Automated Specification-Based Testing of REST Apis
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Studying the Feasibility and Importance of Software Testing: an Analysis
Dr. S.S.Riaz Ahamed / Internatinal Journal of Engineering Science and Technology Vol.1(3), 2009, 119-128 STUDYING THE FEASIBILITY AND IMPORTANCE OF SOFTWARE TESTING: AN ANALYSIS Dr.S.S.Riaz Ahamed Principal, Sathak Institute of Technology, Ramanathapuram,India. Email:[email protected], [email protected] ABSTRACT Software testing is a critical element of software quality assurance and represents the ultimate review of specification, design and coding. Software testing is the process of testing the functionality and correctness of software by running it. Software testing is usually performed for one of two reasons: defect detection, and reliability estimation. The problem of applying software testing to defect detection is that software can only suggest the presence of flaws, not their absence (unless the testing is exhaustive). The problem of applying software testing to reliability estimation is that the input distribution used for selecting test cases may be flawed. The key to software testing is trying to find the modes of failure - something that requires exhaustively testing the code on all possible inputs. Software Testing, depending on the testing method employed, can be implemented at any time in the development process. Keywords: verification and validation (V & V) 1 INTRODUCTION Testing is a set of activities that could be planned ahead and conducted systematically. The main objective of testing is to find an error by executing a program. The objective of testing is to check whether the designed software meets the customer specification. The Testing should fulfill the following criteria: ¾ Test should begin at the module level and work “outward” toward the integration of the entire computer based system. -
Customer Success Story
Customer Success Story Interesting Dilemma, Critical Solution Lufthansa Cargo AG The purpose of Lufthansa Cargo AG’s SDB Lufthansa Cargo AG ordered the serves more than 500 destinations world- project was to provide consistent shipment development of SDB from Lufthansa data as an infrastructure for each phase of its Systems. However, functional and load wide with passenger and cargo aircraft shipping process. Consistent shipment data testing is performed at Lufthansa Cargo as well as trucking services. Lufthansa is is a prerequisite for Lufthansa Cargo AG to AG with a core team of six business one of the leaders in the international air efficiently and effectively plan and fulfill the analysts and technical architects, headed cargo industry, and prides itself on high transport of shipments. Without it, much is at by Project Manager, Michael Herrmann. stake. quality service. Herrmann determined that he had an In instances of irregularities caused by interesting dilemma: a need to develop inconsistent shipment data, they would central, stable, and optimal-performance experience additional costs due to extra services for different applications without handling efforts, additional work to correct affecting the various front ends that THE CHALLENGE accounting information, revenue loss, and were already in place or currently under poor feedback from customers. construction. Lufthansa owns and operates a fleet of 19 MD-11F aircrafts, and charters other freight- With such critical factors in mind, Lufthansa Functional testing needed to be performed Cargo AG determined that a well-tested API on services that were independent of any carrying planes. To continue its leadership was the best solution for its central shipment front ends, along with their related test in high quality air cargo services, Lufthansa database. -
Automated Web Application Testing Using Search Based Software Engineering
Automated Web Application Testing Using Search Based Software Engineering Nadia Alshahwan and Mark Harman CREST Centre University College London London, UK fnadia.alshahwan.10,[email protected] Abstract—This paper introduces three related algorithms and [21]. However, of 399 research papers on SBST,1 only one a tool, SWAT, for automated web application testing using Search [20] mentions web application testing issues and none applies Based Software Testing (SBST). The algorithms significantly search based test data generation to automate web application enhance the efficiency and effectiveness of traditional search based techniques exploiting both static and dynamic analysis. The testing. combined approach yields a 54% increase in branch coverage and Popular web development languages such as PHP and a 30% reduction in test effort. Each improvement is separately Python have characteristics that pose a challenge when ap- evaluated in an empirical study on 6 real world web applications. plying search based techniques such as dynamic typing and identifying the input vector. Moreover, the unique and rich Index Terms—SBSE; Automated Test data generation; Web nature of a web application’s output can be exploited to aid applications the test generation process and potentially improve effective- ness and efficiency. This was the motivation for our work: We seek to develop a search based approach to automated I. INTRODUCTION web application testing that overcomes challenges and takes advantage of opportunities that web applications offer. The importance of automated web application testing de- rives from the increasing reliance on these systems for busi- In this paper we introduce an automated search based ness, social, organizational and governmental functions. -
