What Is Selenium Webdriver? Why Is It Used? Selenium Webdriver Is a Web Framework That Permits You to Execute Cross-Browser Tests

Total Page:16

File Type:pdf, Size:1020Kb

What Is Selenium Webdriver? Why Is It Used? Selenium Webdriver Is a Web Framework That Permits You to Execute Cross-Browser Tests DEPARTMENT OF INFORMATION SCIENCE AND ENGINEERING Study Material for Academic Year 2020-21 (Odd Semester) COURSE NAME : SOFTWARE TESTING AND AUTOMATION COURSE CODE : ISE72 SEMESTER : V111 DepartmentofISE NHCE UNIT-5: Testing Tools: Features of Testing Tools – Guidelines for Selecting Tools – StaticTesting Tools – Dynamic Testing Tools – Advantages and Disadvantages of Testing Tools – When to use Test Tools? Junit, selenium, AutomationScripts practice. Testing Tools: Tools from a software testing context can be defined as a product that supports one or more test activities right from planning, requirements, creating a build, test execution, defect logging and test analysis. Classification of Tools Tools can be classified based on several parameters. They include: The purpose of the tool The Activities that are supported within the tool The Type/level of testing it supports The Kind of licensing (open source, freeware, commercial) The technology used Types ofTools: S.No. Tool Type Used for Used by 1. Test Management Tool Test Managing, scheduling, defect testers logging, tracking and analysis. 2. Configuration For Implementation, execution, All Team management tool tracking changes members 3. Static Analysis Tools Static Testing Developers 4. Test data Preparation Analysis and Design, Test data Testers Tools generation 5. Test Execution Tools Implementation, Execution Testers 6. Test Comparators Comparing expected and actual results All Team members 7. Coverage measurement Provides structural coverage Developers tools 8. Performance Testing Monitoring the performance, response Testers tools time 9. Project planning and For Planning Project Tracking Tools Managers 10. Incident Management For managing the tests Testers Tools Tools Implementation - process Analyse the problem carefully to identify strengths, weaknesses and opportunities The Constraints such as budgets, time and other requirements are noted. Evaluating the options and Short listing the ones that are meets the requirement Developing the Proof of Concept which captures the pros and cons Create a Pilot Project using the selected tool within a specified team Rolling out the tool phase wise across the organization Junit: JUnit is a Regression Testing Framework used by developers to implement unit testing in Java, and accelerate programming speed and increase the quality of code. JUnit Framework can be easily integrated with either of the following − Eclipse Ant Maven Features of JUnit Test Framework JUnit test framework provides the following important features − Fixtures Test suites Test runners JUnit classes Fixtures Fixtures is a fixed state of a set of objects used as a baseline for running tests. The purpose of a test fixture is to ensure that there is a well-known and fixed environment in which tests are run so that results are repeatable. It includes − setUp() method, which runs before every test invocation. tearDown() method, which runs after every test method. Let's check one example − import junit.framework.*; publicclassJavaTestextendsTestCase{ protectedint value1, value2; // assigning the values protectedvoid setUp(){ value1 =3; value2 =3; } // test method to add two values publicvoid testAdd(){ double result = value1 + value2; assertTrue(result ==6); } } Test Suites A test suite bundles a few unit test cases and runs them together. In JUnit, both @RunWith and @Suite annotation are used to run the suite test. Given below is an example that uses TestJunit1 & TestJunit2 test classes. import org.junit.runner.RunWith; import org.junit.runners.Suite; //JUnit Suite Test @RunWith(Suite.class) @Suite.SuiteClasses({ TestJunit1.class,TestJunit2.class }) publicclassJunitTestSuite{ } import org.junit.Test; import org.junit.Ignore; importstatic org.junit.Assert.assertEquals; publicclassTestJunit1{ String message ="Robert"; MessageUtil messageUtil =newMessageUtil(message); @Test publicvoid testPrintMessage(){ System.out.println("Inside testPrintMessage()"); assertEquals(message, messageUtil.printMessage()); } } import org.junit.Test; import org.junit.Ignore; importstatic org.junit.Assert.assertEquals; publicclassTestJunit2{ String message ="Robert"; MessageUtil messageUtil =newMessageUtil(message); @Test publicvoid testSalutationMessage(){ System.out.println("Inside testSalutationMessage()"); message ="Hi!"