Comparative Study on Software Testing Strategies Common Errors Andbug Report 1J.Punitha, 2S.Nivetha,3Dr.M.Inbavalli
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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. -
FUNDAMENTALS of COMPUTING (2019-20) COURSE CODE: 5023 502800CH (Grade 7 for ½ High School Credit) 502900CH (Grade 8 for ½ High School Credit)
EXPLORING COMPUTER SCIENCE NEW NAME: FUNDAMENTALS OF COMPUTING (2019-20) COURSE CODE: 5023 502800CH (grade 7 for ½ high school credit) 502900CH (grade 8 for ½ high school credit) COURSE DESCRIPTION: Fundamentals of Computing is designed to introduce students to the field of computer science through an exploration of engaging and accessible topics. Through creativity and innovation, students will use critical thinking and problem solving skills to implement projects that are relevant to students’ lives. They will create a variety of computing artifacts while collaborating in teams. Students will gain a fundamental understanding of the history and operation of computers, programming, and web design. Students will also be introduced to computing careers and will examine societal and ethical issues of computing. OBJECTIVE: Given the necessary equipment, software, supplies, and facilities, the student will be able to successfully complete the following core standards for courses that grant one unit of credit. RECOMMENDED GRADE LEVELS: 9-12 (Preference 9-10) COURSE CREDIT: 1 unit (120 hours) COMPUTER REQUIREMENTS: One computer per student with Internet access RESOURCES: See attached Resource List A. SAFETY Effective professionals know the academic subject matter, including safety as required for proficiency within their area. They will use this knowledge as needed in their role. The following accountability criteria are considered essential for students in any program of study. 1. Review school safety policies and procedures. 2. Review classroom safety rules and procedures. 3. Review safety procedures for using equipment in the classroom. 4. Identify major causes of work-related accidents in office environments. 5. Demonstrate safety skills in an office/work environment. -
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. -
Comparison of GUI Testing Tools for Android Applications
Comparison of GUI testing tools for Android applications University of Oulu Department of Information Processing Science Master’s Thesis Tomi Lämsä Date 22.5.2017 2 Abstract Test automation is an intriguing area of software engineering, especially in Android development. This is since Android applications must be able to run in many different permutations of operating system versions and hardware choices. Comparison of different tools for automated UI testing of Android applications is done in this thesis. In a literature review several different tools available and their popularity is researched and the structure of the most popular tools is looked at. The two tools identified to be the most popular are Appium and Espresso. In an empirical study the two tools along with Robotium, UiAutomator and Tau are compared against each other in test execution speed, maintainability of the test code, reliability of the test tools and in general issues. An empirical study was carried out by selecting three Android applications for which an identical suite of tests was developed with each tool. The test suites were then run and the execution speed and reliability was analysed based on these results. The test code written is also analysed for maintainability by calculating the lines of code and the number of method calls needed to handle asynchrony related to UI updates. The issues faced by the test developer with the different tools are also analysed. This thesis aims to help industry users of these kinds of applications in two ways. First, it could be used as a source on what tools are over all available for UI testing of Android applications. -
Florida Course Code Directory Computer Science Course Information 2019-2020
FLORIDA COURSE CODE DIRECTORY COMPUTER SCIENCE COURSE INFORMATION 2019-2020 Section 1007.2616, Florida Statutes, was amended by the Florida Legislature to include the definition of computer science and a requirement that computer science courses be identified in the Course Code Directory published on the Department of Education’s website. DEFINITION: The study of computers and algorithmic processes, including their principles, hardware and software designs, applications, and their impact on society, and includes computer coding and computer programming. SECONDARY COMPUTER SCIENCE COURSES Middle and high schools in each district, including combination schools in which any of grades 6-12 are taught, must provide an opportunity for students to enroll in a computer science course. If a school district does not offer an identified computer science course the district must provide students access to the course through the Florida Virtual School (FLVS) or through other means. COURSE NUMBER COURSE TITLE 0200000 M/J Computer Science Discoveries 0200010 M/J Computer Science Discoveries 1 0200020 M/J Computer Science Discoveries 2 0200305 Computer Science Discoveries 0200315 Computer Science Principles 0200320 AP Computer Science A 0200325 AP Computer Science A Innovation 0200335 AP Computer Science Principles 0200435 PRE-AICE Computer Studies IGCSE Level 0200480 AICE Computer Science 1 AS Level 0200485 AICE Computer Science 2 A Level 0200490 AICE Information Technology 1 AS Level 0200495 AICE Information Technology 2 A Level 0200800 IB Computer -
Software Testing
