How my Ph.D. Students Work With Supporting Students (Hint: Not Scrum)

As mentioned in a previous blog post, my Ph.D. students are often experienced software developers who take on the role of a chief programmer in the development of the software system supporting their research. In this work, at any point in time, each of my Ph.D. students is typically supported by 2-7 Bachelor and Master students who contribute to the system under development. Taking a long-term perspective, my Ph.D. students develop quality software rather than throw-away prototypes.

The chief programmer idea is key to making such work successful. While I usually conceive and direct the research, the size of my group has led me to let my Ph.D. students take care of any actual development themselves. (Usually…) In this role, as the chief programmer, they become the central point of coordination and integration of engineering work. In academia, this is a necessity, because an engineering dissertation is typically a multi-year project, while final thesis students, the main source of junior programmers supporting the chief engineer, are only around for six months. Thus, the chief programmer becomes the central technical hub and provider of sustained knowledge of the system under development.

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Chief Programmer Teams Alive And Well in Academia

According to Wikipedia, “a chief programmer team is a programming team organized in a star around a “chief” role, granted to the software engineer who understands the system’s intentions the best. Other team members get supporting roles.” Amusingly, this set-up is alive and well in academia, and for good reason. At least my research group is using it and it works well for us.

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Scrum’s Product Vision vs. Project Mission

As noted previously, Scrum uses the term product to mean artifact. This is fine, as long as the user of Scrum is a software vendor, developing a product for a market. It is confusing, however, if the user is a consulting firm, performing a custom project for a client. If you are a consulting firm, you are not delivering a product, and every time you hear product, you need to think artifact.

The confusion is worst when we talk about a product vision. As always, there are many competing definitions and confused ones at that, but we can safely assume that a product vision is at least a particular type of vision. About a vision, by definition, we know that it is time-less. It describes an abstract future state that we want to achieve, but never actually can reach. As such, a vision serves as a guiding north star for the decisions we make about on-going work. IBM’s vision is (shortened) “client success”, SAP’s is “improved economy”, etc. Any number of management books expound on what a vision is so you can read more there.

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How Project vs. Product Confuses Agile Methods Terminology

In a previous blog post I noted how the terms project and product are being confused in open source. However, it is agile methods, specifically Scrum, where it gets really bad. To recap: A project is a human undertaking to create an artifact. A project, by definition, has a start date and an end date. A product, in contrast, is an artifact (not an undertaking) that is born but typically has no planned end date. Most vendors, selling products to a market, hope they can do this forever.

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How Project vs. Product Confuses Open Source Terminology

The terms project and product are used with continued confusion. Both open source and agile methods are particularly bad offenders, leading people astray. Adapted straight from the textbooks:

  • A project is a human undertaking with the goal of creating an artifact. Its life-cycle is determined by a start date and an end date.
  • A product is a human-made artifact for a market of customers with an open-ended llfe-cycle. It is born with no end date in sight.

Not always, but typically, a project is used to create a custom artifact, while a product is (by definition) made for a market, that is, many different customers.

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Internal Component Marketplaces vs. Transfer Pricing of Inner Source

I was recently asked why I argue against company-internal marketplaces for software components yet emphasize the need for pricing components that cross company boundaries within the same holding company (also known as transfer pricing). The answer is simple: Setting up an internal marketplace is a managerial choice and pricing the movement of code (IP) across company boundaries is a taxable event that you need to deal with: It is not a choice.

Let me take it in steps.

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Open Source License Compliance in Free Mobile Apps

Open source license compliance is not for the faint of heart. Among many things, a company needs to tell the recipients of a distribution which open source software is used in their products. In the case of mobile apps, free or not, the user is the recipient and the app is the distribution. Downloading an app from the app store makes me a user. Lets see what we can learn about open source using an example app.

The following four screenshots show how I made my way from finding an app through installing and starting it. I could not find any information about the distributed open source code along the way.

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Some Argue That Dual-Licensing in Commercial Open Source Indicates a Lack of Ability to Provide Superior Service

This is obviously wrong. The use of dual licensing and the ability to provide superior service for open source are unrelated forms of competitive advantage, and without further circumstances, a business should exploit both advantages. Let me explain.

Dual (or multiple) licensing is a strategy, in which a company develops software, releases it under an aggressively reciprocal (“viral”) license like the AGPLv3 and then offers commercial customers who don’t like the open source license the option to acquire a proprietary license for the software. This is a positional advantage of the vendor, because it is the only company that can apply this strategy (courtesy of being the copyright holder). While I mix things up a bit, it is closely related to what’s been called the open core model or single vendor open source. To maintain this positional advantage, vendors need to follow the commercial open source intellectual property rights imperative.

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The Dancing Robot Dog: Magic Trick or Real Artificial Intelligence?

You may have seen the video below by Boston Dynamics. It shows a robot dog dancing to Uptown Funk by Bruno Mars. It is fun and funny to watch, but people also expressed serious worries about robot inroads into human behavior. However, there is no explanation by Boston Dynamics and it is not at all clear whether this is a simple magic trick created to fool the onlookers or real artificial intelligence (AI) progress.

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