+"Robert"; assertEquals(message,messageUtil.salutationMessage()); } } Test Runners Test runner is used for executing the test cases. Here is an example that assumes the test class TestJunit already exists. import org.junit.runner.JUnitCore; import org.junit.runner.Result; import org.junit.runner.notification.Failure; publicclassTestRunner{ publicstaticvoid main(String[] args){ Result result =JUnitCore.runClasses(TestJunit.class); for(Failure failure : result.getFailures()){ System.out.println(failure.toString()); } System.out.println(result.wasSuccessful()); } } JUnit Classes JUnit classes are important classes, used in writing and testing JUnits. Some of the important classes are − Assert − Contains a set of assert methods. TestCase − Contains a test case that defines the fixture to run multiple tests. TestResult − Contains methods to collect the results of executing a test case. SELENIUM FRAMEWORK: Selenium automates browsers. Selenium has the support of some of the largest browser vendors who have taken (or are taking) steps to make Selenium a native part of their browser. It is also the core technology in countless other browser automation tools, APIs and frameworks. Selenium IDE is an integrated development environment for Selenium scripts. It is implemented as a Chrome and Firefox extension, and allows you to record, edit, and debug tests. Selenium IDE is not only a recording tool: it is a complete IDE. You can choose to use its recording capability, or you may edit your scripts by hand. With autocomplete support and the ability to move commands around quickly, Selenium IDE is the ideal environment for creating Selenium tests no matter what style of tests you prefer. Features: Easy record and playback Intelligent field selection will use IDs, names, or XPath as needed Autocomplete for all common Selenium commands Walk through tests Debug and set breakpoints All in one project file, containing all test cases and suites Selenium IDE has plugin support. Selenium WebDriver WebDriver is designed in a simpler and more concise programming interface along with addressing some limitations in the Selenium-RC API. WebDriver is a compact Object Oriented API when compared to Selenium1.0 It drives the browser much more effectively and overcomes the limitations of Selenium 1.x which affected our functional test coverage, like the file upload or download, pop-ups and dialogs barrier WebDriver overcomes the limitation of Selenium RC's Single Host origin policy WebDriver is the name of the key interface against which tests should be written in Java, the implementing classes one should use are listed as below: ChromeDriver, EventFiringWebDriver, FirefoxDriver, HtmlUnitDriver, InternetExplorerDriv er,PhantomJSDriver, RemoteWebDriver, SafariDriver Selenium WebDriver is one of the most important parts of the Selenium test-suite family, but before directly hopping on to Selenium WebDriver, we must have a basic idea about Selenium. What is Selenium? Selenium refers to a suite of tools that are widely used in the testing community when it comes to cross-browser testing. Selenium cannot automate desktop applications; it can only be used in browsers. It is considered to be one of the most preferred testing tool-suite for automating web applications as it provides support for popular web browsers which makes it very powerful. Browsers supported by Selenium: Google Chrome 12+ Internet Explorer 7,8,9,10 Safari 5.1+ Opera 11.5 Firefox 3+ Along with this, Selenium is also capable of working on multiple Operating Systems. Multiple Operating Systems supported by Selenium: Windows Mac Linux/Unix Another reason why Selenium is gaining popularity is that it provides compatibility with different programming languages which makes it very flexible for the testers to design test cases. Programming Languages supported by Selenium C# Java JavaScript Ruby PythonPHP Note: It is not mandatory to write your Selenium code in the same language as the application. For example, if the application under test is written in PHP, then you don’t have write your Selenium code in PHP. Thus, if a website is written in C#, the Selenium code can be written in PHP too. Selenium Components The Selenium test suite comprises of four main components:- Selenium IDE Selenium RC Selenium Webdriver Selenium Grid Selenium IDE (Integrated Development Environment) is primarily a