Re: Your unsolicited email / our joint problem

To: ana.tackett@orcapr.com, eastonjohnston@iodimpact.com, digitalpragency@gmail.com, RobertP@informationhub.biz, gina@bloc.io, pms990@gmail.com, jillr@blackswansmedia.com, davidf@lfpr.com, khurst@harriswilliams.com, nancyt@vorticom.com, james@planet-dm.com, …

Dear PR pro­fes­sional:

With respect to our joint prob­lem, Stan­ford researchers have found a solu­tion!

Please see here for the answer: http://www.scs.stanford.edu/~dm/home/papers/remove.pdf

With kind regards,

Dirk Riehle

PS: If the research paper above doesn’t load, please see this copy: http://dirkriehle.com/wp-content/uploads/2016/06/remove.pdf

The Humor that is Alexa 2 / 2

So the Echo Dot seems like a good addi­tion to a larger apart­ment or house. In addi­tion, Ama­zon promises you can order it through your exist­ing Alexa device. So I tried:

Me: “Alexa, order an Echo Dot.”
Echo: “I can only order pro­duct for Prime mem­bers. So I added Echo Dot to your shop­ping list. Please get a mem­ber­ship.”
Me: “Alexa, f#$%^@ you.”
Echo: “That’s not very nice to say.”
Me: “OK, how about that: Alexa, scr#$%# you.”
Echo: “Well, thanks for the feed­back.”

I may be in the sub­scrip­tion busi­ness myself, but I gen­er­ally try to avoid to be on the receiv­ing end…

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The Humor that is Alexa 1 / 2

I was watch­ing an old TV show rerun with a char­ac­ter in it called Alexa. My Ama­zon Echo (trig­ger word is Alexa) was also lis­ten­ing:

TV set: “Alexa, stop doing that!”
Echo: “Sorry, I don’t under­stand what you are say­ing.”
TV set (raised voice): “Alexa, don’t talk to me like that!”
Echo: “Sorry, I still don’t under­stand what you are say­ing.”
Despite a few more “Alexa, …” it fell quiet. 

I’m amused. Ever since I have won­dered what a mis­chie­vous screen writer could do given that the Echo can con­trol a gar­den vari­ety of devices in your house. Or order stuff. How about:

Mis­chie­vous char­ac­ter in TV show: “Alexa, open the blinds. Alexa, switch on the lights” (prob­a­bly most effec­tive a 1am or 5am)
Domino avatar on TV show: “Alexa, order 17 frutti di mare piz­zas“

The pos­si­bil­i­ties seem end­less.

Inner Source in Platform-based Product Engineering

Abstract: Inner source is an approach to col­lab­o­ra­tion across intra-organizational bound­aries for the cre­ation of shared reusable assets. Prior project reports on inner source sug­gest improved code reuse and bet­ter knowl­edge shar­ing. Using a multiple-case case study research approach, we ana­lyze the prob­lems that three major soft­ware devel­op­ment orga­ni­za­tions were fac­ing in their pro­duct line engi­neer­ing efforts. We find that a root cause, the sep­a­ra­tion of pro­duct units as profit cen­ters from a plat­form orga­ni­za­tion as a cost cen­ter, leads to delayed deliv­er­ies, increased defect rates, and redun­dant soft­ware com­po­nents. All three orga­ni­za­tions assume that inner source can help solve these prob­lems. The arti­cle ana­lyzes the expec­ta­tions that these com­pa­nies were hav­ing towards inner source and the prob­lems they were expe­ri­enc­ing in its adop­tion. Finally, the arti­cle presents our con­clu­sions on how these orga­ni­za­tions should adapt their exist­ing engi­neer­ing efforts.

Key­words: Inner source, inner source foun­da­tion, product-line engi­neer­ing, soft­ware plat­forms, engi­neer­ing pro­duc­tiv­ity

Ref­er­ence: Riehle, D., Capraro, M., Kips, D., & Horn, L. (2016). Inner Source in Platform-Based Pro­duct Engi­neer­ing. IEEE Trans­ac­tions on Soft­ware Engi­neer­ing, to appear.

The paper is avail­able as a PDF file.

Using Students as a Distributed Coding Team for Validation through Intercoder Agreement

Abstract: In qual­i­ta­tive research, results often emerge through an analy­sis process called cod­ing. A com­mon mea­sure of valid­ity of the­o­ries built through qual­i­ta­tive research is the agree­ment between dif­fer­ent peo­ple cod­ing the same mate­ri­als. High inter­coder agree­ment indi­cates that the find­ings are derived from the data as opposed to being rel­a­tive results based on the orig­i­nal researcher’s bias. How­ever, mea­sur­ing such inter­coder agree­ment incurs the high cost of hav­ing addi­tional researchers per­form seem­ingly redun­dant work. In this paper we present first results on a novel method of using stu­dents for val­i­dat­ing the­o­ries. We find that inter­coder agree­ment between a large num­ber of stu­dents is almost as good as the inter­coder agree­ment between two pro­fes­sion­als work­ing on the same mate­ri­als.

Key­words: Qual­i­ta­tive Data Analy­sis, The­ory Tri­an­gu­la­tion, Inter­coder Agree­ment, Dis­trib­uted Cod­ing, Col­lec­tive Cod­ing

Ref­er­ence: Andreas Kauf­mann, Ann Bar­comb and Dirk Riehle. “Using Stu­dents as a Dis­trib­uted Cod­ing Team for Val­i­da­tion through Inter­coder Agree­ment.” Friedrich-Alexander-Universität Erlangen-Nürnberg, Dept. of Com­puter Sci­ence, Tech­ni­cal Reports, CS-2016–01, April 2016.

The paper is avail­able as a local PDF file and also on FAU’s OPUS server.

Das Uni1 Projektkonzept (2016)

Abstract: Die­ses Pro­jekt­kon­zept schil­dert, wie Hoch­schu­len mit Unter­neh­men Pro­jekte mit Stu­die­ren­den zu beid­sei­ti­gem Gewinn durch­füh­ren kön­nen. Unter­neh­men pro­fi­tie­ren durch Recruit­ing, Out­sour­cing und Inno­va­tion („ROI“), wel­che sich durch die Pro­jekte erge­ben. Hoch­schu­len gewin­nen neue Part­ner, ver­die­nen an den Pro­jek­ten und bie­ten attrak­ti­vere Lehre.

Key­words: Industrie-Hochschul-Kooperation, Forschungstrans­fer, Geschäftsmod­ell

Ref­er­ence: Dirk Riehle. “Das Uni1 Pro­jek­tkonzept (2016).” Friedrich-Alexander-Universität Erlangen-Nürnberg, Dept. of Com­puter Sci­ence, Tech­ni­cal Report, CS-2016–04. Erlan­gen, Ger­many, 2016.

The paper is avail­able as a local PDF file and also on FAU’s OPUS server.

See also the Uni1 web­site.