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By Suzanne Elly. Featured contributors. Joan Selby. Juned Ghanchi. Allaine Lines. Got a story or tip for us? Sign Up for Newsletter Get fresh news, tips, inspiration you need to know from the WWS experts delivered right to your inbox - absolutely free. By David K. By Alexandra Reay. By Brad Smith. By Sara Santos. By Jack Johnson. How does these measurements apply to software development? A team does not always have an impact on contract negotiation, so often talking about money is far from everyday reality kudos to you if you can apply that point of the Agile Manifesto.
With Test-Driven Development, we are getting good at moving a feature from implemented to tested directly in the same commit. Yet the missing step is getting the feature to the users: maybe that's also what Continuous Deployment is all about Dependent events and statistical fluctuations are production systems topics that make a balanced plant close to bankruptcy : however, we're not at the point in which we can model our team as precisely as a factory.
The basic point is that a plant in which everyone is working all the time is inefficient: when an early stage like defining a specification or implementing a feature gets delayed, downstream step such as deployment are dalayed too.
Converely, when an upstream step finish earlier, the downstream stage is already at maximum efficiency and cannot process the intermediate result faster. I wonder if this applies to software development too.
In a factory, workers are specialized and can do just a few jobs across the plant. Since workers and machines have different production rates, there will be just one bottleneck: the slowest one. If products have to pass from the bottleneck, anyone producing faster than the bottleneck will just accumulate WIP in front of him. Continuing with our example, if the analyst or domain expert is churning out specifications for new features every day , most of them are just WIP in front of the development team.
Once there is an established buffer, any additional specification won't raise throughput any faster; instead, it will raise the inventory partial features and the time spent in managing it. I think this is not always true in the most technical phases of development instead.
For example, in a small team a developer may be moved to testing or refactoring, or setting up Continuous Integration or evaluation of a new library. Unless you have a DBA which can just manage databases, your developer is not fixed into a stage of the system. Integrate and implement SOA Sabre services into banking system to allow bank users to redeem reward points online.
Implement a solution to meet web accessibility standards and guidelines WACG along the site content. Redesign layout permitted that people with disabilities can perceive, understand, navigate, and interact with the Web.
Build an indoor positioning system using WiFi, accelerometer and magnetometer signals to locate a shopper in a particular department or aisle. Lead data collection, pre-processing and classification algorithms. Create a platform to make display ads contextually relevant. Save the company thousands of dollars by proposing and implementing the use of open-source Java Native Access to extract critical data from a third-party mileage application, which was otherwise unavailable.
Represent the company writing technical articles and giving lectures at conferences and meetups. Advocate for coding standards and better performance, by measuring and fixing issues found with tools such as YSlow.
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