record/run tool. It is an Add-on or an extension available for both Firefox and Chrome that generates tests quickly through its functionality of record and playback. You don’t need to learn any test scripting language for authoring any functional tests. In the case of working with Selenium RC (Remote Control), one must have good knowledge in at least one programming language. This tool allows you to develop responsive design tests in any scripting language of your choice. Server and client libraries are the two main components of Selenium RC. Its architecture is complex and it has its limitations. Selenium WebDriver is an enhanced version of Selenium RC. It was introduced in the market to overcome the limitation faced in Selenium RC. Though it is an advanced version of RC, its architecture is completely
Recommended publications
  • D1.1.1 Public State of the Art Document
    D1.1.1 Public state of the art document Programme ITEA3 Challenge Smart Engineering Project number 17038 Project name Visual diagnosis for DevOps software development Project duration 1st October 2018 – 30st June 2022 Project website Project WP WP1 - Pre-studies and requirements Project Task Task 1.1 – Update of state-of-art and state-of-the practice analysis for visualization in software projects in DevOps context Deliverable type X Doc Textual deliverable SW Software deliverable Version V17 Delivered 18/11/2019 Access x Public Abstracts are public Confidential D1.1.1 Public state of the art document Document Contributors Partber Author Role EXPERIS Ester Sancho editor EXPERIS Miriam Moreno writer GRO Paris Avgeriou writer INVENCO Mika Koivuluoma writer OCE Lou Somers writer/reviewer OULU Markus Kelanti writer TAU Kari Systä writer/reviewer TAU Outi Sievi-Korte writer/reviewer TIOBE Paul Jansen writer TIOBE Marvin Wener writer UPC Lidia López writer UPC Xavier Franch writer VINCIT Veli-Pekka Eloranta writer Document History Date Version Editors Status 18/06/2019 ToC EXPERIS Table of Content 10/07/2019 V01 TAU Draft 30/09/2019 V02 OCE/GRO Draft 17/10/2019 V06 TIOBE Draft 22/10/2019 V08 OULU Draft 12/11/2019 V09 VINCIT 1ST Final Draft 20/11/2019 V10 OCE Reviewed version 26/11/2019 V12 UPC/EXPERIS/TAU 2nd Final Draft 10/12/2019 V16 EXPERIS Final Version 16/12/2019 V16.01 TAU Peer Review 18/12/2019 V17 EXPERIS Submission 2 D1.1.1 Public state of the art document Table of Contents Executive Summary ............................................................................................................................. 6 1.
    [Show full text]
  • Information Needs for Software Development Analytics
    Information Needs for Software Development Analytics Raymond P.L. Buse Thomas Zimmermann The University of Virginia, USA Microsoft Research [email protected] [email protected] Abstract—Software development is a data rich activity with decision making will likely only become more difficult. many sophisticated metrics. Yet engineers often lack the tools Analytics describes application of analysis, data, and sys- and techniques necessary to leverage these potentially powerful tematic reasoning to make decisions. Analytics is especially information resources toward decision making. In this paper, we present the data and analysis needs of professional software useful for helping users move from only answering questions engineers, which we identified among 110 developers and of information like “What happened?” to also answering managers in a survey. We asked about their decision making questions of insight like “How did it happen and why?” process, their needs for artifacts and indicators, and scenarios Instead of just considering data or metrics directly, one can in which they would use analytics. gather more complete insights by layering different kinds of The survey responses lead us to propose several guidelines for analytics tools in software development including: Engi- analyses that allow for summarizing, filtering, modeling, and neers do not necessarily have much expertise in data analysis; experimenting; typically with the help of automated tools. thus tools should be easy to use, fast, and produce concise The key to applying analytics to a new domain is under- output. Engineers have diverse analysis needs and consider most standing the link between available data and the information indicators to be important; thus tools should at the same time needed to make good decisions, as well as the analyses support many different types of artifacts and many indicators.
