable to understand the goals, principles and limitations of software testing so that the effectiveness of software testing could be maximized.
Ομιλία της Κωνσταντίνας Αγγελέτου, συν ιδρύτριας της εταιρίας πολιτισμού Πλέγμα. Η ομίλια πραγματοποιήθηκε στο Hilton 06/02/2016 στο Xxviii Opentourism στην Αθήνα με θέμα: "Νησιωτικότητα και τουρισμός: το παρόν και το μέλλον"
Cuenta tu experiencia tu experiencia cuentaodc ensemble
Esa fue la presentación para la sesión, Cuenta tu experiencia, tu experiencia cuenta en la XIV convocatoria del Master de Gestión Cultural, teatro, música y danza del ICCMU, Universidad Complutense de Madrid. Gracias por la atención fue un encanto !!!!
Gradle is great for creating automated build tasks. We will explain why and how to code your own gradle plugins and make your build code reusable across projects.
This paper describes the different techniques of testing the software. This paper explicitly addresses the idea for testability and the important thing is that the testing itself-not just by saying that testability is a desirable goal, but by showing how to do it. Software testing is the process we used to measure the quality of developed software. Software Testing is not just about error-finding and their solution but also about checking the client requirements and testing that those requirements are met by the software solution. It is the most important functional phase in the Software Development Life Cycle(SDLC) as it exhibits all mistakes, flaws and errors in the developed software. Without finding these errors, technically termed as ‘bugs,’ software development is not considered to be complete. Hence, software testing becomes an important parameter for assuring quality of the software product. We discuss here about when to start and when to stop the testing of software. How errors or Bugs are formed and rectified. How software testing is done i.e. with the help of Team Work.
Software testing for project report .pdfKamal Acharya
Methods of Software Testing There are two basic methods of performing software testing: 1. Manual testing 2. Automated testing Manual Software Testing As the name would imply, manual software testing is the process of an individual or individuals manually testing software. This can take the form of navigating user interfaces, submitting information, or even trying to hack the software or underlying database. As one might presume, manual software testing is labor-intensive and slow.
Analysis and Design of Algorithms (ADA): An In-depth Exploration
Introduction:
The field of computer science is heavily reliant on algorithms to solve complex problems efficiently. The analysis and design of algorithms (ADA) is a fundamental area of study that focuses on understanding and creating efficient algorithms. This comprehensive overview will delve into the various aspects of ADA, including its importance, key concepts, techniques, and applications.
Importance of ADA:
Efficient algorithms play a critical role in various domains, including software development, data analysis, artificial intelligence, and optimization. ADA provides the tools and techniques necessary to design algorithms that are both correct and efficient. By analyzing the performance characteristics of algorithms, ADA enables computer scientists and engineers to develop solutions that save time, resources, and computational power.
Key Concepts in ADA:
Correctness: ADA emphasizes the importance of designing algorithms that produce correct outputs for all possible inputs. Techniques like mathematical proofs and induction are used to establish the correctness of algorithms.
Complexity Analysis: ADA seeks to analyze the efficiency of algorithms by examining their time and space complexity. Time complexity measures the amount of time required by an algorithm to execute, while space complexity measures the amount of memory consumed.
Asymptotic Notations: ADA employs asymptotic notations, such as Big O, Omega, and Theta, to express the growth rates of functions and classify the efficiency of algorithms. These notations allow for a concise comparison of algorithmic performance.
Algorithm Design Paradigms: ADA explores various design paradigms, including divide and conquer, dynamic programming, greedy algorithms, and backtracking. Each paradigm offers a systematic approach to solving problems efficiently.
Techniques in ADA:
Divide and Conquer: This technique involves breaking down a problem into smaller subproblems, solving them independently, and combining the solutions to obtain the final result. Well-known algorithms like Merge Sort and Quick Sort utilize the divide and conquer approach.
Dynamic Programming: Dynamic programming breaks down a complex problem into a series of overlapping subproblems and solves them in a bottom-up manner. This technique optimizes efficiency by storing and reusing intermediate results. The Fibonacci sequence calculation is a classic example of dynamic programming.
Greedy Algorithms: Greedy algorithms make locally optimal choices at each step, with the hope of achieving a global optimal solution. These algorithms are efficient but may not always yield the best overall solution. The Huffman coding algorithm for data compression is a widely used example of a greedy algorithm.
Backtracking: Backtracking involves searching for a solution to a problem by incrementally building a solution and undoing the choices that lead to dead-ends.
JIMS Vasant KunjII is the Top institute for BCA. JIMS is one of the Best BCA Colleges in Delhi which offers best placements in Top IT Companies in Delhi NCR. It is amongst the top A+ Category highest ranked colleges in Delhi, provides 3 years Regular Degree from UGC Approved University.
This unit of Software Testing is a part of BCA 5th sem syllabi.
Why Software Testing is Crucial in Software Development_.pdfXDuce Corporation
Software testing is the process of verifying and then confirming that a software application or product
performs as expected or not. Testing has its own set of advantages like bug prevention, lower costs of
development, and comparatively better performance.
The software cannot be said to be bug-free from the start. Therefore, software developers might strive
to write code that will reduce the number and severity of flaws that are already there. However, the
majority of bugs are latent and only emerge when the conditions are right.