Software Testing PURPOSE OF TESTING CONTENTS I. Software Testing Background II. Software Error Case Studies 1. Disney Lion King 2. Intel Pentium Floating Point Division Bug 3. NASA Mars Polar Lander 4. Patriot Missile Defense System 5. Y2K Bug III. What is Bug? 1. Terms for Software Failure 2. Software Bug: A Formal Definition 3. Why do Bugs occur? and cost of bug. 4. What exactly does a Software Tester do? 5. What makes a good Software Tester? IV. Software Development Process 1. Product Components 2. What Effort Goes into a Software Product? 3. What parts make up a Software Product? 4. Software Project Staff V. Software Development Lifecycle Models 1. Big Bang Model 2. Code and Fix Model 3. Waterfall Model 4. Spiral Model VI. The Realities of Software Testing VII. Software Testing Terms and Definition 1. Precision and Accuracy 2. Verification and Validation 3. Quality Assurance and Quality Control Anuradha Bhatia Software Testing I. Software Testing Background 1. Software is a set of instructions to perform some task. 2. Software is used in many applications of the real world. 3. Some of the examples are Application software, such as word processors, firmware in an embedded system, middleware, which controls and co-ordinates distributed systems, system software such as operating systems, video games, and websites. 4. All of these applications need to run without any error and provide a quality service to the user of the application. 5. The software has to be tested for its accurate and correct working. Software Testing: Testing can be defined in simple words as “Performing Verification and Validation of the Software Product” for its correctness and accuracy of working. -
Magma: a Ground-Truth Fuzzing Benchmark
Magma: A Ground-Truth Fuzzing Benchmark Ahmad Hazimeh Mathias Payer EPFL EPFL ABSTRACT fuzzer is evaluated against a set of target programs. These target pro- High scalability and low running costs have made fuzz testing grams can be sourced from a benchmark suite—such as the Cyber the de-facto standard for discovering software bugs. Fuzzing tech- Grand Challenge [9], LAVA-M[12], the Juliet Test Suite [30], and niques are constantly being improved in a race to build the ultimate Google’s Fuzzer Test Suite [17], oss-fuzz [2], and FuzzBench [16]— bug-finding tool. However, while fuzzing excels at finding bugs, or from a set of real-world programs [34]. Performance metrics— comparing fuzzer performance is challenging due to the lack of including coverage profiles, crash counts, and bug counts—are then metrics and benchmarks. Crash count, the most common perfor- collected during the evaluation. Unfortunately, while such metrics mance metric, is inaccurate due to imperfections in de-duplication can provide insight into a fuzzer’s performance, they are often methods and heuristics. Moreover, the lack of a unified set of targets insufficient to compare different fuzzers. Moreover, the lackofa results in ad hoc evaluations that inhibit fair comparison. unified set of target programs makes for unfounded comparisons. We tackle these problems by developing Magma, a ground-truth Most fuzzer evaluations consider crash count a reasonable metric fuzzer evaluation framework enabling uniform evaluations and for assessing fuzzer performance. However, crash count is often comparison. By introducing real bugs into real software, Magma inflated [25], even after attempts at de-duplication (e.g., via coverage allows for a realistic evaluation of fuzzers against a broad set of profiles or stack hashes), highlighting the need for more accurate targets. -
Safety and Security Challenge
SAFETY AND SECURITY CHALLENGE TOP SUPERCOMPUTERS IN THE WORLD - FEATURING TWO of DOE’S!! Summary: The U.S. Department of Energy (DOE) plays a very special role in In fields where scientists deal with issues from disaster relief to the keeping you safe. DOE has two supercomputers in the top ten supercomputers in electric grid, simulations provide real-time situational awareness to the whole world. Titan is the name of the supercomputer at the Oak Ridge inform decisions. DOE supercomputers have helped the Federal National Laboratory (ORNL) in Oak Ridge, Tennessee. Sequoia is the name of Bureau of Investigation find criminals, and the Department of the supercomputer at Lawrence Livermore National Laboratory (LLNL) in Defense assess terrorist threats. Currently, ORNL is building a Livermore, California. How do supercomputers keep us safe and what makes computing infrastructure to help the Centers for Medicare and them in the Top Ten in the world? Medicaid Services combat fraud. An important focus lab-wide is managing the tsunamis of data generated by supercomputers and facilities like ORNL’s Spallation Neutron Source. In terms of national security, ORNL plays an important role in national and global security due to its expertise in advanced materials, nuclear science, supercomputing and other scientific specialties. Discovery and innovation in these areas are essential for protecting US citizens and advancing national and global security priorities. Titan Supercomputer at Oak Ridge National Laboratory Background: ORNL is using computing to tackle national challenges such as safe nuclear energy systems and running simulations for lower costs for vehicle Lawrence Livermore's Sequoia ranked No. -
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. -
Managing Defects in an Agile Environment
Managing Defects in an Agile environment Auteur Ron Eringa Managing Defects in an Agile environment Introduction Injecting passion, Agility Teams often struggle with answering the following and quality into your question: “How to manage our Defects in an organisation. Agile environment?”. They start using Scrum as a framework for developing their software and while implementing, they experience trouble on how to deal with the Defects they find/cause along the way. Scrum is a framework that does not explicitly tell you how to handle Defects. The strait forward answer is to treat your Defects as Product Backlog Items that should be added to the Product Backlog. When the priority is set high enough by the Product Owner, they will be picked up by the Development Team in the next Sprint. The application of this is a little bit more difficult and hence should be explained in more detail. RON ERINGA 1. What is a defect? AGILE COACH Wikipedia: “A software bug (or defect) is an error, flaw, After being graduated from the Fontys failure, or fault in a computer program or system that University in Eindhoven, I worked as a Software produces an incorrect or unexpected result, or causes Engineer/Designer for ten years. Although I it to behave in unintended ways. Most bugs arise have always enjoyed technics, helping people from mistakes and errors made by people in either a and organizations are my passion. Especially program’s source code or its design, or in frameworks to deliver better quality together. When people and operating systems used by such programs, and focus towards a common goal, interaction is a few are caused by compilers producing incorrect increasing and energy is released. -
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.