    [Show full text]
  • Software Analytics for Incident Management of Online Services: An
    Software Analytics for Incident Management of Online Services: An Experience Report Jian-Guang Lou, Qingwei Lin, Rui Ding, Tao Xie Qiang Fu, Dongmei Zhang University of Illinois at Urbana-Champaign Microsoft Research Asia, Beijing, P. R. China Urbana, IL, USA {jlou, qlin, juding, qifu, dongmeiz}@microsoft.com [email protected] Abstract—As online services become more and more popular, incident management needs to be efficient and effective in incident management has become a critical task that aims to order to ensure high availability and reliability of the services. minimize the service downtime and to ensure high quality of the A typical procedure of incident management in practice provided services. In practice, incident management is conducted (e.g., at Microsoft and other service-provider companies) goes through analyzing a huge amount of monitoring data collected at as follow. When the service monitoring system detects a ser- runtime of a service. Such data-driven incident management faces several significant challenges such as the large data scale, vice violation, the system automatically sends out an alert and complex problem space, and incomplete knowledge. To address makes a phone call to a set of On-Call Engineers (OCEs) to these challenges, we carried out two-year software-analytics trigger the investigation on the incident in order to restore the research where we designed a set of novel data-driven techniques service as soon as possible. Given an incident, OCEs need to and developed an industrial system called the Service Analysis understand what the problem is and how to resolve it. In ideal Studio (SAS) targeting real scenarios in a large-scale online cases, OCEs can identify the root cause of the incident and fix service of Microsoft.
    [Show full text]
  • Patterns for Implementing Software Analytics in Development Teams
    Patterns for Implementing Software Analytics in Development Teams JOELMA CHOMA, National Institute for Space Research - INPE EDUARDO MARTINS GUERRA, National Institute for Space Research - INPE TIAGO SILVA DA SILVA, Federal University of São Paulo - UNIFESP The software development activities typically produce a large amount of data. Using a data-driven approach to decision making – such as Software Analytics – the software practitioners can achieve higher development process productivity and improve many aspects of the software quality based on the insightful and actionable information. This paper presents a set of patterns describing steps to encourage the integration of the analytics activities by development teams in order to support them to make better decisions, promoting the continuous improvement of software and its development process. Before any procedure to extract data for software analytics, the team needs to define, first of all, their questions about what will need to be measured, assess and monitored throughout the development process. Once defined the key issues which will be tracked, the team may select the most appropriate means for extracting data from software artifacts that will be useful in decision-making. The tasks to set up the development environment for software analytics should be added to the project planning along with the regular tasks. The software analytics activities should be distributed throughout the project in order to add information about the system in small portions. By defining reachable goals from the software analytics findings, the team turns insights from software analytics into actions to improve incrementally the software characteristics and/or its development process. Categories and Subject Descriptors: D.2.8 [Software and its engineering]: Software creation and management—Metrics General Terms: Software Analytics Additional Key Words and Phrases: Software Analytics, Decision Making, Agile Software Development, Patterns, Software Measurement, Development Teams.
    [Show full text]
  • Linkedin Learning Digital Framework
    Competency Courses Duration Level Course Objective Use ICT-based devices, applications, software and Learn what it takes to break through the clutter and sell in the telecommunications market. In this course, Meridith Elliott Powell helps sales professionals services understand and master the unique challenges and skills required to sell into this ever-changing industry. Meridith acquaints you with the trends and Selling into Industries: Telecommunications 00:33.0 Intermediate changes—including network security and over-the-top (OTT) services—that are currently shaping this industry, as well as what telecommunications clients Use basic productivity software, use email and expect from sales reps. Learn how to use a consultative selling approach to gain a deeper understanding of client needs, create urgency by recognizing and other digital communication solving those needs, and continue to expand your sales relationship after the deal is signed. The Systems Security Certified Practitioner (SSCP) certification is an excellent entry point to a career in IT security. To help you prepare for the SSCP exam, Use digital capture devices such as a camera instructor Mike Chapple has designed a series of courses covering each domain. In this installment, Mike covers the objectives of Networks and SSCP Cert Prep: 6 Networks and Communications Security, Domain 6, which comprises 16% of the questions on the exam. Topics include TCP/IP networking, configuring network security 10:09.0 Intermediate Use subject-specialist ICT devices and Communications Security devices, and identifying the different types of network attacks. Plus, learn how to secure your network with firewall rules, switch and router configuration, and applications confidently network monitoring; protect your telecommunications; and understand the unique features and vulnerabilities of wireless networks.
