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When refactoring do you write tests before?

This article is from BMC Bioinformatics , volume 15 . Abstract Background: Scientific workflows management systems are increasingly used to specify and manage bioinformatics experiments. Their programming model appeals to bioinformaticians, who can use them to easily specify complex data processing pipelines. Such a model is underpinned by a graph structure, where nodes represent bioinformatics tasks and links represent the dataflow. The complexity of such graph structures is increasing over time, with possible impacts on scientific workflows reuse. In this work, we propose effective methods for workflow design, with a focus on the Taverna model. We argue that one of the contributing factors for the difficulties in reuse is the presence of "anti-patterns", a term broadly used in program design, to indicate the use of idiomatic forms that lead to over-complicated design. The main contribution of this work is a method for automatically detecting such anti-patterns, and replacing them with different patterns which result in a reduction in the workflow's overall structural complexity. Rewriting workflows in this way will be beneficial both in terms of user experience (easier design and maintenance), and in terms of operational efficiency (easier to manage, and sometimes to exploit the latent parallelism amongst the tasks). Results: We have conducted a thorough study of the workflows structures available in Taverna, with the aim of finding out workflow fragments whose structure could be made simpler without altering the workflow semantics. We provide four contributions. Firstly, we identify a set of anti-patterns that contribute to the structural workflow complexity. Secondly, we design a series of refactoring transformations to replace each anti-pattern by a new semantically-equivalent pattern with less redundancy and simplified structure. Thirdly, we introduce a distilling algorithm that takes in a workflow and produces a distilled semantically-equivalent workflow. Lastly, we provide an implementation of our refactoring approach that we evaluate on both the public Taverna workflows and on a private collection of workflows from the BioVel project. Conclusion: We have designed and implemented an approach to improving workflow structure by way of rewriting preserving workflow semantics. Future work includes considering our refactoring approach during the phase of workflow design and proposing guidelines for designing distilled workflows.

You didn't need a full-blown MVC, you just wanted to add some nice interactive functionality to your server-rendered app. But then one jQuery plugin turns to three, add a dash of statefulness, some error handling, and suddenly you can't sleep at night.   We'll walk through using Ember Components to test-drive a refactor until your front-end code is understandable, usable, and extensible. Armed with TDD and components, you can start to get excited, not exasperated, when asked to add advanced client-side interactions to your website.

The standard approach to generating test suites, manual generation of the test inputs in the suite, is tedious and error-prone, especially for code that takes complex test inputs. This talk presents our approach that automates generation of test suites using test abstractions. Conceptually, test abstractions provide a high-level description of desired test suites; developers do not need to manually write large suites of individual tests but instead write test abstractions from which tools automatically generate individual tests. This approach has helped developers in both academia and industry to discover errors in several real applications. This talk illustrates the approach on testing refactoring engines using imperative test abstractions. Refactorings are behavior-preserving program transformations that improve program design, and refactoring engines are tools that automate the application of refactorings. Refactoring engines are a key component of modern IDEs such as Visual Studio, Eclipse, or NetBeans. A bug in a refactoring engine can have severe consequences as it can erroneously change large bodies of source code. Test inputs for refactoring engines are programs, and the core of our testing of refactoring engines is a framework for generation of abstract syntax trees that represent Java programs. Using this framework, we discovered 21 new bugs in Eclipse and 24 in NetBeans. We didn't test Visual Studio. This is joint work with Brett Daniel, Danny Dig, Kely Garcia, Vilas Jagannath, and Yun Young Lee ©2008 Microsoft Corporation. All rights reserved.