Web Gui Testing Checklist
Web Gui Testing Checklist Wes recrystallizing her quinone congruously, phytophagous and sulphonic. How imponderable is Schroeder when barbate whileand soft-footed Brewer gliff Zachery some incisure yakety-yak affluently. some chatoyancy? Fulgurating and battiest Nealson blossoms her amontillados refine Wbox aims to the field to be able to the automated support data, testing web gui checklist Planned testing techniques, including scripted testing, exploratory testing, and user experience testing. This gui content will the css or dynamic values? Test all input fields for special characters. For instance, create test data assist the maximum and minimum values in those data field. Assisted by timing testing is not tested to the order to achieve true black art relying on gui testing web checklist will best. The web hosting environments you start all web testing gui checklist can provide tests has had made. The gui testing procedures are the weak factors causing delays in agile here offering, gui testing web? At anytime without giving us a testing web gui checklist can also has on. How gui testing checklist for a gui testing web checklist to induce further eliminating redundant if there is transmitted without the below to use of jobs with. Monkey testing tool that an application or even perform testing web gui changes some test android scripts behind successful only allows an. Discusses the preceding css or if a sql injections through an application penetration testing on gui testing web? How much regression testing is enough? Fully automated attack simulations and highly automated fuzzing tests are appropriate here, and testers might also use domain testing to pursue intuitions. -
Leading Practice: Test Strategy and Approach in Agile Projects
CA SERVICES | LEADING PRACTICE Leading Practice: Test Strategy and Approach in Agile Projects Abstract This document provides best practices on how to strategize testing CA Project and Portfolio Management (CA PPM) in an agile project. The document does not include specific test cases; the list of test cases and steps for each test case are provided in a separate document. This document should be used by the agile project team that is planning the testing activities, and by end users who perform user acceptance testing (UAT). Concepts Concept Description Test Approach Defines testing strategy, roles and responsibilities of various team members, and test types. Testing Environments Outlines which testing is carried out in which environment. Testing Automation and Tools Addresses test management and automation tools required for test execution. Risk Analysis Defines the approach for risk identification and plans to mitigate risks as well as a contingency plan. Test Planning and Execution Defines the approach to plan the test cases, test scripts, and execution. Review and Approval Lists individuals who should review, approve and sign off on test results. Test Approach The test approach defines testing strategy, roles and responsibilities of various team members, and the test types. The first step is to define the testing strategy. It should describe how and when the testing will be conducted, who will do the testing, the type of testing being conducted, features being tested, environment(s) where the testing takes place, what testing tools are used, and how are defects tracked and managed. The testing strategy should be prepared by the agile core team. -
Functional Testing Functional Testing
From Pressman, “Software Engineering – a practitionerʼs approach”, Chapter 14 and Pezze + Young, “Software Testing and Analysis”, Chapters 10-11 Today, weʼll talk about testing – how to test software. The question is: How do we design tests? And weʼll start with Functional Testing functional testing. Software Engineering Andreas Zeller • Saarland University 1 Functional testing is also called “black- box” testing, because we see the program as a black box – that is, we ignore how it is being written 2 in contrast to structural or “white-box” testing, where the program is the base. 3 If the program is not the base, then what is? Simple: itʼs the specification. 4 If the program is not the base, then what is? Simple: itʼs the specification. Testing Tactics Functional Structural “black box” “white box” • Tests based on spec • Tests based on code • Test covers as much • Test covers as much specified behavior implemented behavior as possible as possible 5 Why Functional? Functional Structural “black box” “white box” • Program code not necessary • Early functional test design has benefits reveals spec problems • assesses testability • gives additional explanation of spec • may even serve as spec, as in XP 6 Structural testing can not detect that some required feature is missing in the code Why Functional? Functional testing applies at all granularity levels (in contrast to structural testing, which only applies to Functional Structural unit and integration testing) “black box” “white box” • Best for missing logic defects Common problem: Some program logic was simply forgotten Structural testing would not focus on code that is not there • Applies at all granularity levels unit tests • integration tests • system tests • regression tests 7 2,510,588,971 years, 32 days, and 20 hours to be precise. -
HP Functional Testing Software Data Sheet
