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A biking street in the Netherlands

Cycling in the Netherlands is much safer and more convenient than in many other countries, because of the infrastructure - cycle paths, cycle lanes, and signposted cycle routes - and because of the small distances and flatness. All these factors plus many more additional facilities such as numerous picnic places, terraces, small ferry-connections and camping places, makes it often preferable to discover the country by bike rather than by car.

The proliferation of bicycles also means that you're seen as a significant part of the traffic mix - motorists will let you know if you don't keep to the rules and presume you are aware of other traffic. This is specially important to know in the very busy (chaotic) centres of the biggest cities. Here it can be sensible to get off your bike for a few hundred metres and/or leave the centre entirely by taking the bike onto a train, metro or randstadrail-tram).

Some things to know:

Regular signs for bicycle routes are usually white, with a red border and lettering, more recreational/touristic routes to a town or village are green lettered. In rural areas as well as in nature areas, signposts may be so called Paddenstoelen (mushrooms). These are small boxes (more or less resembling the form of a mushroom) near the ground on which the destinations are printed.

There are different ways to use a bicycle:

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Parked bikes in Amsterdam

Bike theft is a serious problem in the Netherlands, especially around train stations, and in larger cities. If possible, use the guarded bike parking ('stalling') at train stations and in some city centres. They will cost up to €1.20 per day. In general, use 2 locks of different kinds (for example, one chain lock and one tube lock). This is because most bike thieves specialize in a particular kind of lock, or carry equipment best suited to one kind of lock. Ideally, you should lock the bike to a lamppost or similar. Bike thieves have been known to simply load unattached bikes onto a pickup truck, so they can crack open the locks at leisure.

In cities, bikes are often stolen by drug addicts, and they sell most stolen bikes too. They often simply offer them for sale to passers-by, if they think no police are watching. Buying a stolen bike is itself illegal, and police do arrest buyers. If you buy for a suspiciously low price (e.g. €10-20), or in a suspicious place (in general, on the street), the law presumes you "know or should have known" the bike was stolen. In other words, actual ignorance of the bike's origins is no excuse.

Bike thefts should be reported to the police. Please do so.

Bike shops are the best place to buy a second-hand bike legally, but prices are high. Some places where you can rent bikes will also sell their written off stock, which is usually well maintained. Most legal (and often cheap) second-hand bike sales now go through online auction sites like marktplaats.nl - the Dutch subsidiary of .

In Study 3, the differences we observe are likely a result of how the average person uses these devices. Smartphones are more likely to be used day-to-day, compared to tablets ( Rainie Zickhur, 2016 ), resulting in differing patterns of news behavior ( Horrigan Duggan, 2015 ). Tablets are also much more likely to be used at home than on mobile networks, making “the dynamics of tablet use more in line with traditional PC-based access than handheld device-based access” ( Napoli Obar, 2014 : 324). Thus, we might expect fewer distinctions between tablet and computer users than between smartphone and computer users. It is also important to note: (a) the number of tablet users is fewer than smartphone users, and (b) smartphones are much more likely to be the devices on which people with mobile-only Internet access rely ( Horrigan Duggan, 2015 ). The attentional deficits we identify for smartphones may be most critical because they apply to more people and to groups most likely to be mobile dependent.

People believe their mobile devices make life easier, going so far as to say they couldn’t live without their smartphones ( Rainie Perrin, 2017 ). However, as others have argued and as our results highlight, access and exposure are distinct from attention ( Chaffee Schleuder, 1986 ). These differences between perceptions of attention and actual attention to information are why it is so important that we unpack the complicated relationship between user, device, and information characteristics. The results we present here should give the news industry pause: readers on mobile devices may spend less time on their sites and be less focussed on their content ( Molyneux, 2017 ). Our results also point to the need to go beyond user-experience testing to include social scientific outcomes. The rush to monetize mobile news delivery may exacerbate the costs of information processing on mobile devices. Building economic value into mobile news may inadvertently decrease its democratic value.