The standard approach to generating test suites, manual generation of the test inputs in the suite, is tedious and error-prone, especially for code that takes complex test inputs. This talk presents our approach that automates generation of test suites using test abstractions. Conceptually, test abstractions provide a high-level description of desired test suites; developers do not need to manually write large suites of individual tests but instead write test abstractions from which tools automatically generate individual tests. This approach has helped developers in both academia and industry to discover errors in several real applications. This talk illustrates the approach on testing refactoring engines using imperative test abstractions. Refactorings are behavior-preserving program transformations that improve program design, and refactoring engines are tools that automate the application of refactorings. Refactoring engines are a key component of modern IDEs such as Visual Studio, Eclipse, or NetBeans. A bug in a refactoring engine can have severe consequences as it can erroneously change large bodies of source code. Test inputs for refactoring engines are programs, and the core of our testing of refactoring engines is a framework for generation of abstract syntax trees that represent Java programs. Using this framework, we discovered 21 new bugs in Eclipse and 24 in NetBeans. We didn't test Visual Studio. This is joint work with Brett Daniel, Danny Dig, Kely Garcia, Vilas Jagannath, and Yun Young Lee ©2008 Microsoft Corporation. All rights reserved.

Ben talks with John Norman about his process and modified approach to the delivery, payment, and tech of modern managed health care. They also touch on age bias in the programming world, living a purpose-driven life, and dealing with startup growth.Iora Health"The Hot Spotters"- Atul GawandeThe Healing of America- T.R. ReidWellnessFXAgile ManifestoHIPAABeing Mortal- Atul Gawande"How to Scale a Development Team"- Adam Wiggins"The Double Diamond Model of Product Definition and Design"- Peter MerholzJohn on TwitterSupport Giant Robots Smashing Into Other Giant Robots

Refactoring is an activity that improves the internal structure of the code without altering its external behavior. When performed on the production code, the tests can be used to verify that the external behavior of the production code is preserved. However, when the refactoring is performed on test code, there is no safety net that assures that the external behavior of the test code is preserved. In this paper, we propose to adopt mutation testing as a means to verify if the behavior of the test code is preserved after refactoring. Moreover, we also show how this approach can be used to identify the part of the test code which is improperly refactored.

Refactoring can improve the quality of a software system as measured by coupling, cohesion, and cyclomatic complexity, but knowing which refactoring choices should be implemented is key. This article presents an approach that guides the refactoring of software systems by combining the use of software metrics and a technique called program slicing. Program slices produced from a single software module are sorted by the respective values of the metrics; a design that provides the most beneficial metric values can be selected from these. This approach can produce a software system with higher quality and maintainability as measured by the metrics.

The standard approach to generating test suites, manual generation of the test inputs in the suite, is tedious and error-prone, especially for code that takes complex test inputs. This talk presents our approach that automates generation of test suites using test abstractions. Conceptually, test abstractions provide a high-level description of desired test suites; developers do not need to manually write large suites of individual tests but instead write test abstractions from which tools automatically generate individual tests. This approach has helped developers in both academia and industry to discover errors in several real applications. This talk illustrates the approach on testing refactoring engines using imperative test abstractions. Refactorings are behavior-preserving program transformations that improve program design, and refactoring engines are tools that automate the application of refactorings. Refactoring engines are a key component of modern IDEs such as Visual Studio, Eclipse, or NetBeans. A bug in a refactoring engine can have severe consequences as it can erroneously change large bodies of source code. Test inputs for refactoring engines are programs, and the core of our testing of refactoring engines is a framework for generation of abstract syntax trees that represent Java programs. Using this framework, we discovered 21 new bugs in Eclipse and 24 in NetBeans. We didn't test Visual Studio. This is joint work with Brett Daniel, Danny Dig, Kely Garcia, Vilas Jagannath, and Yun Young Lee ©2008 Microsoft Corporation. All rights reserved.

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Jeff Hurray joins us to talk about refactoring, tech debt, and architectural contagion. Also the \"Swarm of Drones Lux\" ride mode.