HP Functional Testing software Data sheet With HP Functional Testing you can automate functional and regression testing for every modern software application and environment, extend testing to a wider range of teams, and accelerate the testing process—so you can improve application quality and still make your market window. Simplifies test creation and HP Functional Testing makes it easy to insert, modify, data-drive, and remove test steps. It features: maintenance • Keyword capabilities: Using keywords, testers HP Functional Testing is advanced, automated can build test cases by capturing flows directly testing software for building functional and regression from the application screens and applying robust test suites. It captures, verifies, and replays user record/replay capturing technology. interactions automatically and helps testers quickly • Automatic updating: With new application builds, identify and report on application effects, while you only need to update one reference in the shared providing sophisticated functionality for tester repository and the update is propagated to all collaboration. The product includes HP QuickTest referencing tests. Professional and all of its add-ins. It is sold stand-alone or as part of the broader HP Unified • Easy data-driving: You can quickly data-drive any Functional Testing solution, which couples object definition, method, checkpoint, and output HP Functional Testing with HP Service Test to value through the integrated data table. address both GUI and non-GUI testing. • Timely advice: In -
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 -
A Systematic Review on Regression Testing for Web-Based Applications
Journal of Software A Systematic Review on Regression Testing for Web-Based Applications Anis Zarrad* Department of Computer Science and Information Systems, Prince Sultan University, Riyadh, Saudi Arabia. * Corresponding author. Tel.: +966114948531; email: [email protected] Manuscript submitted December 12, 2014; accepted April 16, 2015. doi: 10.17706/jsw.10.8.971-990 Abstract: Web-based applications and their underlying parts are growing rapidly to offer services over the internet around the world. Web applications play critical roles in various areas such as community development, business, academic, sciences etc. Therefore their correctness and reliability become important factors with each succeeding release. Regression testing is an important means to ensure such factors for every new released version. Regression testing is a verification process to discover the impact of changes in other interconnected modules. With the goal of selecting an appropriate regression testing approach to respond adequately to any changes in Web applications, we conduct a complete systematic study of regression testing techniques in Web applications. Out of 64, we identified a total of 22 papers reporting experiments and case studies. We present a qualitative analysis for used tools, an overview of test case section techniques and empirical study evaluation for every selected work. No approaches were found clearly superior to other since results depend on many varying factors and the deployment environments. We identified the need of evidences where approaches are evaluated cost effective rather than technical description. Key words: Regressing testing, web-based application testing, empirical study, test set, software testing. 1. Introduction In today’s scenario, as the world became global and with the advent of internet technologies, Web-based applications become more effective manner for enterprises, and academic entities to produce business strategies and policies. -
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. -
Continuous Quality and Testing to Accelerate Application Development
Continuous Quality and Testing to Accelerate Application Development How to assess your current testing maturity level and practice continuous testing for DevOps Continuous Quality and Testing to Accelerate Application Development // 1 Table of Contents 03 Introduction 04 Why Is Continuous Quality and Testing Maturity Important to DevOps? 05 Continuous Testing Engineers Quality into DevOps 07 Best Practices for Well- Engineered Continuous Testing 08 Continuous Testing Maturity Levels Level 1: Chaos Level 2: Continuous Integration Level 3: Continuous Flow Level 4: Continuous Feedback Level 5: Continuous Improvement 12 Continuous Testing Maturity Assessment 13 How to Get Started with DevOps Testing? 14 Continuous Testing in the Cloud Choosing the right tools for Continuous Testing On-demand Development and Testing Environments with Infrastructure as Code The Right Tests at the Right Time 20 Get Started 20 Conclusion 21 About AWS Marketplace and DevOps Institute 21 Contributors Introduction A successful DevOps implementation reduces the bottlenecks related to testing. These bottlenecks include finding and setting up test environments, test configurations, and test results implementation. These issues are not industry specific. They can be experienced in manufacturing, service businesses, and governments alike. They can be reduced by having a thorough understanding and a disciplined, mature implementation of Continuous Testing and related recommended engineering practices. The best place to start addressing these challenges is having a good understanding of what Continuous Testing is. Marc Hornbeek, the author of Engineering DevOps, describes it as: “A quality assessment strategy in which most tests are automated and integrated as a core and essential part of DevOps. Continuous Testing is much more than simply ‘automating tests.’” In this whitepaper, we’ll address the best practices you can adopt for implementing Continuous Quality and Testing on the AWS Cloud environment in the context of the DevOps model. -
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.