Optimized Order of Software Testing Techniques in Agile Process – a Systematic Approach
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Smoke Testing
International Journal of Scientific and Research Publications, Volume 4, Issue 2, February 2014 1 ISSN 2250-3153 Smoke Testing Vinod Kumar Chauhan Quality Assurance (QA), Impetus InfoTech Pvt. Ltd. (India) Abstract- Smoke testing is an end-to-end testing which determine the stability of new build by checking the crucial functionality of the application under test and used as criteria of accepting the new build for detailed testing. Index Terms- Software testing, acceptance testing, agile, build, regression testing, sanity testing I. INTRODUCTION The purpose of this research paper is to give details of smoke testing from the industry practices. II. SMOKE TESTING The purpose of smoke testing is to determine whether the new software build is stable or not so that the build could be used for detailed testing by the QA team and further work by the development team. If the build is stable i.e. the smoke test passes then build could be used by the QA and development team. On the stable build QA team performs functional testing for the newly added features/functionality and then performs regression testing depending upon the situation. But if the build is not stable i.e. the smoke fails then the build is rejected to the development team to fix the build issues and create a new build. Smoke Testing is generally done by the QA team but in certain situations, can be done by the development team. In that case the development team checks the stability of the build and deploy to QA only if the build is stable. In other case, whenever there is new build deployment to the QA environment then the team first performs the smoke test on the build and depending upon the results of smoke the decision to accept or reject the build is taken. -
Types of Software Testing
Types of Software Testing We would be glad to have feedback from you. Drop us a line, whether it is a comment, a question, a work proposition or just a hello. You can use either the form below or the contact details on the rightt. Contact details [email protected] +91 811 386 5000 1 Software testing is the way of assessing a software product to distinguish contrasts between given information and expected result. Additionally, to evaluate the characteristic of a product. The testing process evaluates the quality of the software. You know what testing does. No need to explain further. But, are you aware of types of testing. It’s indeed a sea. But before we get to the types, let’s have a look at the standards that needs to be maintained. Standards of Testing The entire test should meet the user prerequisites. Exhaustive testing isn’t conceivable. As we require the ideal quantity of testing in view of the risk evaluation of the application. The entire test to be directed ought to be arranged before executing it. It follows 80/20 rule which expresses that 80% of defects originates from 20% of program parts. Start testing with little parts and extend it to broad components. Software testers know about the different sorts of Software Testing. In this article, we have incorporated majorly all types of software testing which testers, developers, and QA reams more often use in their everyday testing life. Let’s understand them!!! Black box Testing The black box testing is a category of strategy that disregards the interior component of the framework and spotlights on the output created against any input and performance of the system. -
Smoke Testing What Is Smoke Testing?
Smoke Testing What is Smoke Testing? Smoke testing is the initial testing process exercised to check whether the software under test is ready/stable for further testing. The term ‘Smoke Testing’ is came from the hardware testing, in the hardware testing initial pass is done to check if it did not catch the fire or smoked in the initial switch on.Prior to start Smoke testing few test cases need to created once to use for smoke testing. These test cases are executed prior to start actual testing to checkcritical functionalities of the program is working fine. This set of test cases written such a way that all functionality is verified but not in deep. The objective is not to perform exhaustive testing, the tester need check the navigation’s & adding simple things, tester needs to ask simple questions “Can tester able to access software application?”, “Does user navigates from one window to other?”, “Check that the GUI is responsive” etc. Here are graphical representation of Smoke testing & Sanity testing in software testing: Smoke Sanity Testing Diagram The test cases can be executed manually or automated; this depends upon the project requirements. In this types of testing mainly focus on the important functionality of application, tester do not care about detailed testing of each software component, this can be cover in the further testing of application. The Smoke testing is typically executed by testers after every build is received for checking the build is in testable condition. This type of testing is applicable in the Integration Testing, System Testing and Acceptance Testing levels. -
Security Testing
