今日推荐开源项目：《covid-sim》
今日推荐英文原文：《10 Things Every Good Software Development Method Does》
今日推荐开源项目：《covid-sim》传送门：GitHub链接
推荐理由：这是由位于伦敦帝国理工学院的 MRC 全球新型冠状病毒肺炎传染病分析中心开发的 CovidSim 微观仿真模型。随着时间的推移，CovidSim 模拟了新型冠状病毒肺炎感染在整个空间和社会结构人群中的传播动态和严重程度。 它能够模拟干预政策和医疗保健提供如何影响新型冠状病毒肺炎的传播。 随着参数的变化，它可以用来模拟其他呼吸道病毒，如流感病毒。
今日推荐英文原文：《10 Things Every Good Software Development Method Does 》 原文链接：https://codemanship.wordpress.com/2020/05/04/10-things-every-software-developer-should-know/
推荐理由：作者做程序员已经有40年了——其中3年是专业的——在过去的25年里，作者一直热衷于“软件开发”。以下作者认为的每个软件开发者都应该知道的10件事:
10 Things Every Good Software Development Method Does
I’ve been a programmer for the best part of four decades – three of them professionally – and, for the last 25 years, a keen student of this thing we call “software development”. I’ve studied and applied a range of software development methods, principles, and techniques over those years. While, on the surface, Fusion may look different to the Unified Process, which may look different to Extreme Programming, which may look different to DSDM, which may look different to Cleanroom Software Engineering, when you look under the hood of these approaches, they actually have some fundamental things in common.Here are the 10 things every software developer should know:
- Design starts with end users and their goals – be it with use cases, or with user stories, or with the “features” of Feature-Driven Development, the best development approaches drive their solution designs by first asking: Who will be using this software, and what will they be using it to do?
- Designs grow one usage scenario at a time – scenarios or examples drive the best solution designs, and those designs are fleshed out one scenario at a time to satisfy the user’s goal in “happy paths” (or to recover gracefully from not satisfying the user’s goal, which we call “edge cases”). Developers who try to consider multiple scenarios simultaneously tend to bite off more than they can chew.
- Solutions are delivered one scenario at a time – teams who deliver working software in end-to-end slices of functionality (e.g., the UI, business logic and database required to do a thing the user requires) tend to fare better than teams who deliver horizontal slices across their architecture (the UI components for all scenarios, and then the business logic, and then the database code). This is ffor two key reasons. Firstly, they can get user feedback from working features sooner, which speeds up the learning process. Secondly, if they only manage to deliver 75% of the software before a release date, they will have delivered 75% of end-to-end working features, instead of 75% of the layers of all features. We call this incremental delivery.
- Solutions evolve based on user feedback from increments – the other key ingredient in the way we deliver working software is how we learn from the feedback we get from end users in each increment of the software. With the finest requirements and design processes – and the best will in the world – we can’t expect to get it right first time. Maybe our solution doesn’t give them what they wanted. Maybe what they wanted turns out to be not what they really needed. The only way to find out for sure is to deliver what they asked for and let them take it for a spin. And then the feedback starts flooding in. The best approaches accept that feedback is not just unavoidable, it’s very desirable, and teams seek it out as often as possible.
- Plans change – if we can’t know whether we’re delivering the right software for sure until we’ve delivered it, then our approach to planning must be highly adaptable. Although the wasteland of real-world software development is littered with the bleached bones of “waterfall” projects that attempted to get it right first time (and inevitably failed), the idealised world of software development methods rejected that idea many decades ago. All serious methods are iterative, and all serious methods tell us that the plan will necessarily change. It’s management who resist change, not methods.
- Code changes – if plans change based on what we learn from end users, then it stands to reason that our code must also change to accommodate their feedback. This is the sticking point on many “agile” development teams. Their management processes may allow for the plan to change, but their technical practices (or the lack of them) may mean that changing the code is difficult, expensive and risky. There are a range of factors in the cost of changing software, but in the wider perspective, it essentially boils down to “How long will it take to deliver the next working iteration to end users?” If the answer is “months”, then change is going to be slow and the users’ feedback will be backed up like the LA freeway on a Monday morning. If it’s “minutes” then you can iterate very rapidly and learn your way to getting it right much faster. Delivery cycles are fundamental. They’re the metabolism of software development.
