Keeping Continuous Deliveries Safe, by S. Vöst and S. Wagner
Link to article: https://arxiv.org/pdf/1612.04164v1.pdf
One of the challenges in introducing Agile software development into safety critical systems engineering is the ability to secure the safety properties. A number of solutions exist to that challenge, none of them successfully adopted in commercial product development, though. At least to my best knowledge.
The authors of this article propose a way of addressing this challenge by continuous safety builds. A good thing is the fact that this is in the context of automotive software development, although still in the idea phase. Hope to see more of this kind of research soon!
Abstract (of the article, quoted directly from the source):
Allowing swift release cycles, Continuous Delivery has become popular in application software development and
is starting to be applied in safety-critical domains such as the automotive industry.
These domains require thorough analysis regarding safety constraints, which can be achieved by formal verification and the execution of safety tests resulting from a safety analysis on the product. With continuous delivery in place, such tests need to be executed with every build to ensure the latest software still fullfills all safety requirements. Even more though, the safety analysis has to be updated with every change to ensure the safety
test suite is still up-to-date.
We thus propose that a safety analysis should be treated no differently from other deliverables such as source-code and dependencies, formulate guidelines on how to achieve this and advert areas where future research is needed.
I’ve recently done a personal mobility project with Volvo Cars (www.volvocars.com), which was a fantastic experience. I managed to be on Volvo’s site one day a week and developed the course for them — actionable dashboards:)
Here is a short movie about this collaboration, done with the colleagues at Volvo Cars, courtesy of Chalmers.
Link to vimeo
Quite recently I’ve reda one of the books by Daniel H. Pink – “Drive” – which describes what motivates us in general, but in particular in the areas where creativity and research.
In my opinion the ideas of motivation 3.0 are highly applicable for our students. In particular the ability to provide our young colleagues with the ability to become intrinsically motivated to gain the knowledge. We need to understand how to provide them with the “flow” types of task – something that will let the students feel that the task is challenging, but not too difficult.
In the next “software quality” course some of these ideas will come to existence.
We’re starting to take up some online trainings for measurement. The first one is about ISO 15939 and its measurement information model.
Go to the video at GU play: Measurement information model
Towards the end of the year I’d like to make a small reflection on Agile software development. It’s been discussed for a number of years now, yet the evidence of bringing measurable results is rather scarce. Here is one article from Åby Academy in Finland which studies a transformation of a large company to Agile: https://www.researchgate.net/profile/Marta_Olszewska_Plaska/publication/280711876_Did_it_actually_go_this_well_a_Large-Scale_Case_Study_on_an_Agile_Transformation/links/55c1d7ea08aeb28645819d3f.pdf
Studied case: Ericsson
Size: ca. 350 people
Product: roughly 10 years old
Languages: RoseRT, C++, Java
Summary of results: Agile software development provided more features (5x) and faster (60%).
What I like about the paper is that it provides the measurement before the transformation, DURING the transformation and after. Very interesting reading!
In the recent years we’ve seen a lot of discussions and good things about cloud computing – sharing platforms (PaaS), services (SaaS) and software thus optimizing the usage of computer resources.
This sharing of resources is important for making the software sustainable, and helps the companies to focus on what their business is about rather than on their IT infrastructure.
Measurement programs are no different – they are often a strategic value for companies, but they are not really something the companies want to spend their R&D budget for (at least not directly). So, how do we make it happen?
Well, we could use the same approach as in SaaS and PaaS and define MaaS (Measurement-as-a-Service) where we can reuse the knowledge across organizations and minimize the cost for working with the software measurement initiatives.
We’ve tried this concept with one of our industrial partners – Ericsson – and it seems that it works very well. You can read more about it in this article.
And the picture below explains a bit how this works.
Dashboards and all kinds of radiators are very popular in industry now. They allow the companies to disseminate the metrics information and to find the right way of visualizing the metrics.
In a recent article written together with Ericsson and Volvo Cars we have explored how to find the right visualization and we developed a model for choosing the dashboard – http://gup.ub.gu.se/records/fulltext/220504/220504.pdf.
The method quantified a number of dimensions of a good dashboard and provides a simple set of sliders that can be used to select the right visualization. The companies in the study have found it to be a good input to the understanding of what the stakeholders want when they say “dashboard”.
In the next steps we’re currently working on defining a quality model of KPIs – Key Performance Indicators. The first version has shown that it allows the companies to reduce the number of indicators by as much as 90% by finding the ones which are not of good quality.
In our recent work we have explored the possibility of validating that a measurement program is robust. We have worked with seven companies within the software center to establish a method and evaluate it. The results are presented in a newly accepted paper “MeSRAM – A Method for Assessing Robustness of Measurement Programs in Large Software Development Organizations and Its Industrial Evaluation” to appear in Journal of Systems and Software.
In short the method is based on a collecting the evidence that a measurement program contains elements which are important for the program to be able to handle changes. For example whether a measurement program has a dedicated organization working with it and whether the entire company is able to utilize the results from the measurement program.
The method is similar to the stress-testing of banks, so popular in the last decade.
The next step in our research is finding out which metrics the companies should use to assure the long-term robustness of the measurement program. stay tuned!
I’ve read a very interesting article in one of the recents IEEE Software magazines by Darja Smite, Fabio Calefaro and Claes Wohlin: http://www.computer.org/cms/Computer.org/ComputingNow/issues/2015/08/mso2015040026.pdf
The authors look critically at the body of knowledge in the area trying to find evidence of the cost savings. The results are that the evidence is not in the published articles. Does that mean that it is not possible to publish about it? or does it mean that there is no real evidence and the companies make decisions based on the “gut-feeling”?
It will be interesting to observe what happens with the body-of-knowledge on the topics in the longer run.
In our previous studies we’ve used simple summation when aggregating complexity measures. The complexity measures are usually calculated on function level erectile dysfunction and aggregated on the file level. An example is the McCabe complexity.
An example of our papers in this area is:
Antinyan, Vard, et al. “Identifying risky areas of software code in Agile/Lean software development: An industrial experience report.” Software Maintenance, Reengineering and Reverse Engineering (CSMR-WCRE), 2014 Software Evolution Week-IEEE Conference on. IEEE, 2014.
or this one:
Antinyan, Vard, et al. “Monitoring Evolution of Code Complexity and Magnitude of Changes.” Acta Cybernetica 21.3 (2014).
and this one:
Antinyan, Vard, et al. “Monitoring Evolution of Code Complexity in Agile/Lean Software Development.“
I was always Aciclovir without prescription wondering if the results are not biased by the mathematical operations which might not always have a reflection in the empirical world. Until I’ve come across this article which said that the summation is not that problematic after all.
Read the article http://arxiv.org/pdf/1503.08504.pdf: Assi, Rawad Abou. “Investigating the Impact of Metric Aggregation Techniques on Defect Prediction.” arXiv preprint arXiv:1503.08504 (2015).
Since the sample of projects was very small some replication is needed, but the results look quite promising and definitely Colchicine without prescription interesting.
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