Luca de Alfaro in the News

At CONCUR 2007, I learned that our colleague and member of WG1.8 Luca de Alfaro has recently hit the news for his work on an evaluation of trust in contributions to Wikipedia. (See Demo: Coloring the text of the Wikipedia according to its trust.) Luca's work is based on the idea of colouring the text of Wikipedia articles according to a computed value of trust. The trust value of each word of a Wikipedia article is computed as a function of the reputation of the original author, as well as the reputation of all authors who subsequently revised the text.

This work of Luca's was mentioned in the Washington Post (I cannot locate the link anymore), the Jerusalem Post, ACM TechNews and SFGate.com amongst others.

Luca will also be the PC chair for FOSSACS 2009 in York, but this will give him less media exposure :-)

Nadia Busi (1968-2007)

During the excursion for CONCUR 2007, while visiting the Arrábida Convent, we were hit by the sad news that our colleague and friend Nadia Busi had suddenly passed away the night before. A paper having Nadia as one of the authors had been presented at the conference just before we set off for the excursion.

Our community has lost a very active and creative researcher, a woman who could be an example for others to follow and, above all, a very kind human being.

An obituary for Nadia, written by Roberto Gorrieri, will appear in the October issue of the BEATCS. You can read it here.

"We are such stuff
As dreams are made on, and our little life
Is rounded with a sleep."
(Shakespeare, "The Tempest")

Guest Post from Jorge Perez

I received this contribution from Jorge Perez, and post it with pleasure.

I have found your reports on the WG1.8 Workshop extremely enlightening. I am specially impressed by the invited speaker's opinions on the role of probabilistic/stochastic modeling. In my opinion, and having little experience on the theoretical side of the topic, their positions are, at the very least, certainly a matter for debate.

The topic of the workshop also made me remember of the spirit of my former research group in Colombia. For many reasons, the group (called AVISPA, see http://avispa.puj.edu.co/) is interested essentially in applied concurrency. This means thinking at the same time in theory and usable applications, beyond prototypes. Perhaps the most successful application area has been Computer Music.
In collaboration with the French Acoustics/Music Research Institute (IRCAM), AVISPA has designed and implemented formal, concurrent languages to assist music composers in their duties. I know this is not properly an 'industrial application' but it could be an example of how concurrency theory can be fruitfully applied.

AVISPA has recently launched a project on applied concurrency: it is
called REACT (see
http://cic.puj.edu.co/wiki/doku.php?id=grupos:avispa:react), and it aims at consolidating our concurrency languages in several application areas, including security, systems biology, computer music (or more generally: multimedia semantic interaction).

Sorry for the long post, but the topic is very interesting for me and I wanted to share this (perhaps unusual) approach to applied concurrency.

Some Answers By the Workshop Speakers

In a previous post, I listed the questions that the attendees at our CONCUR 2007 workshop raised to the invited speakers and panel members. I also promised to pen down my recollections of their answers. Here they, hoping that I won't misrepresent the opinions of these colleagues too much. I am sure that they will correct me if I inadvertently do so. Anything I write below should be taken with a huge pinch of salt :-)

What is the role/importance of real-time in modelling? Does industry want dense-time or discrete-time models?

Kim G. Larsen (KGL): The vast majority of computing systems in operation today are embedded. Proper modelling and analysis of the behaviour of embedded systems requires time. However, industry does not really seem to care whether the model of time used in the models is discrete or continuous. When analyzing embedded systems, quantitative analysis techniques are needed and I expect that stochastics will play an increasing role in the future.

Jan Friso Groote (JFG): Basically, industry do not know what they want and there is little point in chasing their ever-changing needs. Concrete modelling and analysis of computing systems should be based on a uniform calculus, which is rich enough to model the problem scenarios at hand. As far as real-time is concerned, it should be expressible in the uniform calculus.

How does one involve small- and medium-size companies in collaborations with concurrency theoreticians/practitioners? Does "company size" matter?

Both JFG and KGL reported on several examples of interaction with industry where there seemed no relation between "size" and the success of the interaction. Kim described a successful collaboration on testing of GUI applications with a one-person company having basically no technological expertise. This was compared with the collaboration with Bang and Olufsen, which was a failure despite the resounding success of their first cooperation.

Jan Friso highlighted the successful cooperations with industry within the Laquso project. (See here for more information.)