So you've released a library! Now you need to maintain it. You want to add features, restructure the code, fix bugs, and maybe improve the library's usability. Your users just want their code to carry on working. That's okay! This talk will cover techniques in both code and project management to allow you to keep your code moving forwards without breaking your users' code. It is aimed at developers with a little experience of writing libraries in Python, and will cover some intermediate subjects like function decorators and magic methods. Refactoring in Python is a mixed bag - on the one hand you have powerful tools like the @property decorator, __dunder__ methods, and even metaclasses. On the other hand, because Python code has no concept of private or protected like some other languages, it can be difficult to know what your public interface even is. I'll talk about how to identify your public interface, and make that clear to your users. I'll cover how to structure your tests so you know when you've broken your public interface. I'll discuss how to use some of Python's language features to trick your users into thinking your code hasn't changed at all (except for those brilliant new features you've just added!). And finally, I'll cover how you know it's time to break backwards compatibility and how to break it to your users. Please see our speaker release agreement for details: https://ep2017.europython.eu/en/speaker-release-agreement/

KBall, Nick, and Chris dig into the various dimensions along which projects vary, dig into testing and best practices, and share a number of lessons learned from legacy projects.

Robby speaks with Jason Swett, Software Engineer at Meadows Eye. They discuss the value of understandability, differences between loose and tight coupling in code, and creating a shared vision as a team. Jason also discusses how teams struggle to retain quality engineers and how to teach testing to Ruby on Rails developers.

[Replacement talk] This talk was a replacement for Stanislav Geidl's talk: From legacy code to modern code Honest apologies to anyone whose expectations were subverted, but Stanislav fell sick and could not attend. Find the updated abstract below: This talk will describe experiences and lessons learned from tackling extremely demanding code. How to bring order to mismanaged code and elevate the code base to a standard that's acceptable in today's tech environment. Python makes wonderful code accessible at our fingertips, but it also allows us to take a lot of liberty. When you start, code is beautiful and makes sense. With each step you walk on, you find more and more hacks showing up. Eventually, the brilliant codebase you've started with can not be seen under the mud. Not every code-base can be rewritten, not everything can be redone from scratch. Cool libraries often take a lot of liberty with code structure and make cross-integration difficult, if not impossible. Tests sound ideal, but in practice, they're just so hard to make right. Why is this, and how to change it? The talk will tackle the problems in three parts: - The Easy Wins: What to do to instantly increase the code quality in your organisation. How? Why isn't it enough? - Patterns and Antipatterns: How to identify code that ""smells"", how to replace it? How to integrate into old code, better? - The Philosophy: What approach to set down for the future? Why to care? How to write replace-able code. How to prevent history from repeating. The talk will close with audience discussion and experiences, questions and proposals - building a collection of some on-premise tips and tricks. Please see our speaker release agreement for details: https://ep2019.europython.eu/events/speaker-release-agreement/

Please let us know your take-away of this episode by sharing it with us @_contravariance. An iTunes review is also greatly appreciated! Contact information Contravariance's website GitHub repository Contravariance's Twitter Benedikt's Twitter Bas' Twitter Benedikt's blog Bas' blog Swift Island Swift Island Swift Aveiro The Swift Alps Personal Projects SwiftConf Ray Wenderlich Swift Weekly Brief Appventure.me Appventure.me's Static Site Generator Live Reloading John's Static Site Generator progress The Swift Community Podcast: SwiftUI First Impressions iPadOS Scene support An Introduction to iPadOS Catalyst Benedikt's Catalyst Guide Touch Bar Documentation Antoine van der Lee Project of the week...ish Bismuth Gosh Darn SwiftUI

Replaced by https://www.youtube.com/watch?v=p_cz7AxVdfg (better audio) For Go 1.5, the standard library gained a new package. The Go type checker, go/types, is the foundation for several static analysis tools that can help Go programmers understand, navigate, and refactor their code. In this talk, Alan Donovan will demonstrate these tools and explain the concepts of the go/types API so that you can use it in your own projects. Alan Donovan is a Staff Engineer in Google's infrastructure division in New York, specializing in software-development tools. In 2005, he initiated and led the development of Google's proprietary build system, now open-sourced as Bazel, and has contributed to Google's production monitoring and cluster configuration tools. Since 2012, he has been working on the Go team, designing libraries and tools for static analysis. He is the author of the Go oracle, godoc -analysis, eg, and gorename tools, and is the co-author, with Brian Kernighan, of the forthcoming book The Go Programming Language . See http://gothamgo.com/program#alan_donovan

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

For more information refer to the talk page .

