A tool to help determine weights (or a feature of a creditmap tool) seems most likely to be successful. Such a tool would likely have provide simultaneous views of the credit map and weights: one that allows a detailed view of any particular contriponent and its weight, and the other that provides a view (perhaps graphical) of the entire creditmap and weights.

The value of transitive credit is in measuring the indirect contributions to a product, which today are not quantitatively captured

how the credit map for a product A, which is used by a product B, feeds into the credit map for product B

Any product should list all authors (as currently listed as authors of a paper), all contributors (as currently listed in the acknowledgements of a paper) and all component products that have been used, including both publications and other products such as software and data (as currently either cited, acknowledged, or not included in a paper).

Methods for doing this weighting, whether using a taxonomy or a more traditional list of authors, and analysis of these methods and their impact would likely be developed if this overall idea moves forward.

Guide to Select a Software Development Company

for example, comments and identifiers

AI Robots will be replacing the White Collar Jobs by 6% until 2021

As was hinted at from the star

The Grid is based around ideas familiar to Bitwig Studio

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You can not only apply it to classes, but also to software components and microservices.

picking one and sticking to it is far better than the chaos that ensues when everybody does their own thing

Not every committer has the rights to release or make high level decisions, so we can be much more liberal about giving out commit rights. That increases the committer base for code review and bug triage. As a wider range of expertise in the committer pool smaller changes are reviewed and adjusted without the intervention of the more technical contributors, who can spend their time on reviews only they can do.

The rise of agile coincided with the rise of startups using open source projects. At first, startups just incorporated those projects into their own software. But like any cultural exchange, open source began to affect how startups built products, too.

In short we move all of the new operators to a factory. We group all of the objects of similar lifetime into a single factory

By the way, if the point about being global is that a Singleton can be included in any file and used anywhere in a program, that’s true, but only bad if misused. The Singleton pattern is not inherently bad, it’s misuse is bad

If the singleton class is a “utility class” (e.g. FileUtils, StringUtils, etc.), and has no state, then I would say it’s okay. Such a class is not a liar, per se, because there is no unexpected state change or dependency

ccp.chargePurchaseToCard(100,c); since the logic for purchasing will be in the processor anyway, not the card. Cards don’t process anything

You shouldn’t really be doing this anyway – you should have composed them, possibly via IOC.

It would violate it if you stored a reference to context instead of the engine and later on referred tried to get the engine. For example: class Mechanic { Context context; Mechanic(Context context) { this.context = context; } bool CheckEngine() { return this.context.getEngine().checkIfBusted(); } }

Every time I have to write a test I have to create a graph of objects (the haystack) which no one really needs or cares for, and into this haystack I have to carefully place the needles (the real object of interests) so that the code under test can go and look for them. I have to create the Context just so when I construct the Mechanic it can reach in the Context and get what it realy needs, the Engine. But context is never something which is easy to create. Since context is a kitchen sink which knows just about everything else, its constructor is usually scary. So most of the time I can’t even instantiate Mechanic, not to mention run any tests on it. The testing game is over before it even started

His point seems to be that Constructor Injection can be an anti-pattern if applied too much, particularly if a consumer doesn't need a particular dependency in the majority of cases

The law of leaky abstractions means that whenever somebody comes up with a wizzy new code-generation tool that is supposed to make us all ever-so-efficient, you hear a lot of people saying "learn how to do it manually first, then use the wizzy tool to save time."

A famous example of this is that some SQL servers are dramatically faster if you specify "where a=b and b=c and a=c" than if you only specify "where a=b and b=c" even though the result set is the same. You're not supposed to have to care about the procedure, only the specification. But sometimes the abstraction leaks and causes horrible performance

TCP attempts to provide a complete abstraction of an underlying unreliable network, but sometimes, the network leaks through the abstraction and you feel the things that the abstraction can't quite protect you from. This is but one example of what I've dubbed the Law of Leaky Abstractions

Isolate the dependencies Write the test first Draw the boundary Implement the logic

the study of innovation shows that everything hinges on the hard work of taking a promising idea and making it work — technically, legally, financially, culturally, ecologically. Constraints are great enablers of innovation.

But there’s a downside to the hackathon hype, and our research on designing workplace projects for innovation and learning reveals why. Innovation is usually a lurching journey of discovery and problem solving. Innovation is an iterative, often slow-moving process that requires patience and discipline. Hackathons, with their feverish pace, lack of parameters and winner-take-all culture, discourage this process. We could find few examples of hackathons that have directly led to market success.

what if projects were designed to combine a hacking mindset with rigorous examination of the data and experience they glean? This would reward smart failures that reveal new insights and equip leaders with the information needed to rescale, pivot or axe their projects.

Without feedback, there are three options: I can believe, without evidence, that I am an awesome programmer.  I can believe, without evidence, that I am a terrible programmer and quit to go do something else.  Or finally, I can believe, without evidence, that I am a terrible programmer somehow successfully pretending to be an awesome programmer.

Advice to software development interns