Developer Testing in the IDE: Patterns, Beliefs, and Behavior
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Practical Unit Testing for Embedded Systems Part 1 PARASOFT WHITE PAPER
Practical Unit Testing for Embedded Systems Part 1 PARASOFT WHITE PAPER Table of Contents Introduction 2 Basics of Unit Testing 2 Benefits 2 Critics 3 Practical Unit Testing in Embedded Development 3 The system under test 3 Importing uVision projects 4 Configure the C++test project for Unit Testing 6 Configure uVision project for Unit Testing 8 Configure results transmission 9 Deal with target limitations 10 Prepare test suite and first exemplary test case 12 Deploy it and collect results 12 Page 1 www.parasoft.com Introduction The idea of unit testing has been around for many years. "Test early, test often" is a mantra that concerns unit testing as well. However, in practice, not many software projects have the luxury of a decent and up-to-date unit test suite. This may change, especially for embedded systems, as the demand for delivering quality software continues to grow. International standards, like IEC-61508-3, ISO/DIS-26262, or DO-178B, demand module testing for a given functional safety level. Unit testing at the module level helps to achieve this requirement. Yet, even if functional safety is not a concern, the cost of a recall—both in terms of direct expenses and in lost credibility—justifies spending a little more time and effort to ensure that our released software does not cause any unpleasant surprises. In this article, we will show how to prepare, maintain, and benefit from setting up unit tests for a simplified simulated ASR module. We will use a Keil evaluation board MCBSTM32E with Cortex-M3 MCU, MDK-ARM with the new ULINK Pro debug and trace adapter, and Parasoft C++test Unit Testing Framework. -
Parallel, Cross-Platform Unit Testing for Real-Time Embedded Systems
University of Denver Digital Commons @ DU Electronic Theses and Dissertations Graduate Studies 1-1-2017 Parallel, Cross-Platform Unit Testing for Real-Time Embedded Systems Tosapon Pankumhang University of Denver Follow this and additional works at: https://digitalcommons.du.edu/etd Part of the Computer Sciences Commons Recommended Citation Pankumhang, Tosapon, "Parallel, Cross-Platform Unit Testing for Real-Time Embedded Systems" (2017). Electronic Theses and Dissertations. 1353. https://digitalcommons.du.edu/etd/1353 This Dissertation is brought to you for free and open access by the Graduate Studies at Digital Commons @ DU. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Digital Commons @ DU. For more information, please contact [email protected],[email protected]. PARALLEL, CROSS-PLATFORM UNIT TESTING FOR REAL-TIME EMBEDDED SYSTEMS __________ A Dissertation Presented to the Faculty of the Daniel Felix Ritchie School of Engineering and Computer Science University of Denver __________ In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy __________ by Tosapon Pankumhang August 2017 Advisor: Matthew J. Rutherford ©Copyright by Tosapon Pankumhang 2017 All Rights Reserved Author: Tosapon Pankumhang Title: PARALLEL, CROSS-PLATFORM UNIT TESTING FOR REAL-TIME EMBEDDED SYSTEMS Advisor: Matthew J. Rutherford Degree Date: August 2017 ABSTRACT Embedded systems are used in a wide variety of applications (e.g., automotive, agricultural, home security, industrial, medical, military, and aerospace) due to their small size, low-energy consumption, and the ability to control real-time peripheral devices precisely. These systems, however, are different from each other in many aspects: processors, memory size, develop applications/OS, hardware interfaces, and software loading methods. -
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. -
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. -
Unit Testing Is a Level of Software Testing Where Individual Units/ Components of a Software Are Tested. the Purpose Is to Valid
Unit Testing is a level of software testing where individual units/ components of a software are tested. The purpose is to validate that each unit of the software performs as designed. A unit is the smallest testable part of software. It usually has one or a few inputs and usually a single output. In procedural programming a unit may be an individual program, function, procedure, etc. In object-oriented programming, the smallest unit is a method, which may belong to a base/ super class, abstract class or derived/ child class. (Some treat a module of an application as a unit. This is to be discouraged as there will probably be many individual units within that module.) Unit testing frameworks, drivers, stubs, and mock/ fake objects are used to assist in unit testing. METHOD Unit Testing is performed by using the White Box Testing method. When is it performed? Unit Testing is the first level of testing