    [Show full text]
  • Evaluating and Improving Software Quality Using Text Analysis Techniques - a Mapping Study
    Evaluating and Improving Software Quality Using Text Analysis Techniques - A Mapping Study Faiz Shah, Dietmar Pfahl Institute of Computer Science, University of Tartu J. Liivi 2, Tartu 50490, Estonia {shah, dietmar.pfahl}@ut.ee Abstract: Improvement and evaluation of software quality is a recurring and crucial activ- ity in the software development life-cycle. During software development, soft- ware artifacts such as requirement documents, comments in source code, design documents, and change requests are created containing natural language text. For analyzing natural text, specialized text analysis techniques are available. However, a consolidated body of knowledge about research using text analysis techniques to improve and evaluate software quality still needs to be estab- lished. To contribute to the establishment of such a body of knowledge, we aimed at extracting relevant information from the scientific literature about data sources, research contributions, and the usage of text analysis techniques for the im- provement and evaluation of software quality. We conducted a mapping study by performing the following steps: define re- search questions, prepare search string and find relevant literature, apply screening process, classify, and extract data. Bug classification and bug severity assignment activities within defect manage- ment are frequently improved using the text analysis techniques of classifica- tion and concept extraction. Non-functional requirements elicitation activity of requirements engineering is mostly improved using the technique of concept extraction. The quality characteristic which is frequently evaluated for the prod- uct quality model is operability. The most commonly used data sources are: bug report, requirement documents, and software reviews. The dominant type of re- search contributions are solution proposals and validation research.
    [Show full text]
  • Using Already Existing Data to Answer Questions Asked During Software Change
    Using Already Existing Data to Answer Questions Asked During Software Change Daniel Jigin Oscar Gunnesson [email protected] [email protected] June 14, 2018 Master’s thesis work carried out at Praqma, Malmö. Supervisors: Lars Bendix, [email protected] Christian Pendleton, [email protected] Examiner: Boris Magnusson, [email protected] Abstract The software development business is always adapting new technologies while trying to keep up with the market and the importance of having the best-suited tools, people and processes is clear. There is a need to understand what needs there might be, so that the configuration managers can supply developers with the correct support to increase the development efficiency. Studies of how de- velopers spend their time have shown that they spend as much time searching for whom to contact in the organization to get answers to their questions, as they do getting the job done. In traditional software development, configuration managers used to bring a status report about the software to the managers. We have suggested a more modern approach, fit for an agile methodology, where the status of the software is available for any worker at any time. When asking developers how they find answers they say that it is based on gut feeling coming from previous experiences. Providing data will lead to discussions about decisions being data based rather than gut feeling based . We have investigated CodeScene, a tool that utilizes the version control system GIT to analyze which components that have been committed together and analyzing how it can be utilized when performing an impact analysis and how it can provide the technical debt for a software project.
