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Recently, I am working on my course project, the topic is the creation of a new hybrid software process model by integrating Scrum and Team Software Process (TSP). Integration of these two models will be based on the SEMAT Essence Kernel Framework.
I am wondering:
Which steps should be followed for this integration (like
determination of the roles and artifacts in these two models)?
What should be the criteria to decide on good sides?
Thanks in advance!
The best way I think I can answer this question is by quoting the agile manifesto.
"Individuals and interactions over processes and tools"
Agile is about people, teamwork and craftsmanship. It's about involving the customer closely to figure out what really is needed - and delivering that, in small increments of working software. Agile is inspect and adapt, based on experimental delivery and the feedback and evidence that comes from that.
Trust yourself. Work closely together and you can do this. The best learning often comes from doing. :)
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this is more of an hypothetical question, but might have great consequences. Lot of us in Modelica community are dealing with large scale systems with expensive simulation times. This is usually not an obstacle for bugfixing and development, but speeding up the simulation might allow for better and faster optimizations.
Recently I came across Modia possibilities, claiming to have superb numerical solvers, achieving better simulation times than Dymola, a state-of-the-art Modelica compiler. The syntax seemed to cover all important bits. Recreating large scale component models in Modia is unfeasible, but what about automatically translating the flattenized Modelica to Modia? Is that realistic? Would that provide a speed up? Has anyone tried before? I have searched for some
This might also hopefully improve integration of Modelica models and postprocesssing / identificaiton tooling within one language, instead of using FMI or invoking a separate executable.
Thanks for any suggestions.
For those interested, we might as well start developing this.
We in the Modia team agrees that the modeling know how in Modelica libraries must be reused. So we are working on a translator (brief details given in https://ep.liu.se/ecp/157/060/ecp19157060.pdf) from Modelica to Modia. The plan is to initially provide translated versions of Modelica.Blocks, Modelica.Electrical.Analog and Modelica.Mechanics together with Modia.
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My team is making the transition to Scrum.
I am facing an issue I still not found on the various Scrum resources I've been studying: how to manage training?
I express myself by example:
my team has 4 developers, 2 of them know nothing about Test Driven Development
the project must be done using TDD
Should I create a backlog item "Study TDD" and use the first sprints so that the untrained developers learn TDD?
Or should I remove the developers from the project until they completed the training? Which is the best practice in this case?
Just send them to the training, and continue your sprints as normal. While they are in training they won't contribute to the velocity, the same as if they were sick or on vacation or just having a bad day. The velocity isn't a goal so much it's an indicator.
You can create a story for training if you want, but it isn't necessary. If creating the story helps, by all means do it. Don't do it just because you think you're supposed to. I've been on teams that liked to track non-product tasks, and teams that didn't. Do what your team decides to do.
In your question you wrote:
the project must be done using TDD
I hope that's because the team decided that, and it wasn't something that was decided for them. The whole point of scrum is to build a team that can make these decisions for themselves.
Well, I will answer YES.
you need to create back log
you need to define test cases and follow TDD
you need to do stand-up meetings and daily follow up
you need to define a team member as scrum master who have best understanding
further, you can engage an online training of transformation expert
Like, I know these guys regarding Agile/Scrum Transformation. http://sparklegenius.com/solutions/agile-transformation/
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Recently, I was reading a paper whose name is "On the Effectiveness of Concern Metrics to Detect Code Smells: An Empirical Study".
I come from a non-English speaking country, and I can not quite understand what Concern Metrics means in the field of software engineering.
It is not referring to the relationship between objects?
I have some understanding of java and c #, some people may be able to use java to give me an example.
Thanks.
Like it is said in the paper's abstract: "While traditional metrics quantify properties of software modules, concern metrics quantify concern properties, such as scattering and tangling." Are you familiar to the cross-cutting concern concept? This question provides examples of concerns: Cross cutting concern example Try to read papers on aspect-oriented programming (AOP) to grasp more concepts in order to understand better the relationship between concerns and code. The metrics are attempts to quantify, for instance, the amount of scatterness of a concern (e.g. login) over the source code.
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What can you do after learning big data related concepts, Hadoop, ML, NLP etc? Where can you implement these?
Not really a software related question - but it's very relevant to current technology and why some software exists. So here is an opinion.
We now live in a world where it is possible to monitor and digitally record information on an epic scale that continues to expand with concepts like The Internet of Things.
With this information it becomes possible to look at the evidence behind decisions that previously would have been made by gut instinct or opinions. What impact does road design have on traffic flow? Which medical drugs get best results in the real world and not just in drugs trials? Is there a correlation between office temperature and productivity? and so on for millions of questions in different domains.
Around the world, organisations are using data they never previously had, to get better at whatever they do (Good or bad).
The big data concepts are the tools for managing all this information. Big Data is not just large in volume, it is often unstructured and in different forms.
So to answer your question. You can implement these concepts by working with organisations that are using Big Data. Hopefully you can see the potential of Big Data along with the mind bending headache it can create when trying to make sense of it.
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I tried googling around. I found one website that talked about how many bugs were found and how much it reduce testing. But it was only one page and I found no papers that talk about it.
Is there anything published to show the time or cost savings of using Ada?
There have been a few studies/papers, the only one that springs immediately is probably the most famous:
Comparing Development Costs of C and Ada (1995)
There is also a presentation:
Programming Languages and Lifecycle Cost (1997)
Other studies:
A Comparison of ADA 83 and C++ (1991)
Also of interest Ironsides, which is [AFAIK] the first verified DNS-server, has a couple of papers that mention the costs of buggy/insecure software and the benefits of formal verification.
I have seen one paper comparing the success rate of student teams in developing real time systems in either Ada or C. In that experiment, success rates were significantly higher in Ada; I'll leave the actual details to the paper.
It is "Software Engineering: On the Right Track" on this page