Hubert Garavel (HG) stated there are three necessary conditions for a successful collaboration with industry. The company should have

1. a strong interest in quality,
   
2. a lot of money and
   
3. a formal modelling group in house.
   

These criteria are difficult to find in a small- or medium-size company. In particular, the third criterion above is useful because it opens up the possibility of embedding a company engineer within the academic research group.

Is there any need for stochastic and probabilistic modelling in applications? More pointedly, have you met an example that you could not model because your tool does not support stochastic or probabilistic phenomena?

There seemed to be a general opinion here that probabilistic modelling is nice, but not necessary. More precisely, none of the speakers had yet met an example that they could not model adequately because their models and tools do not permit stochastic or probabilistic modelling.

JFG stated that he wants to work on research topics that can have applicability in real-life scenarios. He wants to have interaction with industry mainly as a way to learn what are the good/bad aspects of his modelling language and his tools. He feels that one should push for the use of the same model for verification and performance evaluation. (I have a vague recollection that this opinion was also shared by Kim.)

How can we, as a community, foster the building of industrial-strength tools based on sound theories?

The general feeling amongst the panelists was that our community does not have the infrastructure to support tooling efforts. HG pointed out how the situation is better in France, where the development of tools and languages is supported and recognized by institutions like INRIA. (My note: In hindsight, this is reflected by the success of long-term efforts like those that led to Esterel, Coq and CAML, amongst others.)

The panelists suggested that conferences and journals should be keener to accept tools and case studies as refereed contributions on a par with papers. JFG pointed out that Science of Computer Programming has now a track devoted to "expositions on implementations of and experiments with novel programming languages, systems and methods." The journal's web page also states that "It must be emphasized that papers describing new software tools of relevance to SCP are welcome under the strict condition that the source code of the tools is open." KGL also stated that the TACAS conference series was initiated precisely to give more visibility to tooling efforts in our community.

For a one-slide viewpoint on the economics of tool development look at slide 72 of Kim's presentation at the workshop.

What has concurrency theory offered industry so far? What are the next steps that the concurrency community should take in order to increase the impact of its research in an industrial setting? And what are future promising application areas for concurrency research?


JFG: Theory does not have much to offer to industry. We should probably view concurrency theory as a nice mathematical theory that need not have any real-world application.

As for what is it that we can do as a CONCUR community to assist in the work on tools, JFG's answer is to organize that as many students are being taught their use and effective application as possible. One of the biggest problems that we are facing is that far too few people in industry understand what formal methods and their tools can effectively bring to industry. To be on the safe side, they do not see where the techniques are effective and what they offer. They however understand that there are other pressing needs to invest time in.

If we teach formal methods we should teach the most advanced ones that the students can swallow. If they understand the advanced methods they can apply the more straightforward techniques. Of course the reverse does not hold. Don't teach them UML and expect them to understand mCRL2. But if you teach them mCRL2, they will not have any conceptual difficulty to apply UML.

KGL: We should make our techniques fit into the whole system-development process. We should also make sure that existing model-based tools that are already in use by industry have much stronger semantic foundations.

HG: Our community is in trouble! The model of concurrency that is prevalent is industry is Java-like (threads and shared variables). Our foundational beliefs are exotic for industry and message-passing, as used in our process calculi, is not the order of the day. Our major challenge is in pushing the clean model of concurrency we like. Every computer science department in every university should play its part in achieving this aim. Education is one of our best weapons to make industry accept our models and the techniques based upon them.

Concurrency Column for October 2007

I have just posted the piece that will appear in the concurrency column for the October 2007 issue of the BEATCS. The article, authored by Sergio Maffeis, is entitled Dynamic Web Data and Process Calculi and reports on the use of concepts and techniques from process calculi in the study and analysis of dynamic data.

Enjoy it.

Rance Cleaveland's Answers

It is a great pleasure for me to post some answers by my old mate Rance Cleaveland to the questions raised at the CONCUR workshop. Thanks to Rance for sharing his experience with us!


What an interesting workshop; I deeply regret not being able to attend.

At Luca's gentle suggestion ;-) I thought I would have a go at questions he posed at the end of his post.


What is the role/importance of real-time in modelling? Does industry want dense-time or discrete-time models?


In my experience with Reactis, my company's testing and verification tool, Reactis customers absolutely need real-time support. This is due to their applications, which are in automotive and aerospace and develop embedded control software. The most widely used commercial modeling languages (Simulink, Stateflow, SCADE) also include real-time as an intrinsic part of their semantics.