Testing is the process of evaluating a system or its component(s) with the intent to find whether it satisfies the specified requirements or not. In simple words, testing is executing a system in order to identify any gaps, errors, or missing requirements in contrary to the actual requirements.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
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In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
DevOps and Testing slides at DASA ConnectKari Kakkonen
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GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4
Software testing
1. 1
Software testing
Software testing is an investigation conducted to provide stakeholders with information about the quality of the product or service under test. Software testing
can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Test
techniques include, but are not limited to, the process of executing a program or application with the intent of finding software bugs (errors or other defects).
It involves the execution of a software component or system to evaluate one or more properties of interest. In general, these properties indicate the extent to
which the component or system under test:
meets the requirements that guided its design and development,
responds correctly to all kinds of inputs,
performs its functions within an acceptable time,
is sufficiently usable,
can be installed and run in its intended environments, and
achieves the general result its stakeholders desire.
As the number of possible tests for even simple software components is practically infinite, all software testing uses some strategy to select tests that are
feasible for the available time and resources. As a result, software testing typically (but not exclusively) attempts to execute a program or application with the
intent of finding software bugs (errors or other defects).
Software testing can provide objective, independent information about the quality of software and risk of its failure to users and/or sponsors.
Software testing can be conducted as soon as executable software (even if partially complete) exists. The overall approach to software development often
determines when and how testing is conducted. For example, in a phased process, most testing occurs after system requirements have been defined and then
implemented in testable programs. In contrast, under an Agile approach, requirements, programming, and testing are often done concurrently.
Overview
Although testing can precisely determine the correctness of software under the assumption of some specific hypotheses (see hierarchy of testing difficulty below),
testing cannot identify all the defects within software. Instead, it furnishes a criticism or comparison that compares the state and behavior of the product
against oracles—principles or mechanisms by which someone might recognize a problem. These oracles may include (but are not limited to)
specifications, contracts, comparable products, past versions of the same product, inferences about intended or expected purpose, user or customer
expectations, relevant standards, applicable laws, or other criteria.
A primary purpose of testing is to detect software failures so that defects may be discovered and corrected. Testing cannot establish that a product functions
properly under all conditions but can only establish that it does not function properly under specific conditions. The scope of software testing often includes
examination of code as well as execution of that code in various environments and conditions as well as examining the aspects of code: does it do what it is
supposed to do and do what it needs to do. In the current culture of software development, a testing organization may be separate from the development team.
There are various roles for testing team members. Information derived from software testing may be used to correct the process by which software is developed.
Every software product has a target audience. For example, the audience for video game software is completely different from banking software. Therefore,
when an organization develops or otherwise invests in a software product, it can assess whether the software product will be acceptable to its end users, its
target audience, its purchasers and other stakeholders. Software testing is the process of attempting to make this assessment.
Defects and failures
Not all software defects are caused by coding errors. One common source of expensive defects is requirement gaps, e.g., unrecognized requirements which
result in errors of omission by the program designer. Requirement gaps can often be non-functional requirements such
as testability, scalability, maintainability, usability, performance, andsecurity.
Software faults occur through the following processes. A programmer makes an error (mistake), which results in a defect (fault, bug) in the software source
code. If this defect is executed, in certain situations the system will produce wrong results, causing a failure. Not all defects will necessarily result in failures. For
example, defects in dead code will never result in failures. A defect can turn into a failure when the environment is changed. Examples of these changes in
environment include the software being run on a newcomputer hardware platform, alterations in source data, or interacting with different software. A single
defect may result in a wide range of failure symptoms.
Input combinations and preconditions
A fundamental problem with software testing is that testing under all combinations of inputs and preconditions (initial state) is not feasible, even with a simple
product. This means that the number of defects in a software product can be very large and defects that occur infrequently are difficult to find in testing. More
significantly, non-functionaldimensions of quality (how it is supposed to be versus what it is supposed to do)—
usability, scalability, performance, compatibility, reliability—can be highly subjective; something that constitutes sufficient value to one person may be intolerable
to another.
Software developers can't test everything, but they can use combinatorial test design to identify the minimum number of tests needed to get the coverage they
want. Combinatorial test design enables users to get greater test coverage with fewer tests. Whether they are looking for speed or test depth, they can use
combinatorial test design methods to build structured variation into their test cases. Note that "coverage", as used here, is referring to combinatorial coverage,
not requirements coverage.
Economics
A study conducted by NIST in 2002 reports that software bugs cost the U.S. economy $59.5 billion annually. More than a third of this cost could be avoided if
better software testing was performed.
It is commonly believed that the earlier a defect is found, the cheaper it is to fix it. The following table shows the cost of fixing the defect depending on the stage
it was found. For example, if a problem in the requirements is found only post-release, then it would cost 10–100 times more to fix than if it had already been
found by the requirements review. With the advent of modern continuous deployment practices and cloud-based services, the cost of re-deployment and
maintenance may lessen over time.
2. 2
Cost to fix a defect
Time detected
Requirements Architecture Construction System test Post-release
Time introduced
Requirements 1× 3× 5–10× 10× 10–100×
Architecture – 1× 10× 15× 25–100×
Construction – – 1× 10× 10–25×
The data from which this table is extrapolated is scant. Laurent Bossavit says in his analysis:
The “smaller projects” curve turns out to be from only two teams of first-year students, a sample size so small that extrapolating to “smaller projects in general”
is totally indefensible. The GTE study does not explain its data, other than to say it came from two projects, one large and one small. The paper cited for the
Bell Labs “Safeguard” project specifically disclaims having collected the fine-grained data that Boehm’s data points suggest. The IBM study (Fagan’s paper)
contains claims which seem to contradict Boehm’s graph, and no numerical results which clearly correspond to his data points.
