KEYNOTES:

The Future of Testing - BJ Rollison, Test Architect at Microsoft

The challenges of testing software are much greater today as compared to developing software. But, to meet these challenges, the function of the software testing professional will need to increase and expand well beyond traditional roles. The skills and knowledge of software testers will evolve in order to design effective tests for complex systems and perform detailed analysis of data to provide qualified information to the project stakeholders. As Thomas L. Friedman states in The World is Flat: “And that is why the great challenge for our time will be to absorb these changes in ways that do not overwhelm people or leave them behind.” This keynote discusses some of the influences driving changes in software testing, some common problems in our discipline, and suggests ways we can meet our future challenges.

Investment Modeling as an Exemplar of Exploratory Test Automation - Cem Kaner, Director, Center for Software Testing Education & Research, Florida Institute of Technology.

Most of the activity in modern stock markets is programmed. In algorithmic trading, which accounted for over 60% of equity transactions in American exchanges last year, software decides what to buy and what price (and how much) and when to place the trades. Imagine testing one of these systems. You could focus on VERIFICATION—does the system correctly implement the model (does it make the trades the underlying model would make) and does it execute the trades correctly (placing the right orders, monitoring the results and recognizing errors). You could focus on OPTIMIZATION and PERFORMANCE—in a fiercely competitive marketplace, the software must quickly get data from the exchanges, interpret the data and get orders to the exchanges and it must do so under competition for resources (e.g. load) at the local system level, in the services the system relies on, and in the paths to the exchanges. You could focus on SECURITY—how vulnerable is the system to espionage or interference? And you can focus on VALIDATION—is this the right model? It doesn't help anyone (except your competitors) if you can reliably and quickly get the wrong trades to the exchange. You can probably do the basic verifications as regression tests, maybe even as manual regression tests, but the rest of these concerns require good tools, intense automation, and most of this testing should be exploratory.

Doug Hoffman and I started teaching techniques for automated ET in the late 1990's, calling them "high volume test automation." These techniques go after bugs that are virtually impossible to expose or isolate in manual testing. One of the challenges in teaching automated ET is the extent to which sophisticated testing relies on a deeper knowledge of the application under test. As I've worked with investment models over the past two years, I've realized that this is a type of application that can probably capture the interest of most of the people in our community and thus serve as a good foundation for explaining where I think the next generation of testing should be headed.

These are not new ideas. I have no desire to rebrand them and pretend that my clique of academics and consultants invented them. I first saw automated ET techniques in use in 1985; Hoffman was using some over 30 years ago. These ideas have old roots. My contribution is to make them a little more accessible, via better explanation and examples, with a little better cheerleading for ideas whose time is long overdue.

Closing keynote & Remarks - Hung Q. Nguyen, Chairman/CEO, LogiGear Corporation.

As we conclude the conference with new ideas and a fresh perspective, as well as recognizing more challenges awaiting us, Hung will share his thoughts on improving software testing efficiency. In that, he will discuss the various dimensions of efficiency, how we know (within our organization) where we are today, what is better and what we can do better tomorrow, and then set measurable and achievable goals.

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