開源日報 每天推薦一個 GitHub 優質開源項目和一篇精選英文科技或編程文章原文,堅持閱讀《開源日報》,保持每日學習的好習慣。
今日推薦開源項目:《一種新的形式 LoveRecord》
今日推薦英文原文:《The Dirtiest Word in Software》
開源日報第511期:《一種新的形式 LoveRecord》
今日推薦開源項目:《一種新的形式 LoveRecord》傳送門:GitHub鏈接
推薦理由:昨天是七夕節(別問昨天幹啥去了,問就改代碼),相信情侶和非情侶都有自己不同的過法吧。這次要介紹的項目是一個用編碼能力來支撐的表達愛意的網站——這只不過是表達愛意的另一種形式,就如同工匠選擇製造,歌手選擇歌唱,詩人用詩句讚頌一樣,表達愛意的形式千變萬化,但是愛的意念始終作為形式的核心,只要牢記這點的話,就算形式再怎麼變換,相信某人總是能感受到的。
今日推薦英文原文:作者:
原文鏈接:https://medium.com/better-programming/the-dirtiest-word-in-software-6590162707a3
推薦理由:理想很豐滿,現實很骨感

The Dirtiest Word in Software

Better wash your mouth out with soap

I swear a lot. Imagine a sailor in a bad mood, with Tourettes. That』s me. I』ve concocted swear words that would peel the paint off the Sistine Chapel. Alas, even with my repertoire of riotous racket, I can』t come close to this word. Prepare yourself.

The word is… prediction. Wow, look at it. Ten letters, all lined up in a particular order. Screw it, I』ll say it again. Prediction!

Why exactly is it such a bad word? Why does it strike fear into the hearts of engineers all over the world? Why is it that even typing this word sends shivers down my spine?

Predictions Are Always Wrong

True. The accuracy of predictions in software leaves a lot to be desired. Every single day we see this: deadlines go unheeded, estimations fall to pieces, meetings are overrun, and budgets are maxed out. Many of us have been burned so often that whenever we』re faced with a date, we panic. 「It will be done when it』s done!」 we screech, with no hint of past trauma at all.

What Can We Do?

We know software isn』t predictable — it』s fraught with variance and hidden complexity. We first need to accept that fact. Things go wrong, and things break. However, much like when we guess the weather, we have tools at our disposal. Tools that can limit the variance, change our perspective, and fine-tune our predictability.

My next articles are going to be on predictability. In them, I will explore the key components of software prediction: the misconceptions, the dysfunctions, the successes, and the outright failures. We』ll go from batch sizes to Poisson distributions to Little』s Law and all the way back. And because I love you guys, we』ll get started right now.

Batch Sizes

No doubt, an agile coach has chased you down a hallway by now. With their arms full of Post-its, they』ve howled, 「Beware the batch size!」 If you』re smart, you would』ve hidden in a cupboard and waited for them to get tired. But what the hell is a batch size?

Imagine a road. That road has got cars flying up and down it all the time. Small coupès dance in and out of the lanes. But one day, a series of lorries pile into the road. Ten of them, all at once. We』ve all likely seen this before — it forms a traffic jam. Why?

Motherfreaking batch sizes

The road can handle lots of small cars that zip in and out of the lanes. However, when a collection of 16-wheeler trucks appear, trouble begins to brew. A large batch of work will suddenly slow other things down. Those little cars are now stuck behind the trucks.

And how does this relate back to predictability?

A key element of predictability is ensuring that things can flow through your system of work. Your team should be able to quickly pick up a task, ascertain a solution, and deliver it. Large tasks take a long time to solve and deliver.

I know what you』re thinking. Half can do the big task, and half can do the small task. Easy! Yet, for a moment, think of the road. The more tasks you kick off in parallel, the more cars on the road. More cars mean longer queues. Teams are almost always disrupted by large batch sizes.

So How Do We Improve This?

When we』re refining our backlog, make sure that the tasks closest to the top are nice and small. The thinnest possible slice is the phrase I keep hearing. Shave the feature down to its purest form. Reveal the essence of the task, the spirit of the story.

With a collection of small stories, there are no lorries on your road. The team can regularly build and deliver working software at rapid intervals. Regular delivery forms a rudimentary kind of predictability. You know that if this small task appears first, it』s very likely to be done sooner.

The next time you』re stuck behind a lorry, or infinitely worse, a stray tractor, remember this. Large batches cause queues. Queues delay work. Delays are the number one cause in unpredictability and missed deadlines. Break down the batches.
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