Ironically, given the sound and fury in the academic community, the industrial people I have interacted with for the most part do not care whether time is discrete or continuous. Sometimes, I have encountered customers who want to do hybrid-systems style modeling, and for these people continuity is important.


How does one involve small- and medium-size companies in collaborations with concurrency theoreticians/practitioners? Does "company size" matter?



Regarding SMEs (small- and medium-size enterprises ... a common acronym among US policymakers): I think the best way to involve them is via projects funded by third parties (governments, or a large partner). SMEs generally don't have the overheads to support "blue-sky" research, and their investment-return horizons are necessarily of shorter duration. At both Reactive Systems and Fraunhofer, our concurrency-oriented SME collaborations have either involved collaborations on government research grants or project work on behalf of larger customer. In the latter cases, it was important that we work in commercial notations (e.g. Simulink) rather than research-oriented ones.

Large companies do have resources to put into more basic research, but there is another phenomenon to be aware of: researchers in these companies often view outside researchers as competitors for their internal research funds. So collaborations with these organizations are highly dependent on the personal connections between company and non-company researchers. So-called "business unit" personnel are often the easiest to deal with, but in this case there needs to be a clear, typically short-term, pay-off to them for the collaboration.


Is there any need for stochastic and probabilistic modelling in applications? More pointedly, have you met an example that you could not model because your tool does not support stochastic or probabilistic phenomena?


We support simple probabilistic modeling in Reactis in the form of probability distributions over system inputs that we sample when creating tests. This feature, however, is almost never used by our customers. The reasons for this mostly boil down to a lack of training these engineers receive in stochastic modeling and control, which in turn is tied into the lack of good (or maybe standard) theory for stochastic differential equations.

More precisely, the engineers in automotive and aero that I've dealt with are usually mechanical or electrical engineers with backgrounds in control theory. The feedback control they use relies on plant models (i.e. "environments") being given as differential equations, which are deterministic. The plant models they devise for testing their control-system designs often have parameters that they tweak in order to test how their ideas work under different conditions.

These engineers talk in the abstract about how useful it would be to develop analytical frameworks for probabilistic plants, but tractable theories of probability spaces of differential equations are unknown, as far as I can tell.


How can we, as a community, foster the building of industrial-strength tools based on sound theories?


To have an industial following, tools have to work with languages that industry uses. For most research tools this is a problem, because the input languages are typically invented by the tool developers.

I see two possibilities. One is to work on commercial languages such as Simulink. These languages are often a catastrophe from a mathematical perspective, but they also usually contain subsets that can be nicely formalized for the purposes of giving tool support. If tools have a nice "intermediate notation" into which these cores can be translated, then this offers a pathway for potential industrial customers to experiment with the tools.

The second approach is to become involved in standardization efforts for modeling languages. UML 2.0 has benefited to some extent from concurrency theory, but there are many aspects of that language that remain informal and imprecise.


What has concurrency theory offered industry so far? What are the next steps that the concurrency community should take in order to increase the impact of its research in an industrial setting? And what are future promising application areas for concurrency research?


I think the best way to answer first question is to "trace backward" from commercial tools / modeling languages that have some basis in concurrency. Such tools would include those based on Statecharts (Stateflow, STATEMATE, BetterState); others based on Message Sequence Charts (Rational Rose, other UML tools); the French synchronous-language tools (SCADE, Esterel); tools that include model checkers (the EDA = "electronic design automation" industry); tools that use model-checking-base ideas for other analyses (Reactis, DesignVerifier).

Unfortunately the process-algebra community has had relatively little impact on commercial tool development. This is not due to shortcomings in the theory, in my opinion, but in the inattention that compositionality continues to receive in the (non-research) modeling community. In my experience, event-based modeling is also relatively uncommon, at least in auto and aero: sampling of "state variables" is the preferred modeling paradigm.

I personally would like to see work on semantically robust combinations of specification formulas (e.g. MSCs + state machines, or temporal logic + process algebra) and related tools; theoretically well-founded approaches to verifying systems that use floating-point numbers; and compositional, graphical modeling languages (lots of work done already, but still no commercial interest).

Moshe Vardi's Answers

Moshe Vardi has kindly sent me some brief answers to the questions I posted yesterday. I post them here in order to foster further discussion, and thank Moshe for his contribution.