Austin Bingham - Python refactoring with Rope and Traad [EuroPython 2014] [23 July 2014] Rope is a powerful Python refactoring library. Traad (Norwegian for “thread”) is a tool which makes it simpler to integrate rope into IDEs via a simple HTTP API. In this session we’ll look at how traad and rope work together and how traad integrates with at least one popular editor. ----- Python is a modern, dynamic language which is growing in popularity, but tool support for it is sometime lacking or only available in specific environments. For refactoring and other common IDE functions, however, the powerful open-source rope library provides a set of tools which are designed to be integrated into almost any programming environment. Rope supports most common refactorings, such as renaming and method extraction, but also more Python-specific refactorings, such as import organization. Rope’s underlying code analysis engine also allows it to do things like locating method definitions and generating auto-completion suggestions. While rope is designed to be used from many environments, it’s not always easy or ideal to integrate rope directly into other programs. Traad (Norwegian for “thread”) is another open-source project that addresses this problem by wrapping rope into a simple client-server model so that client programs (IDEs, editors, etc.) can perform refactorings without needing to embed rope directly. This simplifies dependencies, makes clients more robust in the face of errors, eases traad client development, and even allows clients to do things like switch between Python 2 and 3 refactoring in the same session. In this session we’ll look at how rope operates, and we’ll see how traad wraps it to provide an easier integration interface. The audience will get enough information to start using rope themselves, either directly or via traad, and they’ll see how to use traad for integrating rope into their own environments. More generally, we’ll look at why client-server refactoring tools might be preferable to the more standard approach of direct embedding.

How Go can better help refactoring of the overall package structure of your code. Russ Cox has helped to create the Go Programming Language since 2008, when the language was still just a prototype. His work there started with the Go compiler and runtime, and developing Go's standard library. Today, he is a co-Tech Lead for the Go project and the Go team (a role he shares with Rob Pike).

How Go can better help refactoring of the overall package structure of your code. Russ Cox has helped to create the Go Programming Language since 2008, when the language was still just a prototype. His work there started with the Go compiler and runtime, and developing Go's standard library. Today, he is a co-Tech Lead for the Go project and the Go team (a role he shares with Rob Pike).

Robby speaks with Victor Rentea, an independent technical trainer and Lead Architect at IBM based in Romania. Victor talks about teaching other engineers about legacy code, calling yourself an "expert", and what to do when you're rushed to deliver features but are dealing with refactoring challenges.

Refactoring is an established technique from the OO-community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the OO-paradigm in particular, its ideas have not been applied to Logic Programming until now. This paper applies the ideas of refactoring to Prolog programs. A catalogue is presented listing refactorings classified according to scope. Some of the refactorings have been adapted from the OO-paradigm, while others have been specifically designed for Prolog. Also the discrepancy between intended and operational semantics in Prolog is addressed by some of the refactorings. In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and the experience with applying \vipress to a large Prolog legacy system is reported. Our main conclusion is that refactoring is not only a viable technique in Prolog but also a rather desirable one.

The series of the scammer who is named Nour Saidana. Uploading all of the videos in this series will be uploaded here for knowledge of his practices and scams, along with having these here in case of an inevitable lawsuit against him for his practices.

The series of the scammer who is named Nour Saidana. Uploading all of the videos in this series will be uploaded here for knowledge of his practices and scams, along with having these here in case of an inevitable lawsuit against him for his practices.

Mike Barnett chairs this session at Faculty Summit 2011, which includes the following presentations. Project Roslyn: Exposing the VB and C# Compiler’s Code Analysis—Karen Ng, Microsoft Beyond Behavior Preservation—Ralph Johnson, University of Illinois, Urbana Champaign How Are Developers Using Refactoring Tools?—Emerson Murphy-Hill, North Carolina State University ©2011 Microsoft Corporation. All rights reserved.