Boehm doesn’t even cite a paper for the TRW data, except when writing for “Making Software” in 2010, and there he cited the original 1976 article. There exists
a large study conducted at TRW at the right time for Boehm to cite it, but that paper doesn’t contain the sort of data that would support Boehm’s claims.[
Roles
Software testing can be done by software testers. Until the 1980s, the term "software tester" was used generally, but later it was also seen as a separate
profession. Regarding the periods and the different goals in software testing, different roles have been established: manager, test lead, test analyst, test
designer, tester, automation developer, andtest administrator.
History
The separation of debugging from testing was initially introduced by Glenford J. Myers in 1979. Although his attention was on breakage testing ("a successful
test is one that finds a bug") it illustrated the desire of the software engineering community to separate fundamental development activities, such as debugging,
from that of verification.Dave Gelperin and William C. Hetzel classified in 1988 the phases and goals in software testing in the following stages:
Until 1956 – Debugging oriented[
1957–1978 – Demonstration oriented
1979–1982 – Destruction oriented[
1983–1987 – Evaluation oriented
1988–2000 – Prevention oriented
Testing methods
Static vs. dynamic testing
There are many approaches available in software testing. Reviews, walkthroughs, or inspections are referred to as static testing, whereas actually executing
programmed code with a given set of test cases is referred to as dynamic testing. Static testing is often implicit, as proofreading, plus when programming
tools/text editors check source code structure or compilers (pre-compilers) check syntax and data flow as static program analysis. Dynamic testing takes place
when the program itself is run. Dynamic testing may begin before the program is 100% complete in order to test particular sections of code and are applied to
discrete functions or modules. Typical techniques for this are either using stubs/drivers or execution from a debugger environment.
Static testing involves verification, whereas dynamic testing involves validation. Together they help improve software quality. Among the techniques for static
analysis, mutation testing can be used to ensure the test-cases will detect errors which are introduced by mutating the source code.
The box approach
Software testing methods are traditionally divided into white- and black-box testing. These two approaches are used to describe the point of view that a test
engineer takes when designing test cases.
White-Box testing
White-box testing (also known as clear box testing, glass box testing, transparent box testing and structural testing) tests internal structures or workings
of a program, as opposed to the functionality exposed to the end-user. In white-box testing an internal perspective of the system, as well as programming skills,
are used to design test cases. The tester chooses inputs to exercise paths through the code and determine the appropriate outputs. This is analogous to testing
nodes in a circuit, e.g. in-circuit testing (ICT).
While white-box testing can be applied at the unit, integration and system levels of the software testing process, it is usually done at the unit level. It can test
paths within a unit, paths between units during integration, and between subsystems during a system–level test. Though this method of test design can uncover
many errors or problems, it might not detect unimplemented parts of the specification or missing requirements.
Techniques used in white-box testing include:
API testing (application programming interface) – testing of the application using public and private APIs
Code coverage – creating tests to satisfy some criteria of code coverage (e.g., the test designer can create tests to cause all statements in the program
to be executed at least once)
3. 3
Fault injection methods – intentionally introducing faults to gauge the efficacy of testing strategies
Mutation testing methods
Static testing methods
Code coverage tools can evaluate the completeness of a test suite that was created with any method, including black-box testing. This allows the software team
to examine parts of a system that are rarely tested and ensures that the most important function points have been tested.[23]
Code coverage as a software
metric can be reported as a percentage for:
Function coverage, which reports on functions executed
Statement coverage, which reports on the number of lines executed to complete the test
100% statement coverage ensures that all code paths or branches (in terms of control flow) are executed at least once. This is helpful in ensuring correct
functionality, but not sufficient since the same code may process different inputs correctly or incorrectly.
Black-box testing
Black box diagram
Black-box testing treats the software as a "black box", examining functionality without any knowledge of internal implementation. The testers are only
aware of what the software is supposed to do, not how it does it. Black-box testing methods include: equivalence partitioning, boundary value analysis, all-
pairs testing, state transition tables, decision table testing, fuzz testing, model-based testing, use case testing, exploratory testing and specification-based
testing.
Specification-based testing aims to test the functionality of software according to the applicable requirements. This level of testing usually requires
thorough test cases to be provided to the tester, who then can simply verify that for a given input, the output value (or behavior), either "is" or "is not" the
same as the expected value specified in the test case. Test cases are built around specifications and requirements, i.e., what the application is supposed
to do. It uses external descriptions of the software, including specifications, requirements, and designs to derive test cases. These tests can
be functional or non-functional, though usually functional.
Specification-based testing may be necessary to assure correct functionality, but it is insufficient to guard against complex or high-risk situations.
One advantage of the black box technique is that no programming knowledge is required. Whatever biases the programmers may have had, the tester
likely has a different set and may emphasize different areas of functionality. On the other hand, black-box testing has been said to be "like a walk in a dark
labyrinth without a flashlight. Because they do not examine the source code, there are situations when a tester writes many test cases to check something
that could have been tested by only one test case, or leaves some parts of the program untested.
This method of test can be applied to all levels of software testing: unit, integration, system and acceptance. It typically comprises most if not all testing at
higher levels, but can also dominate unit testing as well.