• What is the role/importance of real-time in modelling? Does industry want dense-time or discrete-time models?

Moshe: Complex hardware designs today are locally synchronous, but globally asynchronous. Using multiple clocks to specify temporal properties is very
important, but I personally saw, so far, no application that required
dense-time reasoning. (Perhaps timing analysis of circuits requires dense
time?)

• How does one involve small- and medium-size companies in collaborations with concurrency theoreticians/practitioners? Does "company size" matter?

Moshe: Large companies can afford to think longer term and invest in internal/external research. This is quite harder to do with small companies, which typically looks for immediate solutions to their problems.

• Is there any need for stochastic and probabilistic modelling in applications? More pointedly, have you met an example that you could not model because your tool does not support stochastic or probabilistic phenomena?

Moshe: I have not seen it so far, but I do hear people starting to talk about probabilistic behavior of computer circuits. Perhaps we'll see a growing need for stochastic modeling in a few years.

• How can we, as a community, foster the building of industrial-strength tools based on sound theories?

Moshe: Academia can rarely build industrial-strength tools. Academic tools are
often the work of a single graduate student. Industry can put several PhD-level people on a single project.

• What has concurrency theory offered industry so far? What are the next steps that the concurrency community should take in order to increase the impact of its research in an industrial setting? And what are future promising application areas for concurrency research?

Moshe: IMHO, the biggest successes of the concurrency-theory community, broadly
conceived, is model checking and the development of synchronous languages. At the same time, many research direction in concurrency theory, such as process calculi and bisimulation theory have had fairly minimal impact. The theory community is often attracted to research based on its theoretical appeal, which does not always correlate with its industrial applicability. This does not mean that industrial applicability should be the guiding principle of research. Nevertheless, it would be worthwhile to pause once in a few years and examine the potential applicability of
theoretical research.

Report on the WG1.8 Workshop at CONCUR 2007---Part 1

Preface

As you may know, Jos Baeten, Wan Fokkink, Anna Ingolfsdottir, Uwe Nestmann and I organized a Workshop on Applying Concurrency Research in Industry, co-located with CONCUR 2007 in Lisbon, on behalf of WG1.8. The workshop was held on the afternoon of Friday, 7 September, and ran concurrently with the last two sessions of the main conference. Despite the competition with CONCUR, we had about 25 participants at the workshop, including several members of the working group. I think that this was a rather decent level of attendance for a "strategic event".

In this post, for the benefit of the WG members and of the community as a whole, I'll try to summarize the main discussion points that were raised during the presentations at the workshop and the ensuing panel discussion. I will also try to recall some of the questions that the audience asked the panel members. I hope that some of blog readers will want to contribute their opinion on these points and give their own answers to those questions themselves.

The organizers of the workshop will use all of the contributions that they'll receive in putting together an article for the concurrency column of the BEATCS.

Report on the Invited Talks

Note: I encourage the speakers to correct anything they said that I may have misinterpreted or misrepresented. I take full responsibility for any error I might have made in relaying the gist of the invited talks, and I'll be happy to post corrections and further comments. This is meant to be a live repository.

The workshop began with four invited presentations delivered by Hubert Garavel, Vincent Danos, Kim G. Larsen and Jan Friso Groote.

Hubert gave an overview of his twenty-year work on the CADP tool set, which is the oldest concurrency-theoretic tool still in activity. A thread underlying his work in what he called "applied concurrency theory" is that one must push the main results of our research area to industry and that this is only possible with the development of strong tool support for our methods. Hubert said that one of his design principles has been to restrict the tool's functionality for efficiency reasons, and that elegant semantics and efficient execution are two separate (at times conflicting) issues.

I have a note to the effect that, during Hubert's presentation, somebody (possibly Hubert himself) said that a lot of code doing bisimulation minimization has been lost over the years. We simply have not been consistent enough in preserving some of our earlier tooling efforts for the present generations of developers. Jan Friso said that current bisimulation minimization algorithms do not scale up to the size of the systems that are currently being analyzed, and asked whether it would be appropriate to rekindle research and implementation efforts on efficient and scalable bisimulation algorithms.