ISSN 1866-5705 www.testingexperience.com free digital version print version 8,00 € printed in Germany 6 The Magazine for Professional Testers The MagazineforProfessional Security Testing © iStockphoto/alexandru_lamba June, 2009 © iStockphoto/Manu1174 ISTQB® Certified Tester Foundation Level for only 499,- € plus VAT ONLINE TRAINING English & German www.testingexperience.learntesting.com Certified Tester Advanced Level coming soon Editorial Dear readers, One of my professors at the university said once to all of us: Computer scientists are at some point criminals. What he meant was that we or some of us – computer scientists – at some point like to try things that are not that “legal”. The most of us are “clean”, but some of us are “free time hackers”! Nowadays the hackers are almost away from the 17 years old guy, trying to pen- etrate in some website and so on. They are now adults, with families, cars, pets, holidays and a job. They are professionals earning money for acting as such. Application Security is not only important and essential for the companies and their businesses, technology and employees. Application Security is a macroeco- nomic aspect for the countries. There are a lot of secret services or governments agencies working on getting technology or information by advance hacking the server and databases of top companies or governments worldwide. When we hear that some countries could be behind the penetration of the USA electricity net- work, you can imagine what is going on outside. Are we testers prepared for that job? I’m not! Last year we had the first tutorial by Manu Cohen about Application Security Testing. -
Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK
1 From Start-ups to Scale-ups: Opportunities and Open Problems for Static and Dynamic Program Analysis Mark Harman∗, Peter O’Hearn∗ ∗Facebook London and University College London, UK Abstract—This paper1 describes some of the challenges and research questions that target the most productive intersection opportunities when deploying static and dynamic analysis at we have yet witnessed: that between exciting, intellectually scale, drawing on the authors’ experience with the Infer and challenging science, and real-world deployment impact. Sapienz Technologies at Facebook, each of which started life as a research-led start-up that was subsequently deployed at scale, Many industrialists have perhaps tended to regard it unlikely impacting billions of people worldwide. that much academic work will prove relevant to their most The paper identifies open problems that have yet to receive pressing industrial concerns. On the other hand, it is not significant attention from the scientific community, yet which uncommon for academic and scientific researchers to believe have potential for profound real world impact, formulating these that most of the problems faced by industrialists are either as research questions that, we believe, are ripe for exploration and that would make excellent topics for research projects. boring, tedious or scientifically uninteresting. This sociological phenomenon has led to a great deal of miscommunication between the academic and industrial sectors. I. INTRODUCTION We hope that we can make a small contribution by focusing on the intersection of challenging and interesting scientific How do we transition research on static and dynamic problems with pressing industrial deployment needs. Our aim analysis techniques from the testing and verification research is to move the debate beyond relatively unhelpful observations communities to industrial practice? Many have asked this we have typically encountered in, for example, conference question, and others related to it. -
A Framework for Evaluating Performance of Software Testing Tools
INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020 ISSN 2277-8616 A Framework For Evaluating Performance Of Software Testing Tools Pramod Mathew Jacob, Prasanna Mani Abstract: Software plays a pivotal role in this technology era. Due to its increased applicable domains, quality of the software being developed is to be monitored and controlled. Software organization follows many testing methodologies to perform quality management. Testing methodologies can be either manual or automated. Automated testing tools got massive acceptability among software professionals due to its enhanced features and functionalities than that of manual testing. There are hundreds of test automation tools available, among which some perform exceptionally well. Due to the availability of large set of tools, it is a herculean task for the project manager to choose the appropriate automation tool, which is suitable for their project domain. In this paper, we derive a software testing tool selection model which evaluates the performance aspects of a script-based testing tool. Experimental evaluation proves that, it can be used to compare and evaluate various performance characteristics of commercially accepted test automation tools based on user experience as well as system performance. Index Terms: Automated testing, Software testing, Test script, Testing Tool, Test bed, Verification and Validation. —————————— ◆ —————————— 1 INTRODUCTION S OFTWARE is advanced in recent days by enhancing its applicable domains. Software is embedded in almost all electronic gadgets and systems. In this scenario the quality of the software plays a significant role. The customer or end – user should be satisfied which is primarily depended on quality and capability of the software being developed. -