Robby speaks with Clare Sudbery, Lead Engineer with Made Tech. They discuss how to document and prioritize technical debt with a visual tool, trunk-based development patterns, and the importance of getting fast feedback.

Robby speaks with Clare Sudbery, Lead Engineer with Made Tech. They discuss how to document and prioritize technical debt with a visual tool, trunk-based development patterns, and the importance of getting fast feedback.

John Reese https://2018.northbaypython.org/schedule/presentation/23/ Python includes a concrete syntax tree (CST) in the standard library, useful for mass refactoring code bases of all sizes. I'll walk through the differences between abstract and concrete syntax trees (AST and CST), why a CST is useful for refactoring, and how you can build basic refactoring tools on top of a CST to modify your entire code base quickly and safely. Lastly, I'll demonstrate what's possible with these tools, including upgrading code to new interfaces, or wholesale movement of code between modules. This talk assumes a basic understanding of how Python works, but will otherwise provide enough context to be useful to those who haven't previously worked with syntax trees. A Python conference north of the Golden Gate North Bay Python is a single-track conference with a carefully curated set of talks representing the diverse Python community and their different areas of interest. If a topic is less to your interest, or you've met some people you really want to sit down and chat with, we'll have plenty of areas away from the main theatre to catch up and chat. Our goal is to keep prices as low as possible. That means we won't be catering lunch. Instead, you can look forward to extra-long lunch breaks you can use to explore all of the great food options around the venue.

JavaScript systems are becoming increasingly complex and large. To tackle the challenges involved in implementing these systems, the language is evolving to include several constructions for programming- in-the-large. For example, although the language is prototype-based, the latest JavaScript standard, named ECMAScript 6 (ES6), provides native support for implementing classes. Even though most modern web browsers support ES6, only a very few applications use the class syntax. In this paper, we analyze the process of migrating structures that emulate classes in legacy JavaScript code to adopt the new syntax for classes introduced by ES6. We apply a set of migration rules on eight legacy JavaScript systems. In our study, we document: (a) cases that are straightforward to migrate (the good parts); (b) cases that require manual and ad-hoc migration (the bad parts); and (c) cases that cannot be migrated due to limitations and restrictions of ES6 (the ugly parts). Six out of eight systems (75%) contain instances of bad and/or ugly cases. We also collect the perceptions of JavaScript developers about migrating their code to use the new syntax for classes.

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Delta-oriented programming (DOP) is a flexible transformational approach to implement software product lines. In delta-oriented product lines, variants are generated by applying operations contained in delta modules to a (possibly empty) base program. These operations can add, remove or modify named elements in a program (e.g., classes, methods and fields in a Java program). This paper presents algorithms for refactoring a delta-oriented product line into monotonic form, i.e., either to contain add and modify operations only (monotonic increasing) or to contain remove and modify operations only (monotonic decreasing). Because of their simpler structure, monotonic delta-oriented product lines are easier to analyze. The algorithms are formalized by means of a core calculus for DOP of product lines of Java programs and their correctness and complexity are given.

Alan Donovan gives a guided tour of several static analysis tools designed to help Go programmers understand, navigate and refactor their code. Join us for the next DigitalOcean Meetup: http://www.meetup.com/DigitalOcean_Community/

Python Facilitating Code Refactoring Abstract Ben Christenson

All about the recent refactoring pieces announced at WWDC 2017 and open sourced in the last few months.

Demo of using the Refactoring Browser in VisualWorks Smalltalk 5

In this episode, Adam and Steve Schoger answer listener questions about UI design, and share all of the details about their upcoming book and design resource Refactoring UI.

Episodio sobre refactoring. Cuando lo hacemos? hablamos sobre esto, sobre la utilidad que le encontramos y damos alguna bobliografía que a nosotros nos sirvió para asimilar conceptos.

Amal Hussein (Engineering Manager at npm) joined the show to talk about AST's - aka, abstract syntax trees. Amal is giving a talk at All Things Open on the subject so we asked her to give us an early preview. She's on a mission to democratize the knowledge and usage of AST's to push legacy code and the web forward.