Visual testing
The aim of visual testing is to provide developers with the ability to examine what was happening at the point of software failure by presenting the data in
such a way that the developer can easily find the information he or she requires, and the information is expressed clearly.
At the core of visual testing is the idea that showing someone a problem (or a test failure), rather than just describing it, greatly increases clarity and
understanding. Visual testing therefore requires the recording of the entire test process – capturing everything that occurs on the test system in video
format. Output videos are supplemented by real-time tester input via picture-in-a-picture webcam and audio commentary from microphones.
Visual testing provides a number of advantages. The quality of communication is increased dramatically because testers can show the problem (and the
events leading up to it) to the developer as opposed to just describing it and the need to replicate test failures will cease to exist in many cases. The
developer will have all the evidence he or she requires of a test failure and can instead focus on the cause of the fault and how it should be fixed.
Visual testing is particularly well-suited for environments that deploy agile methods in their development of software, since agile methods require greater
communication between testers and developers and collaboration within small teams.
Ad hoc testing and exploratory testing are important methodologies for checking software integrity, because they require less preparation time to
implement, while the important bugs can be found quickly. In ad hoc testing, where testing takes place in an improvised, impromptu way, the ability of a
test tool to visually record everything that occurs on a system becomes very important.
Visual testing is gathering recognition in customer acceptance and usability testing, because the test can be used by many individuals involved in the
development process. For the customer, it becomes easy to provide detailed bug reports and feedback, and for program users, visual testing can record
user actions on screen, as well as their voice and image, to provide a complete picture at the time of software failure for the developer.
Further information: Graphical user interface testing
Grey-box testing
Main article: Gray box testing
Grey-box testing (American spelling: gray-box testing) involves having knowledge of internal data structures and algorithms for purposes of designing
tests, while executing those tests at the user, or black-box level. The tester is not required to have full access to the software's source code. Manipulating
input data and formatting output do not qualify as grey-box, because the input and output are clearly outside of the "black box" that we are calling the
system under test. This distinction is particularly important when conducting integration testing between two modules of code written by two different
developers, where only the interfaces are exposed for test.
However, tests that require modifying a back-end data repository such as a database or a log file does qualify as grey-box, as the user would not normally
be able to change the data repository in normal production operations. Grey-box testing may also include reverse engineering to determine, for instance,
boundary values or error messages.
By knowing the underlying concepts of how the software works, the tester makes better-informed testing choices while testing the software from outside.
Typically, a grey-box tester will be permitted to set up an isolated testing environment with activities such as seeding a database. The tester can observe
the state of the product being tested after performing certain actions such as executing SQL statements against the database and then executing queries
to ensure that the expected changes have been reflected. Grey-box testing implements intelligent test scenarios, based on limited information. This will
particularly apply to data type handling, exception handling, and so on.
4. 4
Testing levels
There are generally four recognized levels of tests: unit testing, integration testing, system testing, and acceptance testing. Tests are frequently grouped
by where they are added in the software development process, or by the level of specificity of the test. The main levels during the development process
as defined by the SWEBOK guide are unit-, integration-, and system testing that are distinguished by the test target without implying a specific process
model. Other test levels are classified by the testing objective.
Unit testing
Main article: Unit testing
Unit testing, also known as component testing, refers to tests that verify the functionality of a specific section of code, usually at the function level. In an
object-oriented environment, this is usually at the class level, and the minimal unit tests include the constructors and destructors.
These types of tests are usually written by developers as they work on code (white-box style), to ensure that the specific function is working as expected.
One function might have multiple tests, to catch corner cases or other branches in the code. Unit testing alone cannot verify the functionality of a piece of
software, but rather is used to ensure that the building blocks of the software work independently from each other.
Unit testing is a software development process that involves synchronized application of a broad spectrum of defect prevention and detection strategies
in order to reduce software development risks, time, and costs. It is performed by the software developer or engineer during the construction phase of the
software development lifecycle. Rather than replace traditional QA focuses, it augments it. Unit testing aims to eliminate construction errors before code
is promoted to QA; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall development and QA
process.
Depending on the organization's expectations for software development, unit testing might include static code analysis, data flow analysis, metrics analysis,
peer code reviews, code coverage analysis and other software verification practices.
Integration testing
Main article: Integration testing
Integration testing is any type of software testing that seeks to verify the interfaces between components against a software design. Software components
may be integrated in an iterative way or all together ("big bang"). Normally the former is considered a better practice since it allows interface issues to be
located more quickly and fixed.
Integration testing works to expose defects in the interfaces and interaction between integrated components (modules). Progressively larger groups of
tested software components corresponding to elements of the architectural design are integrated and tested until the software works as a system.
Component interface testing[edit]
The practice of component interface testing can be used to check the handling of data passed between various units, or subsystem components, beyond
full integration testing between those units. The data being passed can be considered as "message packets" and the range or data types can be checked,
for data generated from one unit, and tested for validity before being passed into another unit. One option for interface testing is to keep a separate log file
of data items being passed, often with a timestamp logged to allow analysis of thousands of cases of data passed between units for days or weeks. Tests
can include checking the handling of some extreme data values while other interface variables are passed as normal values. Unusual data values in an
interface can help explain unexpected performance in the next unit. Component interface testing is a variation of black-box testing, with the focus on the
data values beyond just the related actions of a subsystem component.