and is performed prior to Integration Testing. BENEFITS Unit testing increases confidence in changing/ maintaining code. If good unit tests are written and if they are run every time any code is changed, we will be able to promptly catch any defects introduced due to the change. Also, if codes are already made less interdependent to make unit testing possible, the unintended impact of changes to any code is less. Codes are more reusable. In order to make unit testing possible, codes need to be modular. This means that codes are easier to reuse. Development is faster. How? If you do not have unit testing in place, you write your code and perform that fuzzy ‘developer test’ (You set some breakpoints, fire up the GUI, provide a few inputs that hopefully hit your code and hope that you are all set.) If you have unit testing in place, you write the test, write the code and run the test. -
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. -
Including Jquery Is Not an Answer! - Design, Techniques and Tools for Larger JS Apps
Including jQuery is not an answer! - Design, techniques and tools for larger JS apps Trifork A/S, Headquarters Margrethepladsen 4, DK-8000 Århus C, Denmark [email protected] Karl Krukow http://www.trifork.com Trifork Geek Night March 15st, 2011, Trifork, Aarhus What is the question, then? Does your JavaScript look like this? 2 3 What about your server side code? 4 5 Non-functional requirements for the Server-side . Maintainability and extensibility . Technical quality – e.g. modularity, reuse, separation of concerns – automated testing – continuous integration/deployment – Tool support (static analysis, compilers, IDEs) . Productivity . Performant . Appropriate architecture and design . … 6 Why so different? . “Front-end” programming isn't 'real' programming? . JavaScript isn't a 'real' language? – Browsers are impossible... That's just the way it is... The problem is only going to get worse! ● JS apps will get larger and more complex. ● More logic and computation on the client. ● HTML5 and mobile web will require more programming. ● We have to test and maintain these apps. ● We will have harder requirements for performance (e.g. mobile). 7 8 NO Including jQuery is NOT an answer to these problems. (Neither is any other js library) You need to do more. 9 Improving quality on client side code . The goal of this talk is to motivate and help you improve the technical quality of your JavaScript projects . Three main points. To improve non-functional quality: – you need to understand the language and host APIs. – you need design, structure and file-organization as much (or even more) for JavaScript as you do in other languages, e.g. -
Testing and Debugging Tools for Reproducible Research
Testing and debugging Tools for Reproducible Research Karl Broman Biostatistics & Medical Informatics, UW–Madison kbroman.org github.com/kbroman @kwbroman Course web: kbroman.org/Tools4RR We spend a lot of time debugging. We’d spend a lot less time if we tested our code properly. We want to get the right answers. We can’t be sure that we’ve done so without testing our code. Set up a formal testing system, so that you can be confident in your code, and so that problems are identified and corrected early. Even with a careful testing system, you’ll still spend time debugging. Debugging can be frustrating, but the right tools and skills can speed the process. "I tried it, and it worked." 2 This is about the limit of most programmers’ testing efforts. But: Does it still work? Can you reproduce what you did? With what variety of inputs did you try? "It's not that we don't test our code, it's that we don't store our tests so they can be re-run automatically." – Hadley Wickham R Journal 3(1):5–10, 2011 3 This is from Hadley’s paper about his testthat package. Types of tests ▶ Check inputs – Stop if the inputs aren't as expected. ▶ Unit tests – For each small function: does it give the right results in specific cases? ▶ Integration tests – Check that larger multi-function tasks are working. ▶ Regression tests – Compare output to saved results, to check that things that worked continue working. 4 Your first line of defense should be to include checks of the inputs to a function: If they don’t meet your specifications, you should issue an error or warning. -
The Art, Science, and Engineering of Fuzzing: a Survey