    [Show full text]
  • Enterprise Edition
    Enterprise Edition 1.6.1 February 9, 2017 Contents 1 Getting Started 3 1.1 Configure Your Environment . .3 1.1.1 Install the Supporting Tools . .3 1.1.2 Setup an SSH Key for Git . .3 1.2 Installation . .3 1.2.1 Run CodeScene from the Command Line . .4 1.2.2 Install CodeScene on a Server . .4 1.2.3 Configure additional users . .5 1.3 Run an Analysis . .5 1.3.1 Creating a New Project . .5 1.3.2 Force an Analysis . .8 1.3.3 Run a Retrospective . .8 1.3.4 Find your Way Around . .8 1.4 Ensure you use a Mailmap . 10 1.5 Use a Reverse Proxy for HTTPS Support . 10 1.6 Display A Monitor Dashboard . 10 1.6.1 View the Monitor Dashboard . 10 2 Guides 12 2.1 Technical . 12 2.1.1 Hotspots . 12 2.1.2 Temporal Coupling . 16 2.1.3 Complexity Trends . 21 2.1.4 X-Ray . 26 2.1.5 Code Churn . 33 2.1.6 Code Age . 36 2.2 Architectural . 40 2.2.1 Architectural Analyses . 40 2.3 Social . 45 2.3.1 Social Networks . 45 2.3.2 Knowledge Distribution . 48 2.3.3 Parallel Development and Code Fragmentation . 50 2.3.4 Modus Operandi . 51 2.3.5 Know the possible Biases in the Data . 53 2.4 Project Management . 54 2.4.1 Project Management Analyses . 54 2.4.2 Risk Analysis . 58 3 Configuration 61 3.1 Project Configuration . 61 3.1.1 Specify the Git Repository to Analyze .
    [Show full text]
  • Measuring Architectural Degeneration – in Systems Written in the Interpreted Dynamically Typed Multi- Paradigm Language Python
    Linköping University | Department of Computer and Information Science Master thesis, 30 ECTS | Datateknik 2019 | LIU-IDA/LITH-EX-A--19/059--SE Measuring Architectural Degeneration – In Systems Written in the Interpreted Dynamically Typed Multi- Paradigm Language Python Anton Mo Eriksson & Hampus Dunström Supervisor : Anders Fröberg Examiner : Erik Berglund Linköpings universitet SE–581 83 Linköping +46 13 28 10 00 , www.liu.se Upphovsrätt Detta dokument hålls tillgängligt på Internet - eller dess framtida ersättare - under 25 år från publicer- ingsdatum under förutsättning att inga extraordinära omständigheter uppstår. Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner, skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat för ickekommersiell forskning och för undervisning. Över- föring av upphovsrätten vid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning av dokumentet kräver upphovsmannens medgivande. För att garantera äktheten, säkerheten och till- gängligheten finns lösningar av teknisk och administrativ art. Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman i den omfattning som god sed kräver vid användning av dokumentet på ovan beskrivna sätt samt skydd mot att dokumentet än- dras eller presenteras i sådan form eller i sådant sammanhang som är kränkande för upphovsmannens litterära eller konstnärliga anseende eller egenart. För ytterligare information om Linköping University Electronic Press se förlagets hemsida http://www.ep.liu.se/. Copyright The publishers will keep this document online on the Internet - or its possible replacement - for a period of 25 years starting from the date of publication barring exceptional circumstances. The online availability of the document implies permanent permission for anyone to read, to down- load, or to print out single copies for his/hers own use and to use it unchanged for non-commercial research and educational purpose.
    [Show full text]
  • Insights Into the Technology and Trends Shaping the Future
    TECHNOLOGY RADAR VOL.16 Insights into the technology and trends shaping the future thoughtworks.com/radar #TWTechRadar CONTRIBUTORS The Technology Radar is prepared by the ThoughtWorks Technology Advisory Board, comprised of: Rebecca Parsons (CTO) | Martin Fowler (Chief Scientist) | Badri Janakiraman | Bharani Subramaniam | Camilla Crispim Erik Doernenburg | Evan Bottcher | Fausto de la Torre | Hao Xu | Ian Cartwright James Lewis | Jonny LeRoy | Marco Valtas | Mike Mason | Neal Ford Rachel Laycock | Scott Shaw | Srihari Srinivasan | Zhamak Dehghani WHAT’S NEW? Highlighted themes in this edition: CONVERSATIONAL UI AND platforms. It appears that the “cloud wars” have NATURAL LANGUAGE PROCESSING moved from competing on storage and compute to cognitive capabilities, as witnessed by the willingness watch the video (thght.works/ConUI) to open-source previously differentiating tools such as Kubernetes and Mesos. Conversation—a new way to interact with applications— took the ecosystem by storm with tools such as Siri, All the big players have offerings in this space, along Cortana, and Allo, and then extended into homes with with interesting niche players worth assessing. Although devices such as Amazon Echo and Google Home. we still have reservations about the ethical and privacy implications of these services, we see great promise Building conversational and natural language user in utilizing these powerful tools in novel ways. Our interfaces, while presenting new challenges, has obvious clients are already investigating what new horizons they benefits. The team behind the Echo intentionally may expose by combining commodity cognition with omitted a screen, forcing them to rethink many human- intelligence about their own businesses. machine interactions. DEVELOPER EXPERIENCE AS THE The conversational trend is not just limited to voice; NEW DIFFERENTIATOR as messaging apps have grown to dominate both watch the video (thght.works/DevExp) phones and workplaces, we see conversations with other humans being supplemented by intelligent chatbots.