System testing
Main article: System testing
System testing, or end-to-end testing, tests a completely integrated system to verify that it meets its requirements.[37]
For example, a system test might
involve testing a logon interface, then creating and editing an entry, plus sending or printing results, followed by summary processing or deletion (or
archiving) of entries, then logoff.
In addition, the software testing should ensure that the program, as well as working as expected, does not also destroy or partially corrupt its operating
environment or cause other processes within that environment to become inoperative (this includes not corrupting shared memory, not consuming or
locking up excessive resources and leaving any parallel processes unharmed by its presence).
Acceptance testing
Main article: Acceptance testing
At last the system is delivered to the user for Acceptance testing.
Testing Types
Installation testing
Main article: Installation testing
An installation test assures that the system is installed correctly and working at actual customer's hardware.
Compatibility testing
Main article: Compatibility testing
A common cause of software failure (real or perceived) is a lack of its compatibility with other application software, operating systems (or operating
system versions, old or new), or target environments that differ greatly from the original (such as a terminal or GUI application intended to be run on
the desktop now being required to become a web application, which must render in a web browser). For example, in the case of a lack of backward
compatibility, this can occur because the programmers develop and test software only on the latest version of the target environment, which not all users
may be running. This results in the unintended consequence that the latest work may not function on earlier versions of the target environment, or on older
hardware that earlier versions of the target environment was capable of using. Sometimes such issues can be fixed by proactively abstracting operating
system functionality into a separate program module or library.
Smoke and sanity testing
Sanity testing determines whether it is reasonable to proceed with further testing.
Smoke testing consists of minimal attempts to operate the software, designed to determine whether there are any basic problems that will prevent it from
working at all. Such tests can be used as build verification test.
5. 5
Regression testing
Main article: Regression testing
Regression testing focuses on finding defects after a major code change has occurred. Specifically, it seeks to uncover software regressions, as degraded
or lost features, including old bugs that have come back. Such regressions occur whenever software functionality that was previously working, correctly,
stops working as intended. Typically, regressions occur as an unintended consequence of program changes, when the newly developed part of the
software collides with the previously existing code. Common methods of regression testing include re-running previous sets of test-cases and checking
whether previously fixed faults have re-emerged. The depth of testing depends on the phase in the release process and the risk of the added features.
They can either be complete, for changes added late in the release or deemed to be risky, or be very shallow, consisting of positive tests on each feature,
if the changes are early in the release or deemed to be of low risk. Regression testing is typically the largest test effort in commercial software
development, due to checking numerous details in prior software features, and even new software can be developed while using some old test-cases to
test parts of the new design to ensure prior functionality is still supported.
Acceptance testing
Main article: Acceptance testing
Acceptance testing can mean one of two things:
1. A smoke test is used as an acceptance test prior to introducing a new build to the main testing process, i.e. before integration or regression.
2. Acceptance testing performed by the customer, often in their lab environment on their own hardware, is known as user acceptance testing (UAT).
Acceptance testing may be performed as part of the hand-off process between any two phases of development.
Alpha testing
Alpha testing is simulated or actual operational testing by potential users/customers or an independent test team at the developers' site. Alpha testing is
often employed for off-the-shelf software as a form of internal acceptance testing, before the software goes to beta testing.
Beta testing
Beta testing comes after alpha testing and can be considered a form of external user acceptance testing. Versions of the software, known as beta versions,
are released to a limited audience outside of the programming team. The software is released to groups of people so that further testing can ensure the
product has few faults or bugs. Sometimes, beta versions are made available to the open public to increase the feedback field to a maximal number of
future users.
Functional vs non-functional testing
Functional testing refers to activities that verify a specific action or function of the code. These are usually found in the code requirements documentation,
although some development methodologies work from use cases or user stories. Functional tests tend to answer the question of "can the user do this" or
"does this particular feature work."
Non-functional testing refers to aspects of the software that may not be related to a specific function or user action, such as scalability or other performance,
behavior under certain constraints, or security. Testing will determine the breaking point, the point at which extremes of scalability or performance leads
to unstable execution. Non-functional requirements tend to be those that reflect the quality of the product, particularly in the context of the suitability
perspective of its users.
Destructive testing
Main article: Destructive testing
Destructive testing attempts to cause the software or a sub-system to fail. It verifies that the software functions properly even when it receives invalid or
unexpected inputs, thereby establishing the robustness of input validation and error-management routines. Software fault injection, in the form of fuzzing,
is an example of failure testing. Various commercial non-functional testing tools are linked from the software fault injection page; there are also numerous
open-source and free software tools available that perform destructive testing.
Further information: Exception handling and Recovery testing
Software performance testing
Performance testing is generally executed to determine how a system or sub-system performs in terms of responsiveness and stability under a particular
workload. It can also serve to investigate, measure, validate or verify other quality attributes of the system, such as scalability, reliability and resource
usage.
Load testing is primarily concerned with testing that the system can continue to operate under a specific load, whether that be large quantities of data or
a large number of users. This is generally referred to as software scalability. The related load testing activity of when performed as a non-functional activity
is often referred to as endurance testing.Volume testing is a way to test software functions even when certain components (for example a file or database)
increase radically in size. Stress testing is a way to test reliability under unexpected or rare workloads. Stability testing (often referred to as load or
endurance testing) checks to see if the software can continuously function well in or above an acceptable period.
