Firenxis

Manifesto for Agile Software Development

We are uncovering better ways of developing
software by doing it and helping others do it.
Through this work we have come to value:

Individuals and interactions over processes and tools
Working software over comprehensive documentation
Customer collaboration over contract negotiation
Responding to change over following a plan

That is, while there is value in the items on
the right, we value the items on the left more.

Kent Beck
Mike Beedle
Arie van Bennekum
Alistair Cockburn
Ward Cunningham
Martin Fowler
James Grenning
Jim Highsmith
Andrew Hunt
Ron Jeffries
Jon Kern
Brian Marick
Robert C. Martin
Steve Mellor
Ken Schwaber
Jeff Sutherland
Dave Thomas

© 2001, the above authors
this declaration may be freely copied in any form,
but only in its entirety through this notice.

Embrace change!  Photo credit

by Mark Hendrickson, on TechCrunch

In a recently published patent, Google describes a vision for an open wireless world, one in which mobile devices (and smartphones in particular) are no longer married to particular cellular service providers.

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The Google patent for “Flexible Communication Systems and Methods” contends that cellphone users should also have the freedom to connect through various networks and methods, and that the communication service they choose at any particular time and location should be determined by competitive market forces.

The idea is that you could, for example, make phone calls and browse the internet on your smartphone via WiFi when at home, Verizon when downtown, and perhaps AT&T when out in the countryside. You’d base your decision on both pricing and quality of service, with the quality of coverage in your current location playing a major role.

Full article: Google’s End Run Around the Wireless Carriers, via TechCrunch

The following is a digested excerpt from the book “Scaling Software Agility” by Dean Leffingwell. Read the complete chapter here. Order the book via Amazon here.

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Throughout the 1980s and into the 1990s, most DoD projects were mandated to follow a waterfall cycle of development as documented in the published standard DoD STD 2167. A report on failure rates in one sample concluded that 75 percent of the projects failed or were never used [Larman2004]. Consequently, a task force was convened. Chaired by Dr. Frederick Brooks, a well-known software engineering expert, the report recommended replacing the waterfall with iterative and incremental development:

DOD STD 2167 likewise needs a radical overhaul to reflect modern best practice. Evolutionary development is best technically, it saves time and money.

Statistical evidence and several authors’ experience [Larman2004],[Boehm1988],[Tomas2001] leads to conclude that the waterfall model does not work. By looking deeper into the assumptions of the waterfall model, it is possible to understand why it fails.

ASSUMPTIONS UNDERLYING THE WATERFALL MODEL

In retrospect, it appears that we made at least four key assumptions with the model that simply turned out to be incorrect:

1. There exists a reasonably well-defined set of requirements if we only take the time to understand them.
2. During the development process, changes to requirements will be small enough that we can manage them without substantially rethinking or revising our plans.
3. System integration is an appropriate and necessary process, and we can reasonably predict how it will go based upon architecture and planning.
4. Software innovation and the research and development that is required to create a significant new software application can be done on a predictable schedule.

Let’s look at these assumptions in light of what we have learned over the last few decades of building enterprise class systems.

Read the rest of this entry »

At Firenxis, we’ve spent quite a lot of time analyzing the problems of Quality Assurance.

Quality Assurance: Why?

In these times, everybody can give away lots of services, to lots of people, but not everybody can do it the right way. What’s even worse, it’s not easy to know if you are giving a good service to your customers. Whether you are a mobile operator selling ringtones, a bank, or a retailer selling flowers, you know the uptime is critical.

Failures are unacceptable. Always. You do not expect your barista at the local Starbucks to take your order, take the money, give you the change, and then hear “We cannot complete your request at this moment. Please come back later”. Imagine how frustrating that’d be. Imagine how frustrating it IS for YOUR customers, when a machine displays those words on a screen.

In an era of fully remote services, most interaction with customers is through machines. When a transaction fails on your website, some (if not all) of these take place:

• You do not fulfill your customer’s needs.
• You lose a sell.
• Your customer leaves frustrated.
• Your customer loses confidence in your service.
• Your customer loses confidence in your brand.
• You fail in your company’s mission.

Do our clients receive a good service?

This is a big question, that’s been driving our research for a long time: Are your customers getting a good service? How do you know? Is it possible to know? If you don’t know that answer… will you just hope that your customers receive good service, based on income figures? are you willing to address quality problems ONLY after your income is affected? if so, how long it would take you to figure that out? are you sure those problems aren’t taking place now?

We can work together in order to answer these questions.

Some problems we’ll face

As we’ve seen, there are tricky questions to answer. We want to be in the shoes of a customer, experience your service, and get a quantifiable qualification of your service, week to week, or even minute by minute. In other words, we want to measure the quality.

Often quality is the sum of all the organization efforts. It is clear that customers perceive the services as a whole, and a failure in one organizational unit could detriment overall service.

We’d also want to analyze how much quality influences in your income. Some services might be more sensitive to quality than others. Efforts could be much more effective when applied to the real problem zone.

Our research

At Firenxis we have assessed these problems and we can offer innovative solutions based in automatic customers simulation, quality metrics and resulting quality data analysis. We are commited to solve our customers problems of quality assurance, by using our tools and knowledge, or by creating new tools and knowledge. We can bring this until now hidden information to the light, and help you fulfill your customers expectations.