This project was funded in part by the Texas AM University Department of Communication and College of Liberal Arts and the Manship School of Mass Communication at Louisiana State University. We would like to thank the following individuals for helpful conversations and feedback at various stages of this project: Vin Arceneaux, Leticia Bode, Amber Boydstun, Scott Campbell, Kirby Goidel, Jennifer Jerit, Martin Johnson, Mark Peffley, David Peterson, Stuart Soroka, Jamie Settle, Talia Stroud, Emily Sydnor, Chris Weber, and Chris Wlezien. We are also grateful to participants in the Political Communication Lecture Series, Department of Communication Studies, University of Texas at Austin, November 7, 2016, participants at the Experimental Approaches to Studying Democratic Politics Conference, Princeton University, Princeton, New Jersey May 5–6, 2016, the Social Psychology Colloquia, Department of Psychology, Texas AM University, March 25, 2017, participants at the St. Louis Area Methods Meeting, University of Missouri, April 22, 2017, and the Political Behavior and Political Institutions Research Group , Political Science, Texas AM University, May 9, 2017.

At least 10,000. Maybe a million. One million .

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Consider 10 layers with 3 potential branch points at each layer. Number of code paths: 3 10 > 59,000. How about 4 branch points per layer? 4 10 > 1,000,000. How about 3 branch and 12 layers? 3 12 > 530,000.

Even if one of your 12 layers has a single code path, 3 11 > 177,000.

Even if your 10-layer application has only an average of 3.5 code paths per layer, 3.5 10 > 275,000 1 .

To simplify the arithmetic, suppose you need only 100,000 integrated tests to cover your application. Integrated tests typically touch the file system or a network connection, meaning that they run on average at a rate of no more than 50 tests per second. Your 100,000-test integrated test suite executes in 2000 seconds or 34 minutes. That means that you execute your entire test suite only when you feel ready to check in. Some teams let their continuous build execute those tests, and hope for the best, wasting valuable time when the build fails and they need to backtrack an hour.

How long do you need to write 100,000 tests? If it takes 10 minutes to write each test—that includes thinking time, time futzing around with the test to make it pass the first time, and time maintaining your test database, test web server, test application server, and so on—then you need 2,778 six-hour human-days (or pair-days if you program in pairs). That works out to 556 five-day human-weeks (or pair-weeks).

Even if I overestimate by a factor of five, you still need two full-time integrated test writers for a one-year project and a steady enough flow of work to keep them busy six hours per day and you can’t get any of it wrong, because you have no time to rewrite those tests.

No.You’ll have those integrated test writers writing production code by week eight.

Since you won’t write all those tests, you’ll write the tests you can. You’ll write the happy path tests and a few error cases. You won’t check all ten fields in a form. You won’t check what happens on February 29. You’ll jam in a database change rather than copy and paste the 70 tests you need to check it thoroughly. You’ll write around 50 tests per week, which translates to 2,500 tests in a one-year project. Not 100,000.

2.5% of the number you need to test your application thoroughly.

Even if you wrote the most important 2.5%, recognizing the nearly endless duplication in the full complement of tests, you’d cover somewhere between 10% and 80% of your code paths, and you’ll have no idea whether you got closer to 10% or 80% until your customers start pounding the first release.

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So you write your 2,500 integrated tests. Perhaps you even write 5,000 of them. When your customer finds a defect, how will you fix it? Yes: with another handful of integrated tests. The more integrated tests you write, the more of a false sense of security you feel. (Remember, you just increased your code path coverage from 5% to 5.01% with those ten integrated tests.) This false sense of security helps you feel good about releasing more undertested code to your customers, which means they find more defects, which you fix with yet more integrated tests. Over time your code path coverage decreases because the complexity of your code base grows more quickly than your capacity to write enough integrated tests to cover it.

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Christchurch United FC is a proud football club based in Christchurch, New Zealand, with a strong history of provincial and international representative players, championship wins and Chatham Cup success.

The club is based at Christchurch Football Centre, 466 Yaldhurst Road, Yaldhurst.

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