There is little agreement on what the specific goals of performance testing are. The terms load testing, performance testing, scalability testing, and volume
testing, are often used interchangeably.
Real-time software systems have strict timing constraints. To test if timing constraints are met, real-time testing is used.
Usability testing
Usability testing is to check if the user interface is easy to use and understand. It is concerned mainly with the use of the application.
Accessibility testing
Accessibility testing may include compliance with standards such as:
Americans with Disabilities Act of 1990
Section 508 Amendment to the Rehabilitation Act of 1973
Web Accessibility Initiative (WAI) of the World Wide Web Consortium (W3C)
6. 6
Security testing
Security testing is essential for software that processes confidential data to prevent system intrusion by hackers.
Internationalization and localization
The general ability of software to be internationalized and localized can be automatically tested without actual translation, by using pseudolocalization. It
will verify that the application still works, even after it has been translated into a new language or adapted for a new culture (such as different currencies
or time zones).
Actual translation to human languages must be tested, too. Possible localization failures include:
Software is often localized by translating a list of strings out of context, and the translator may choose the wrong translation for an ambiguous source
string.
Technical terminology may become inconsistent if the project is translated by several people without proper coordination or if the translator is
imprudent.
Literal word-for-word translations may sound inappropriate, artificial or too technical in the target language.
Untranslated messages in the original language may be left hard coded in the source code.
Some messages may be created automatically at run time and the resulting string may be ungrammatical, functionally incorrect, misleading or
confusing.
Software may use a keyboard shortcut which has no function on the source language's keyboard layout, but is used for typing characters in the layout
of the target language.
Software may lack support for the character encoding of the target language.
Fonts and font sizes which are appropriate in the source language may be inappropriate in the target language; for example, CJK characters may
become unreadable if the font is too small.
A string in the target language may be longer than the software can handle. This may make the string partly invisible to the user or cause the software
to crash or malfunction.
Software may lack proper support for reading or writing bi-directional text.
Software may display images with text that was not localized.
Localized operating systems may have differently named system configuration files and environment variables and different formats for
date and currency.
Development testing
Development Testing is a software development process that involves synchronized application of a broad spectrum of defect prevention and detection
strategies in order to reduce software development risks, time, and costs. It is performed by the software developer or engineer during the construction
phase of the software development lifecycle. Rather than replace traditional QA focuses, it augments it. Development Testing aims to eliminate construction
errors before code is promoted to QA; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall
development and QA process.
Depending on the organization's expectations for software development, Development Testing might include static code analysis, data flow analysis
metrics analysis, peer code reviews, unit testing, code coverage analysis, traceability, and other software verification practices.
A/B testing
A/B testing is basically a comparison of two outputs, generally when only one variable has changed: run a test, change one thing, run the test again,
compare the results. This is more useful with more small-scale situations, but very useful in fine-tuning any program. With more complex projects,
multivariant testing can be done.
Concurrent testing
In concurrent testing, the focus is more on what the performance is like when continuously running with normal input and under normal operation as
opposed to stress testing, or fuzz testing. Memory leak is more easily found and resolved using this method, as well as more basic faults.
Conformance testing or type testing
In software testing, conformance testing verifies that a product performs according to its specified standards. Compilers, for instance, are extensively
tested to determine whether they meet the recognized standard for that language.
Testing process
Traditional waterfall development model
A common practice of software testing is that testing is performed by an independent group of testers after the functionality is developed, before it is
shipped to the customer. This practice often results in the testing phase being used as a project buffer to compensate for project delays, thereby
compromising the time devoted to testing.
Another practice is to start software testing at the same moment the project starts and it is a continuous process until the project finishes.
Further information: Capability Maturity Model Integration and Waterfall model
Agile or Extreme development model
In contrast, some emerging software disciplines such as extreme programming and the agile software development movement, adhere to a "test-driven
software development" model. In this process, unit tests are written first, by the software engineers (often with pair programming in the extreme
programming methodology). Of course these tests fail initially; as they are expected to. Then as code is written it passes incrementally larger portions of
the test suites. The test suites are continuously updated as new failure conditions and corner cases are discovered, and they are integrated with any
regression tests that are developed. Unit tests are maintained along with the rest of the software source code and generally integrated into the build
process (with inherently interactive tests being relegated to a partially manual build acceptance process). The ultimate goal of this test process is to
achieve continuous integration where software updates can be published to the public frequently.
7. 7
This methodology increases the testing effort done by development, before reaching any formal testing team. In some other development models, most
of the test execution occurs after the requirements have been defined and the coding process has been completed.
Top-down and bottom-up
Bottom Up Testing is an approach to integrated testing where the lowest level components (modules, procedures, and functions) are tested first, then
integrated and used to facilitate the testing of higher level components. After the integration testing of lower level integrated modules, the next level of
modules will be formed and can be used for integration testing. The process is repeated until the components at the top of the hierarchy are tested. This
approach is helpful only when all or most of the modules of the same development level are ready. This method also helps to determine the levels of
software developed and makes it easier to report testing progress in the form of a percentage.
Top Down Testing is an approach to integrated testing where the top integrated modules are tested and the branch of the module is tested step by step
until the end of the related module.
In both, method stubs and drivers are used to stand-in for missing components and are replaced as the levels are completed.
A sample testing cycle
Although variations exist between organizations, there is a typical cycle for testing.[46]
The sample below is common among organizations employing
the Waterfall developmentmodel. The same practices are commonly found in other development models, but might not be as clear or explicit.
