Chris Hart - Bookmarks

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Cloud computing and your career | Cloud Computing - InfoWorld

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Google

"The most interesting novels," Newsweek editor Malcolm Jones wrote in a recent book review, "are the ones where the flaws and virtues can't be pulled apart."

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Dr. Dobb's | Software Engineering ≠ Computer Science | June 4, 2009

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Software engineering has an essential human component. Software maintainability, for example, is the ability of people to understand, find, and repair defects in a software system. The maintainability of software may be influenced by some formal notions of computer science -- perhaps the cyclomatic complexity of the software's control graph. But maintainability crucially involves humans, and their ability to grasp the meaning and intention of source code. The question of whether a particular software system is highly maintainable cannot be answered just by mechanically examining the software.
- What should this software do? (requirements, usability, safety)
- What should the software look like inside, so it is easy to fix and modify? (architecture, design, scalability, portability, extensibility)
- How long will it take to create? (estimation)
- How should we build it? (coding, testing, measurement, configuration)
- How should we organize the team to work efficiently? (management, process, documentation)
Tried-and-true methods that work for one team of programmers do not work for other teams
Exhaustive analysis of past programming projects may not produce a good estimation for the next
We should stop trying to prove fundamental results in software engineering and accept that the significant advances in this domain will be general guidelines.
In the same way, classical computer science is helpful to software engineering, but will never be the whole story. Good software engineering also includes creativity, vision, multi-disciplinary thinking, and humanity. This observation frees software engineering researchers to spend time on what does succeed -- building up a body of collected wisdom for future practitioners. We should not try to make software engineering into an extension of mathematically-based computer science. It won't work, and can distract us from useful advances waiting to be discovered.

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booktrade.info - Book Trade Announcements - Random House Group Launches New Social Network For Book Clubs

www.readersplace.co.uk

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A New Model for IT Demand Management

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In short, when it comes to supply and demand, IT is unduly focused on the supply side of the equation, or the how (project management, software development and managing physical assets like hardware and networks)—to the detriment of the demand side, or the what (capturing and prioritizing demand, assigning resources based on business objectives and doing projects that deliver business benefits).
Once projects have been delivered, the absence of rational demand management becomes even more acute. While you can usually count on business executives to obtain the funding to launch projects, the same is rarely true to fund the resulting applications after delivery. This is usually because the executive sponsor has either moved on (often as a result of the project's success—or failure) or is far less motivated to go and bat for operational funding, which doesn't have the same visibility and organizational rewards as launching a new project—especially when, as is usually the case, the magnitude of the ongoing funding was not part of the original business case.
So demand management is clearly the missing link in most IT departments. Yet any successful business model by definition has to be built on the effective management of demand as well as supply.
For those who believe in the myth of the sacrosanct "IT Annual Plan," remember it's just that—a myth. In the real world demand is coming in every single day, so the challenge is to capture that demand, both planned and unplanned, as early as possible, expose the high-level business justification and set up an ongoing dialogue between IT and its customers. This enables the management of a demand pipeline. An opportunity analysis on this pipeline, based on an appropriate scoring model, will give rise to an initial screening and validation process which will enable an idea to move down to next stage and become a project request. Typical examples of filtering criteria for a scoring model are expected revenue, expected cost reduction, regulatory compliance or operational improvements.

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Amazon.com -- News Release

Amazon publishing initiative.

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Manifesto < Killing the Buddha

Killing the Buddha insists that if religion matters at all it matters enough to be taken to task. We believe it’s high time for a new canon to be created, and that the Web is just the place to collect it. We refuse to accept the internet as a world wide shopping mall. We know intuitively it can be a sort of Talmudic cathedral, a tool of transcendence made of words. We’re here to build it. If the end result looks more like Babel than the City of God, so be it. Babel, after all, came close.

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Battle Stations - WSJ.com

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The Modern Library | 100 Best | Novels

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Application Platform Strategies Blog: SOA is Dead; Long Live Services

Original blog post from Manes... Nice graphic...

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SOA gets an obituary | InfoWorld | News | 2009-01-05 | By Paul Krill

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Brave New World: Our 2009 Predictions

7. Editorial / Production Content Development
We envisage that more and more publishers will review their antiquated development process and realise the opportunity benefits to be taken from digitising this. The key to success will be down to the implementation approach and managing the change programme. The old adage, ‘if a customer service clerk doesn’t like the system, you sack the clerk, but if and editor doesn’t like the system you sack the system,’ will still apply. Another important opportunity will be to pull the publishing business (content, context and rights) under one single digital process.

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