Model-Based Api Testing for Smt Solvers
MODEL-BASED API TESTING FOR SMT SOLVERS Aina Niemetz ?y, Mathias Preiner ?y, Armin Biere ? ?Johannes Kepler University, Linz, Austria yStanford University, USA SMT Workshop 2017, July 22 – 23 Heidelberg, Germany SMT Solvers highly complex usually serve as back-end to some application key requirements: correctness robustness performance −! full verification difficult and still an open question −! solver development relies on traditional testing techniques 1/22 Testing of SMT Solvers State-of-the-art: unit tests regression test suite grammar-based black-box input fuzzing with FuzzSMT [SMT’09] generational input fuzzer for SMT-LIB v1 patched for SMT-LIB v2 compliance generates random but valid SMT-LIB input especially effective in combination with delta debugging not possible to test solver features not supported by the input language This work: model-based API fuzz testing −! generate random valid API call sequences 2/22 Model-Based API fuzz testing −! generate random valid API call sequences Previously: model-based API testing framework for SAT [TAP’13] implemented for the SAT solver Lingeling allows to test random solver configurations (option fuzzing) allows to replay erroneous solver behavior −! results promising for other solver back-ends Here: model-based API testing framework for SMT lifts SAT approach to SMT implemented for the SMT solver Boolector tailored to Boolector for QF_(AUF)BV with non-recursive first-order lambda terms −! effective and promising for other SMT solvers −! more general approach left to future -
Devsecops DEVELOPMENT & DEVOPS INFRASTRUCTURE
DevSecOps DEVELOPMENT & DEVOPS INFRASTRUCTURE CREATE SECURE APPLICATIONS PARASOFT’S APPROACH - BUILD SECURITY IN WITHOUT DISRUPTING THE Parasoft provides tools that help teams begin their security efforts as DEVELOPMENT PROCESS soon as the code is written, starting with static application security test- ing (SAST) via static code analysis, continuing through testing as part of Parasoft makes DevSecOps possible with API and the CI/CD system via dynamic application security testing (DAST) such functional testing, service virtualization, and the as functional testing, penetration testing, API testing, and supporting in- most complete support for important security stan- frastructure like service virtualization that enables security testing be- dards like CWE, OWASP, and CERT in the industry. fore the complete application is fully available. IMPLEMENT A SECURE CODING LIFECYCLE Relying on security specialists alone prevents the entire DevSecOps team from securing software and systems. Parasoft tooling enables the BENEFIT FROM THE team with security knowledge and training to reduce dependence on PARASOFT APPROACH security specialists alone. With a centralized SAST policy based on in- dustry standards, teams can leverage Parasoft’s comprehensive docs, examples, and embedded training while the code is being developed. ✓ Leverage your existing test efforts for Then, leverage existing functional/API tests to enhance the creation of security security tests – meaning less upfront cost, as well as less maintenance along the way. ✓ Combine quality and security to fully understand your software HARDEN THE CODE (“BUILD SECURITY IN”) Getting ahead of application security means moving beyond just test- ✓ Harden the code – don’t just look for ing into building secure software in the first place. -
Exploring Languages with Interpreters and Functional Programming Chapter 11
Exploring Languages with Interpreters and Functional Programming Chapter 11 H. Conrad Cunningham 24 January 2019 Contents 11 Software Testing Concepts 2 11.1 Chapter Introduction . .2 11.2 Software Requirements Specification . .2 11.3 What is Software Testing? . .3 11.4 Goals of Testing . .3 11.5 Dimensions of Testing . .3 11.5.1 Testing levels . .4 11.5.2 Testing methods . .6 11.5.2.1 Black-box testing . .6 11.5.2.2 White-box testing . .8 11.5.2.3 Gray-box testing . .9 11.5.2.4 Ad hoc testing . .9 11.5.3 Testing types . .9 11.5.4 Combining levels, methods, and types . 10 11.6 Aside: Test-Driven Development . 10 11.7 Principles for Test Automation . 12 11.8 What Next? . 15 11.9 Exercises . 15 11.10Acknowledgements . 15 11.11References . 16 11.12Terms and Concepts . 17 Copyright (C) 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 1 (662) 915-5358 Browser Advisory: The HTML version of this textbook requires a browser that supports the display of MathML. A good choice as of October 2018 is a recent version of Firefox from Mozilla. 2 11 Software Testing Concepts 11.1 Chapter Introduction The goal of this chapter is to survey the important concepts, terminology, and techniques of software testing in general. The next chapter illustrates these techniques by manually constructing test scripts for Haskell functions and modules. 11.2 Software Requirements Specification The purpose of a software development project is to meet particular needs and expectations of the project’s stakeholders. -
Model-Based API Testing for SMT Solvers∗