Requirements analysis: Testing should begin in the requirements phase of the software development life cycle. During the design phase, testers
work to determine what aspects of a design are testable and with what parameters those tests work.
Test planning: Test strategy, test plan, testbed creation. Since many activities will be carried out during testing, a plan is needed.
Test development: Test procedures, test scenarios, test cases, test datasets, test scripts to use in testing software.
Test execution: Testers execute the software based on the plans and test documents then report any errors found to the development team.
Test reporting: Once testing is completed, testers generate metrics and make final reports on their test effort and whether or not the software tested
is ready for release.
Test result analysis: Or Defect Analysis, is done by the development team usually along with the client, in order to decide what defects should be
assigned, fixed, rejected (i.e. found software working properly) or deferred to be dealt with later.
Defect Retesting: Once a defect has been dealt with by the development team, it is retested by the testing team. AKA Resolution testing.
Regression testing: It is common to have a small test program built of a subset of tests, for each integration of new, modified, or fixed software, in
order to ensure that the latest delivery has not ruined anything, and that the software product as a whole is still working correctly.
Test Closure: Once the test meets the exit criteria, the activities such as capturing the key outputs, lessons learned, results, logs, documents related
to the project are archived and used as a reference for future projects.
Automated testing
Many programming groups are relying more and more on automated testing, especially groups that use test-driven development. There are many
frameworks to write tests in, and continuous integration software will run tests automatically every time code is checked into a version control system.
While automation cannot reproduce everything that a human can do (and all the ways they think of doing it), it can be very useful for regression testing.
However, it does require a well-developed test suite of testing scripts in order to be truly useful.
Testing tools
Program testing and fault detection can be aided significantly by testing tools and debuggers. Testing/debug tools include features such as:
Program monitors, permitting full or partial monitoring of program code including:
Instruction set simulator, permitting complete instruction level monitoring and trace facilities
Program animation, permitting step-by-step execution and conditional breakpoint at source level or in machine code
Code coverage reports
Formatted dump or symbolic debugging, tools allowing inspection of program variables on error or at chosen points
Automated functional GUI testing tools are used to repeat system-level tests through the GUI
Benchmarks, allowing run-time performance comparisons to be made
Performance analysis (or profiling tools) that can help to highlight hot spots and resource usage
Some of these features may be incorporated into an Integrated Development Environment (IDE).
Measurement in software testing
Usually, quality is constrained to such topics as correctness, completeness, security, but can also include more technical requirements as described under
the ISOstandard ISO/IEC 9126, such as capability, reliability, efficiency, portability, maintainability, compatibility, and usability.
There are a number of frequently used software metrics, or measures, which are used to assist in determining the state of the software or the adequacy
of the testing.
Hierarchy of testing difficulty
Based on the amount of test cases required to construct a complete test suite in each context (i.e. a test suite such that, if it is applied to the implementation
under test, then we collect enough information to precisely determine whether the system is correct or incorrect according to some specification), a
hierarchy of testing difficulty has been proposed.[47] [48]
It includes the following testability classes:
Class I: there exists a finite complete test suite.
Class II: any partial distinguishing rate (i.e. any incomplete capability to distinguish correct systems from incorrect systems) can be reached with a
finite test suite.
8. 8
Class III: there exists a countable complete test suite.
Class IV: there exists a complete test suite.
Class V: all cases.
It has been proved that each class is strictly included into the next. For instance, testing when we assume that the behavior of the implementation under
test can be denoted by a deterministic finite-state machine for some known finite sets of inputs and outputs and with some known number of states belongs
to Class I (and all subsequent classes). However, if the number of states is not known, then it only belongs to all classes from Class II on. If the
implementation under test must be a deterministic finite-state machine failing the specification for a single trace (and its continuations), and its number of
states is unknown, then it only belongs to classes from Class III on. Testing temporal machines where transitions are triggered if inputs are produced within
some real-bounded interval only belongs to classes from Class IV on, whereas testing many non-deterministic systems only belongs to Class V (but not
all, and some even belong to Class I). The inclusion into Class I does not require the simplicity of the assumed computation model, as some testing cases
involving implementations written in any programming language, and testing implementations defined as machines depending on continuous magnitudes,
have been proved to be in Class I. Other elaborated cases, such as the testing framework by Matthew Hennessy under must semantics, and temporal
machines with rational timeouts, belong to Class II.
Testing artifacts
The software testing process can produce several artifacts.
Test plan
A test specification is called a test plan. The developers are well aware what test plans will be executed and this information is made available to
management and the developers. The idea is to make them more cautious when developing their code or making additional changes. Some companies
have a higher-level document called a test strategy.
Traceability matrix
A traceability matrix is a table that correlates requirements or design documents to test documents. It is used to change tests when related source
documents are changed, to select test cases for execution when planning for regression tests by considering requirement coverage.