    [Show full text]
  • Software Analytics in Practice
    FOCUS: THE MANY FACES OF SOftWARE ANALYTICS • software practitioners could Software conduct software analytics by themselves, • researchers from academia or in- dustry could collaborate with soft- Analytics ware practitioners from software companies or open source commu- nities and transfer their analytics in Practice technologies to real-world use, or • practitioners could organically adopt analytics technologies devel- Dongmei Zhang, Shi Han, Yingnong Dang, Jian-Guang Lou, oped by researchers. and Haidong Zhang, Microsoft Research Asia However, no matter how this is pur- Tao Xie, University of Illinois at Urbana-Champaign sued, it remains a huge challenge. We’ve worked on a number of soft- ware analytics projects that have had a // The StackMine project produced a software analytics high impact on software development 7–10 system for Microsoft product teams. The project provided practice. To illustrate the lessons we’ve learned from them, we describe several lessons on applying software analytics technologies our experiences developing StackMine, to make an impact on software development practice. // a scalable system for postmortem per- formance debugging.7 The Promise and Challenges of Software Analytics As we mentioned before, software an- alytics aims to obtain insightful and actionable information. Insightful in- formation conveys knowledge that’s meaningful and useful for practitioners THE SOFTWARE DEVELOPMENT software domain, we formed Micro- performing a specific task. Actionable process produces various types of data soft Research Asia’s Software Analyt- information is information with which such as source code, bug reports, check- ics Group (http://research.microsoft. practitioners can devise concrete ways in histories, and test cases. Over the past com/groups/sa) in 2009.
    [Show full text]
  • Software Analytics to Software Practice: a Systematic Literature Review
    2015 IEEE/ACM 1st International Workshop on Big Data Software Engineering Software Analytics to Software Practice: A Systematic Literature Review Tamer Mohamed Abdellatif, Luiz Fernando Capretz, and Danny Ho Department of Electrical & Computer Engineering Western University London, Ontario, Canada [email protected], [email protected], [email protected] Abstract—Software Analytics (SA) is a new branch of big data suitable and supportive insights and facts to software industry analytics that has recently emerged (2011). What distinguishes stakeholders to make their decision making easier, faster, more SA from direct software analysis is that it links data mined from precise, and more confident. The main difference between SA many different software artifacts to obtain valuable insights. and direct software analysis is that rather than just providing These insights are useful for the decision-making process straightforward insights extraction SA performs additional throughout the different phases of the software lifecycle. Since SA is currently a hot and promising topic, we have conducted a advanced steps. As clarified by Hassan [1], SA must provide systematic literature review, presented in this paper, to identify visualization and useful interpretation of insights in order to gaps in knowledge and open research areas in SA. Because many facilitate decision making. researchers are still confused about the true potential of SA, we This paper is organized as follows: In Section II, we will had to filter out available research papers to obtain the most SA- illustrate our review methodology. Our review results are relevant work for our review. This filtration yielded 19 studies illustrated in Section III. Section IV presents the limitation of out of 135.
    [Show full text]