1 The Art, Science, and Engineering of Fuzzing: A Survey Valentin J.M. Manes,` HyungSeok Han, Choongwoo Han, Sang Kil Cha, Manuel Egele, Edward J. Schwartz, and Maverick Woo Abstract—Among the many software vulnerability discovery techniques available today, fuzzing has remained highly popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of empirical evidence in discovering real-world software vulnerabilities. At a high level, fuzzing refers to a process of repeatedly running a program with generated inputs that may be syntactically or semantically malformed. While researchers and practitioners alike have invested a large and diverse effort towards improving fuzzing in recent years, this surge of work has also made it difficult to gain a comprehensive and coherent view of fuzzing. To help preserve and bring coherence to the vast literature of fuzzing, this paper presents a unified, general-purpose model of fuzzing together with a taxonomy of the current fuzzing literature. We methodically explore the design decisions at every stage of our model fuzzer by surveying the related literature and innovations in the art, science, and engineering that make modern-day fuzzers effective. Index Terms—software security, automated software testing, fuzzing. ✦ 1 INTRODUCTION Figure 1 on p. 5) and an increasing number of fuzzing Ever since its introduction in the early 1990s [152], fuzzing studies appear at major security conferences (e.g. [225], has remained one of the most widely-deployed techniques [52], [37], [176], [83], [239]). In addition, the blogosphere is to discover software security vulnerabilities. At a high level, filled with many success stories of fuzzing, some of which fuzzing refers to a process of repeatedly running a program also contain what we consider to be gems that warrant a with generated inputs that may be syntactically or seman- permanent place in the literature. -
Background Goal Unit Testing Regression Testing Automation
Streamlining a Workflow Jeffrey Falgout Daniel Wilkey [email protected] [email protected] Science, Discovery, and the Universe Bloomberg L.P. Computer Science and Mathematics Major Background Regression Testing Jenkins instance would begin running all Bloomberg L.P.'s main product is a Another useful tool to have in unit and regression tests. This Jenkins job desktop application which provides sufficiently complex systems is a suite would then report the results on the financial tools. Bloomberg L.P. of regression tests. Regression testing Phabricator review and signal the author employs many computer programmers allows you to test very high level in an appropriate way. The previous to maintain, update, and add new behavior which can detect low level workflow required manual intervention to features to this product. bugs. run tests. This new workflow only the The product the code base was developer to create his feature branch in implementing has a record/playback order for all tests to be run automatically. Goal feature. This was leveraged to create a Many of the tasks that a programmer regression testing framework. This has to perform as part of a team can be framework leveraged the unit testing automated. The goal of this project was framework wherever possible. to work with a team to automate tasks At various points during the playback, where possible and make them easier callback methods would be invoked. An example of the new workflow, where a Jenkins where impossible. These methods could have testing logic to instance will automatically run tests and update the make sure the application was in the peer review. -
Introduction to Unit Testing
INTRODUCTION TO UNIT TESTING In C#, you can think of a unit as a method. You thus write a unit test by writing something that tests a method. For example, let’s say that we had the aforementioned Calculator class and that it contained an Add(int, int) method. Let’s say that you want to write some code to test that method. public class CalculatorTester { public void TestAdd() { var calculator = new Calculator(); if (calculator.Add(2, 2) == 4) Console.WriteLine("Success"); else Console.WriteLine("Failure"); } } Let’s take a look now at what some code written for an actual unit test framework (MS Test) looks like. [TestClass] public class CalculatorTests { [TestMethod] public void TestMethod1() { var calculator = new Calculator(); Assert.AreEqual(4, calculator.Add(2, 2)); } } Notice the attributes, TestClass and TestMethod. Those exist simply to tell the unit test framework to pay attention to them when executing the unit test suite. When you want to get results, you invoke the unit test runner, and it executes all methods decorated like this, compiling the results into a visually pleasing report that you can view. Let’s take a look at your top 3 unit test framework options for C#. MSTest/Visual Studio MSTest was actually the name of a command line tool for executing tests, MSTest ships with Visual Studio, so you have it right out of the box, in your IDE, without doing anything. With MSTest, getting that setup is as easy as File->New Project. Then, when you write a test, you can right click on it and execute, having your result displayed in the IDE One of the most frequent knocks on MSTest is that of performance. -
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.