Test case
A test case normally consists of a unique identifier, requirement references from a design specification, preconditions, events, a series of steps (also
known as actions) to follow, input, output, expected result, and actual result. Clinically defined a test case is an input and an expected result.[49]
This can
be as pragmatic as 'for condition x your derived result is y', whereas other test cases described in more detail the input scenario and what results might
be expected. It can occasionally be a series of steps (but often steps are contained in a separate test procedure that can be exercised against multiple
test cases, as a matter of economy) but with one expected result or expected outcome. The optional fields are a test case ID, test step, or order of execution
number, related requirement(s), depth, test category, author, and check boxes for whether the test is automatable and has been automated. Larger test
cases may also contain prerequisite states or steps, and descriptions. A test case should also contain a place for the actual result. These steps can be
stored in a word processor document, spreadsheet, database, or other common repository. In a database system, you may also be able to see past test
results, who generated the results, and what system configuration was used to generate those results. These past results would usually be stored in a
separate table.
Test script
A test script is a procedure, or programing code that replicates user actions. Initially the term was derived from the product of work created by automated
regression test tools. Test Case will be a baseline to create test scripts using a tool or a program.
Test suite
The most common term for a collection of test cases is a test suite. The test suite often also contains more detailed instructions or goals for each collection
of test cases. It definitely contains a section where the tester identifies the system configuration used during testing. A group of test cases may also contain
prerequisite states or steps, and descriptions of the following tests.
Test fixture or test data
In most cases, multiple sets of values or data are used to test the same functionality of a particular feature. All the test values and changeable environmental
components are collected in separate files and stored as test data. It is also useful to provide this data to the client and with the product or a project.
Test harness
The software, tools, samples of data input and output, and configurations are all referred to collectively as a test harness.
Certifications[edit]
Several certification programs exist to support the professional aspirations of software testers and quality assurance specialists. No certification now
offered actually requires the applicant to show their ability to test software. No certification is based on a widely accepted body of knowledge. This has led
some to declare that the testing field is not ready for certification.[50]
Certification itself cannot measure an individual's productivity, their skill, or practical
knowledge, and cannot guarantee their competence, or professionalism as a tester.
Software testing certification types
Exam-based: Formalized exams, which need to be passed; can also be learned by self-study [e.g., for ISTQB or QAI]
Education-based: Instructor-led sessions, where each course has to be passed [e.g., International Institute for Software Testing (IIST)]
Testing certifications
ISEB offered by the Information Systems Examinations Board
ISTQB Certified Tester, Foundation Level (CTFL) offered by the International Software Testing Qualification Board
ISTQB Certified Tester, Advanced Level (CTAL) offered by the International Software Testing Qualification Board
Quality assurance certifications
CSQE offered by the American Society for Quality (ASQ)
CQIA offered by the American Society for Quality (ASQ)
9. 9
Controversy
Some of the major software testing controversies include:
What constitutes responsible software testing?
Members of the "context-driven" school of testingbelieve that there are no "best practices" of testing, but rather that testing is a set of skills that allow the
tester to select or invent testing practices to suit each unique situation.
Agile vs. traditional
Should testers learn to work under conditions of uncertainty and constant change or should they aim at process "maturity"? The agile testing movement
has received growing popularity since 2006 mainly in commercial circles,[58][59]
whereas government and militarysoftware providers use this methodology
but also the traditional test-last models (e.g. in the Waterfall model).
Exploratory test vs. scripted
[61]
Should tests be designed at the same time as they are executed or should they be designed beforehand?
Manual testing vs. automated
Some writers believe that test automation is so expensive relative to its value that it should be used sparingly. More in particular, test-driven
development states that developers should write unit-tests, as those of XUnit, before coding the functionality. The tests then can be considered as a way
to capture and implement the requirements.
Software design vs. software implementation
Should testing be carried out only at the end or throughout the whole process?
Who watches the watchmen?
The idea is that any form of observation is also an interaction—the act of testing can also affect that which is being tested.[63]
Is the existence of the ISO 29119 software testing standard justified?
Significant opposition has formed out of the ranks of the context-driven school of software testing about the ISO 29119 standard. Professional testing
associations, such as The International Society for Software Testing, are driving the efforts to have the standard withdrawn.
Software verification and validation
Software testing is used in association with verification and validation:
Verification: Have we built the software right? (i.e., does it implement the requirements).
Validation: Have we built the right software? (i.e., do the deliverables satisfy the customer).
The terms verification and validation are commonly used interchangeably in the industry; it is also common to see these two terms incorrectly defined.
According to the IEEE Standard Glossary of Software Engineering Terminology:
Verification is the process of evaluating a system or component to determine whether the products of a given development phase satisfy the conditions
imposed at the start of that phase.
Validation is the process of evaluating a system or component during or at the end of the development process to determine whether it satisfies specified
requirements.
According to the ISO 9000 standard:
Verification is confirmation by examination and through provision of objective evidence that specified requirements have been fulfilled.
Validation is confirmation by examination and through provision of objective evidence that the requirements for a specific intended use or application have
been fulfilled.
Software quality assurance (SQA)
Software testing is a part of the software quality assurance (SQA) process. In SQA, software process specialists and auditors are concerned for the
software development process rather than just the artifacts such as documentation, code and systems. They examine and change the software engineering
process itself to reduce the number of faults that end up in the delivered software: the so-called "defect rate". What constitutes an "acceptable defect rate"
depends on the nature of the software; A flight simulator video game would have much higher defect tolerance than software for an actual airplane.
Although there are close links with SQA, testing departments often exist independently, and there may be no SQA function in some companies.
Software testing is a task intended to detect defects in software by contrasting a computer program's expected results with its actual results for a given set
of inputs. By contrast, QA (quality assurance) is the implementation of policies and procedures intended to prevent defects from occurring in the first place.