Model-Based API Testing for SMT Solvers∗ Aina Niemetz, Mathias Preiner, and Armin Biere Institute for Formal Models and Verification Johannes Kepler University, Linz, Austria Abstract Verification back ends such as SMT solvers are typically highly complex pieces of soft- ware with performance, correctness and robustness as key requirements. Full verification of SMT solvers, however, is difficult due to their complex nature and still an open question. Grammar-based black-box input fuzzing proved to be effective to uncover bugs in SMT solvers but is entirely input-based and restricted to a certain input language. State-of-the- art SMT solvers, however, usually provide a rich API, which often introduces additional functionality not supported by the input language. Previous work showed that applying model-based API fuzzing to SAT solvers is more effective than input fuzzing. In this pa- per, we introduce a model-based API testing framework for our SMT solver Boolector. Our experimental results show that model-based API fuzzing in combination with delta debugging techniques is effective for testing SMT solvers. 1 Introduction State-of-the-art Satisfiability Modulo Theories (SMT) solvers are typically highly complex pieces of software, and since they usually serve as back-end to some application, the level of trust in this application strongly depends on the level of trust in the underlying solver. Full verification of SMT solvers, however, is difficult due to their complex nature and still an open question. Hence, solver developers usually rely on traditional testing techniques such as unit and regression tests. At the SMT workshop in 2009, in [10] Brummayer et al. -
Continuous Testing for Devops Evolving Beyond Simple Automation
Technical Whitepaper 1 Continuous Testing for DevOps Evolving Beyond Simple Automation INTRODUCTION DevOps represents a cultural shift that stresses collaboration be- on acceleration. Moreover, adopting a bona fide Continuous Testing tween the business, developers, and IT professionals. Software test process (more than just automated tests running regularly) helps automation can enhance these connections and help organizations promote all of the core pillars of DevOps: Culture, Automation, Lean, achieve desired SDLC acceleration, but it’s important to recognize Metrics, and Sharing. that automation is just one piece of the DevOps puzzle. In this paper, we’ll explore why and how Continuous Testing’s real- Since testing is often one of the greatest constraints in the SDLC, time objective assessment of an application’s business risks is a optimizing quality processes to allow testing to begin earlier, as well critical component of DevOps. as shrink the amount of testing required, can have a marked impact DEVOPS PRINCIPLES There are several key pieces to understanding DevOps revolutions and they are often brought about by a compelling event at an organization, such as a shift to agile. As organizations start to move into an agile development methodology, they start to uncover other processes that can be accelerated, such as delivery by DevOps and testing by Continuous Testing. The acceleration that is set in motion via agile makes it necessary to accelerate the release schedule. In order to ensure a successful release, an organization must adopt continuous testing to make sure the conveyer belt does not break down. The modernization maturity model has these three distinct phases: AGILE Agile software development is a different way of thinking about approaching the challenge of development time. -
Empirical Evaluation of the Effectiveness and Reliability of Software Testing Adequacy Criteria and Reference Test Systems
Empirical Evaluation of the Effectiveness and Reliability of Software Testing Adequacy Criteria and Reference Test Systems Mark Jason Hadley PhD University of York Department of Computer Science September 2013 2 Abstract This PhD Thesis reports the results of experiments conducted to investigate the effectiveness and reliability of ‘adequacy criteria’ - criteria used by testers to determine when to stop testing. The research reported here is concerned with the empirical determination of the effectiveness and reliability of both tests sets that satisfy major general structural code coverage criteria and test sets crafted by experts for testing specific applications. We use automated test data generation and subset extraction techniques to generate multiple tests sets satisfying widely used coverage criteria (statement, branch and MC/DC coverage). The results show that confidence in the reliability of such criteria is misplaced. We also consider the fault-finding capabilities of three test suites created by the international community to serve to assure implementations of the Data Encryption Standard (a block cipher). We do this by means of mutation analysis. The results show that not all sets are mutation adequate but the test suites are generally highly effective. The block cipher implementations are also seen to be highly ‘testable’ (i.e. they do not mask faults). 3 Contents Abstract ............................................................................................................................ 3 Table of Tables ...............................................................................................................