- Testing is fast and continuous – if the delivery cycle of the team is its metabolism, then testing is its thyroid. How long it takes to establish if our software’s broken will determine how fast our delivery cycle’ can be (if the goal is to avoid delivering broken software, of course.) If you aspire to a delivery cycle of minutes, then that leaves minutes to re-test your software. If all your testing’s done manually, then a modestly complex system will likely take weeks to re-test. And it’s a double whammy. Studies show that the longer a bug goes undetected, the exponentially greater it costs to fix it. If I break some code now and find out a minute from now, it’s a trifle to fix it. If I find out 6 weeks from now, it’s a whole other ball game. Teams who leave testing late typically end up spending most of their time fixing bugs instead of delivering valuable features and changes. All of this can profoundly impact delivery cycles and the cost of adapting to user feedback. Testing early and often is a feature of all serious methods. Automating our tests so they run fast is a feature of all the best methods.
- All work is undo-able – If we accept that its completely unrealistic to expect to get things right first time, then we must also accept that all the work we do is essentially an experiment from which we must learn. Sometimes, what we’ll learn is that what we’ve done is simply no good, and we need to do over. Software Configuration Management (of which version control is the central pillar) is a key component of all serious software development methods. A practice like Continuous Integration, done right, can bring us high levels of undo-ability, which massively reduces risk in what is a pretty risky endeavour. To use an analogy, think of software development as a multi-level computer game. Experienced gamers know to back up their place in the game frequently, so they don’t have to replay huge parts of it after a boo-boo. Same thing with version control and SCM. We don’t want our versions to be too far apart, or we’ll end up in a situation where we have to redo weeks or months of work because we took a wrong turn in the maze.
- Architecture is a process (not a person or a thing) – The best development methods treat software architecture and design as an ongoing activity that involves all stakeholders and is never finished. Good architectures are driven directly from user goals, ensuring that those goals are satisfied by the design above all else (e.g., use case realisations in the Unified Process), and applying organising principles – Simple Design, “Tell, Don’t Ask”, SOLID etc – to the internals of the solution design to ensure the code will be malleable enough to change to meet future needs. As an activity, architecture encompasses everything from the goals and tasks of end users, to the modular structure of the solution, to the everyday refactorings that are performed against code that falls short, the test suites that guard against regressions, the documentation that ships with the end product, and everything else which is informed by the design process. Since architecture is all-encompassing, all serious development methods mandate that it be a shared responsibility. The best methods strongly encourage a high level of architectural awareness within the team through continuous visualisation and review of the design. To some extent, everyone involved is defining the architecture. It is ever-changing and everyone’s responsibility.
- “Done” means we achieved the customer’s end goal – All of our work is for nothing if we don’t solve the problem we set out to solve. Too many teams are short-sighted when it comes to evaluating their success, considering only that a list of requested features was delivered, or that a product vision was realised. But all that tells us is that we administered the medicine. It doesn’t tell us if the medicine worked. If iterative development is a search algorithm, then it’s a goal-seeking search algorithm. One generation of working software at a time, we ask our end users to test the solution as a fit to their problem, learn what worked and what didn’t, and then go around again with an improved solution. We’re not “done” until the problem’s been solved. While many teams pay lip service to business goals or a business context, it’s often more as an exercise in arse-covering – “We need a business case to justify this £10,000,000 CRM system we’ve decided to build anyway!” – than the ultimate driver of the whole development process. Any approach that makes defining the end goal a part of the development process has put the cart before the horse. If we don’t have an end goal – a problem to be solved – then development shouldn’t begin. But all iterative development methods – and they’re all iterative to some degree – can be augmented with an outer feedback loop that considers business goals and tests working software in business situations, driving everything from there.
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