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Handling error conditions is a core part of the software we write. However, we often treat it as a second class citizen, obscuring our intent through abuse of null values and exceptions that make our code hard to understand and maintain. In the functional programming community, it is common to use datatypes such as Option, Either or Validated to make our intentions explicit when dealing with errors. We can leverage the compiler to verify that we are handling them instead of hoping for the best at runtime. This results in code that is clearer, without hidden path flows. We’ll show how we have been doing this in Kotlin, with the help of the Arrow library.
Error handling
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Thoughtworks
Mutation testing in software development surfaced in academia during the 70's and has recently seen a resurgence in popularity as a legitimate tool in your testing arsenal. In this session we review the conventional testing pyramid, modern approaches to testing software and look at how mutation testing can help fill in those blind spots.
Your test coverage is a lie!
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The continued adoption of containers for deployments has introduced a new path for security issues. In this talk, we will cover the most common areas of vulnerabilities, the challenges in securing your containers, some good practices to help overcome these issues and how to run container security scanning as part of your deployment pipeline.
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Mainframes handle 30 billion business transactions each day and 87% of all credit card transactions*, they are not traditionally associated with flexible, fail-fast development approaches. Can we bring the practices of agile, CI/CD and fully automated deployments to applications running on a mainframe? During our talk, we'll tell you a story about test automation; redefining the smallest testable unit of a program. And we'll discuss our learnings from introducing continuous integration and agile practices to the world of insurance and mainframes. *9 Mainframe statistics that may surprise you
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ThoughtWorks' Lucy Kurian, James Lewis & Kief Morris discuss tech trends in our latest Technology Radar, covering techniques, platforms, tools, languages and frameworks.
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Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.
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Speed up your Tests - Devi Sridharan, ThoughtWorks
1.
Speed up your
tests Devi Sridharan
2.
Long test suite….
3.
Identify flaky tests Never
heard of it!!!
4.
Flaky Test contd… Isolate
flaky test Analyse Fix the flakiness Monitor it continuously
5.
Parallelisation Independent tests Multiple Virtual
machines Parallel execution tools (selenium Grid,Test Load Balancer etc )
6.
Break the Tests Smoke
Test Suite Regression Test Suite
7.
Create smart test
data A wise QA once said:
8.
Create smart test
data[Contd…] Create test data via database or API fast Reliable
9.
Fan of xpaths?? To
identify objects Use direct attributes like id,name Avoid generic locators like //table/tr[2]/td
10.
More caffeine to
tests… say ‘NO’ to generic waits Conditional waits
11.
Unit test is
no more Dev’s Territory… :)
12.
Questions???
Download now