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Context: Developers design test suites to automatically verify that software meets its expected behaviors. Many dynamic analysis techniques are performed on the exploitation of execution traces from test cases. However, in practice, there is only one trace that results from the execution of one manually-written test case. Objective: In this paper, we propose a new technique of test suite refactoring, called B-Refactoring. The idea behind B-Refactoring is to split a test case into small test fragments, which cover a simpler part of the control flow to provide better support for dynamic analysis. Method: For a given dynamic analysis technique, our test suite refactoring approach monitors the execution of test cases and identifies small test cases without loss of the test ability. We apply B-Refactoring to assist two existing analysis tasks: automatic repair of if-statements bugs and automatic analysis of exception contracts. Results: Experimental results show that test suite refactoring can effectively simplify the execution traces of the test suite. Three real-world bugs that could previously not be fixed with the original test suite are fixed after applying B-Refactoring; meanwhile, exception contracts are better verified via applying B-Refactoring to original test suites. Conclusions: We conclude that applying B-Refactoring can effectively improve the purity of test cases. Existing dynamic analysis tasks can be enhanced by test suite refactoring.

Software architecture is defined as the process of a well-structured solution that meets all of the technical and operational requirements, as well as improving the quality attributes of the system such as readability, Reliability, maintainability, and performance. It involves a series of design decisions that can have a considerable impact on the systems quality attributes, and on the overall success of the application. In this work, we start with analysis and investigation of two open source software (OSS) platforms DMARF and GIPSY, predominantly implemented in Java. Many research papers have been studied in order to gain more insights and clear background about their architectures, enhancement, evolution, challenges, and features. Subsequently, we extract and find their needs, high-level requirements, and architectural structures which lead to important design decisions and thus influence their quality attributes. Primarily, we reversed engineering each system0s source code to reconstruct its domain model and class diagram model. We tried to achieve the traceability between requirements and other design artifacts to be consistent. Additionally, we conducted both manual and automated refactoring techniques to get rid of some existing code smells to end up with more readable and understandable code without affecting its observable behavior.

We describe how to use refactoring tools to transform a Java program conforming to the Composite design pattern into a program conforming to the Visitor design pattern with the same external behavior. We also describe the inverse transformation. We use the refactoring tool provided by IntelliJ IDEA.

You didn't need a full-blown MVC, you just wanted to add some nice interactive functionality to your server-rendered app. But then one jQuery plugin turns to three, add a dash of statefulness, some error handling, and suddenly you can't sleep at night.   We'll walk through using Ember Components to test-drive a refactor until your front-end code is understandable, usable, and extensible. Armed with TDD and components, you can start to get excited, not exasperated, when asked to add advanced client-side interactions to your website.

One of the easiest ways to clean up a design is to simply give every element a little more room to breathe.

Perma.cc archive of http://www.randomhacks.net/2007/02/21/refactoring-probability-distributions/ created on 2016-08-24 22:31:19+00:00.

GothamGo 2015: Using go/types for Code Comprehension and Refactoring Tools by Alan Donovan For Go 1.5, the standard library gained a new package. The Go type checker, go/types, is the foundation for several static analysis tools that can help Go programmers understand, navigate, and refactor their code. In this talk, Alan Donovan will demonstrate these tools and explain the concepts of the go/types API so that you can use it in your own projects. Alan Donovan is a Staff Engineer in Google's infrastructure division in New York, specializing in software-development tools. In 2005, he initiated and led the development of Google's proprietary build system, now open-sourced as Bazel, and has contributed to Google's production monitoring and cluster configuration tools. Since 2012, he has been working on the Go team, designing libraries and tools for static analysis. He is the author of the Go oracle, godoc -analysis, eg, and gorename tools, and is the co-author, with Brian Kernighan, of the forthcoming book The Go Programming Language . See http://gothamgo.com/program#alan_donovan This is a replacement (with better audio) of this earlier upload: https://www.youtube.com/watch?v=3N381ubZTeo