Earlier that day, Vincent had delivered an inspiring tutorial on his work in doing rule-based analysis of biological signalling. Listening to his tutorial, I was left with the impression that he is really having an impact in the life sciences, and that experimental biologists might very well use his tools based on concurrency-theoretic ideas. At the workshop, Vincent presented another way in which concurrency-theoretic ideas can help experimental biologists in their work. Experimental biology has a huge knowledge representation problem. (Vincent mentioned that there are two papers published in that area each minute!) In his opinion, experimental biologists can/should

• use concurrency-inspired languages to express biological understanding and
  
• display this information in a wiki-type system.
  

This will allow them to construct models systematically and to simulate them (exploiting the executable nature of concurrency-theoretic models) well beyond what is possible today by means of experiments.

Kim's talk was based on his experience with the ten-year development of the Uppaal tool, and reported on the knowledge transfer activity, which is part of his involvement in CISS. Apart from surveying the development of Uppaal and its recent offsprings, Kim's talk sent out the following general messages to the audience.

• Tools are a necessary condition for the successful transfer of concurrency-theoretic ideas in industry. Tool development is labour intensive, and one needs the sustained effort of many people over many years to produce good software tools.
  
• Academic courses offered to students and to industry practitioners play a key role.
  
• Concurrency researchers should try and target different communities of potential users. One never knows where successful applications are going to stem from.
  
• A good beginning is useful! Being able to start with a success story may lead to further successes and a long-term collaborations. However, Kim warned against assuming that a good beginning is a guarantee of a good ending, and recounted the story of the Aalborg collaboration with Bang and Olufsen, who disappeared from sight after Klaus Havelund, Arne Skou and Kim found and fixed a bud in one of their protocols. See here.
  
• The success of CISS shows that several companies are very interested in applying concurrency-theoretic ideas and tools because this reduces time to market and increases the quality of their products.
  
• The impact of one's work on the application of concurrency-theoretic research in industry is not always directly proportial to the amount of effort one puts into the work itself. Kim gave the example of the synthesis of control software controlling the temperature and humidity in an actual pig stable in Denmark. This software was synthesized using Uppaal Cora in a short time and is actually running to the satisfaction of its customers :-)
• Finally, Kim called for an expansion of the use of concurrency theory. We should link our work to testing, optimization etc. and embed it into standard software engineering methodologies, which are familiar to practitioners.
  

Jan Friso presented an overview of the mCRL2 tool set, and gave a demo of several features of the system. He stated his belief that proving the correctness of systems by hand gives one understanding that mere button-press model-checking does not yield. However, one needs tools to transfer knowledge to industry and to validate one's manual verifications. He also shared Hubert's belief that the initial emphasis on abstract data types in CADP and muCRL2 was a mistake, but that formalisms supporting data are necessary in applications. One of Jan Friso's messages was that high-performance in tools is underestimated, and that achieving it requires a lot of subtle work. Jan Friso also stressed the importance of teaching courses to our students that involve modelling and analysis of real-life industrial case studies. In that way, when students go and work in industry they will know that there are effective modelling languages and tools that they can use efficiently to check their designs before implementing them. He also stressed the importance of visualization tools.

Some Questions to the Speakers

Here are some questions that were addressed to the speakers during the panel discussion, in no particular order. I encourage readers of this report to post their own answers and further questions as comments to the post. Later on, I will post the answers from the panel members as I recall them.

• What is the role/importance of real-time in modelling? Does industry want dense-time or discrete-time models?
• How does one involve small- medium-size companies in collaborations with concurrency theoreticians/practitioners?
• Is there any need for stochastic and probabilistic modelling in applications? More pointedly, have you met an example that you could not model because your tool does not support stochastic or probabilistic phenomena?
• How can we, as a community, foster the building of industrial-strength tools based on sound theories?
• What has concurrency theory offered industry so far? What are the next steps that the concurrency community should take in order to increase the impact of its research in an industrial setting?

I hope that you will contribute your own questions to the above list and share your answers with the rest of the community via this blog. I will soon post some of the answers given by our panel at the workshop.

Addendum 14/9/2007: After I wrote this post, it occurred to me that the workshop discussion may have given the impression that industrial impact can solely be achieved by means of tools and joint case studies. Moshe Vardi's work on specification languages like ForSpec on the other hand indicates that the development of theoretically sound and clean specification languages that are actually used by industry is another area in which in the community can (and I believe should) have an impact.
I hope I can quote Moshe as saying
"In fact, I believe that much of my industrial impact has been achieved through the development of clean and useful theory."