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Closed 10 years ago.
Does anyone have any suggestions on what Model Based Testing Tools to use? Is Spec Explorer/SPEC# worth it's weight in tester training?
What I have traditionally done is create a Visio Model where I call out the states and associated variables, outputs and expected results from each state. Then in a completely disconnected way, I data drive my test scripts with those variables based on that model. But, they are not connected. I want a way to create a model, associate the variables in a business friendly way, that will then build the data parameters for the scripts.
I can't be the first person to need this. Is there a tool out there that will do basically that? Short of developing it myself.
You might find the following answer to a similar question helpful:
http://testing.stackexchange.com/questions/92/how-to-get-started-with-model-based-testing
In it, I mention:
UML Pad http://web.tiscali.it/ggbhome/umlpad/umlpad.htm
A list of free UML Tools: http://en.wikipedia.org/wiki/Category:Free_UML_tools
Our Pairwise and combinatorial test case generator (which generates tests for you automatically based on a model you create - even if you don't create a UML model): http://hexawise.com
Incidentally, as explained in the answer I link to above, I focus my energies (research, tool development focus, passion, etc.) on the second part of your question - generating efficient and effective sets of tests that maximize coverage in a minimum number of test cases.
Justin (Founder of Hexawise)
I think an updated version of the "Spec Explorer for Visual Studio" power tool is supposed to be released soon - it's much easier to ramp up on than the current version, but still takes some time to learn.
If you want to start smaller, nmodel (also from microsoft) is a good place to start.
Check out TestOptimal. It offers full cycle Model-Based Testing with built-in data driven testing and combinatorial testing right within the model. It has graphical modeling and debugging which you can play the model and it graphically animates the model execution. You can link state/transition to the requirements. Models can be re-purposed for load testing with no changes. It can even create full automated MBT for web applications without any coding/scripting. Check out this short slide presentation: http://TestOptimal.com/tutorials/Overview.htm
You should try the "MaTeLo" tool of All4Tec. www.all4tec.net
"MaTeLo is a test cases generator for black box functional and system testing. Conformed to the Model Based Testing approach, MaTeLo uses Markov chains for modeling the test. This statistic addin allows products validation in a Systematic way. The efficiency is achieved by a reduction of the human resources needed, an increase of the model reuse and by the enhancement of the test strategy relevance (due to the reliability target). MaTeLo is independent and user-friendly, offers to the validation activities to pass from test scripting to real test engineering and to focus on the real added value of testing: the test plans"
You can ask an evaluation licence and try by yourself.
You can find some exemples here : http://www.all4tec.net/wiki/index.php?title=Tutorials
A colleague of mine have made this tool, http://mbt.tigris.org/ and its being used in large scale testing environments for years. It's Open Source and all..
Updating:
Here are short whitepaper: http://www.prolore.se/filer/whitepaper/MBT-Agile.pdf
This tool is great with MBT, yED a free modelling software.
I can tell you that the 2010 version of Spec Explorer that requires The Professional version of Visual Studio is a great tool, assuming you already have Visual Studio. The older version of spec explorer was good, but the limitation was that if you ended up modeling a system that was non-finite, you were out of luck.
The new version has improved techniques for looking at 'slices' of the model to the point where you have finite states. Once you have the finite states, you can generate the test cases.
The great thing is that as you change the model and re-slice your model, it's straightforward to re-generate tests and re-run them. This certainly beats the manual process any day.
I can't compare this tool to other toolsets, but the integration with Visual Studio is invaluable. If you don't use Visual Studio, you may have limited success.
Related
I would like to optimize a design by having an optimizer make changes to a CAD file, which is then analyzed in FEM, and the results fed back into the optimizer to make changes on the design based on the FEM, until the solution converges to an optimum (mass, stiffness, else).
This is what I envision:
create a blueprint of the part in a CAD software (e.g. CATIA).
run an optimizer code (e.g. fmincon) from within a programming language (e.g. Python). The parameters of the optimizer are parameters of the CAD model (angles, lengths, thicknesses, etc.).
the optimizer evaluates a certain design (parameter set). The programming language calls the CAD software and modifies the design accordingly.
the programming language extracts some information (e.g. mass).
then the programming language extracts a STEP file and passes it a FEA solver (e.g. Abaqus) where a predefined analysis is performed.
the programming language reads the results (e.g. max van Mises stress).
the results from CAD and FEM (e.g. mass and stress) are fed to the optimizer, which changes the design accordingly.
until it converges.
I know this exists from within a closed architecture (e.g. isight), but I want to use an open architecture where the optimizer is called from within an open programming language (ideally Python).
So finally, here are my questions:
Can it be done, as I described it or else?
References, tutorials please?
Which softwares do you recommend, for programming, CAD and FEM?
Yes, it can be done. What you're describing is a small parametric structural sizing multidisciplinary optimization (MDO) environment. Before you even begin coding up the tools or environment, I suggest doing some preliminary work on a few areas
Carefully formulate the minimization problem (minimize f(x), where x is a vector containing ... variables, subject to ... constraints, etc.)
Survey and identify individual tools of interest
How would each tool work? Input variables? Output variables?
Outline in a Design Structure Matrix (a.k.a. N^2 diagram) how the tools will feed information (variables) to each other
What optimizer is best suited to your problem (MDF?)
Identify suitable convergence tolerance(s)
Once the above steps are taken, I would then start to think MDO implementation details. Python, while not the fastest language, would be an ideal environment because there are many tools that were built in Python to solve MDO problems like the one you have and the low development time. I suggest going with the following packages
OpenMDAO (http://openmdao.org/): a modern MDO platform written by NASA Glenn Research Center. The tutorials do a good job of getting you started. Note that each "discipline" in the Sellar problem, the 2nd problem in the tutorial, would include a call to your tool(s) instead of a closed-form equation. As long as you follow OpenMDAO's class framework, it does not care what each discipline is and treats it as a black-box; it doesn't care what goes on in-between an input and an output.
Scipy and numpy: two scientific and numerical optimization packages
I don't know what software you have access to, but here are a few tool-related tips to help you in your tool survey and identification:
Abaqus has a Python API (http://www.maths.cam.ac.uk/computing/software/abaqus_docs/docs/v6.12/pdf_books/SCRIPT_USER.pdf)
If you need to use a program that does not have an API, you can automate the GUI using Python's win32com or Pywinauto (GUI automation) package
For FEM/FEA, I used both MSC PATRAN and MSC NASTRAN on previous projects since they have command-line interfaces (read: easy to interface with via Python)
HyperSizer also has a Python API
Install Pythonxy (https://code.google.com/p/pythonxy/) and use the Spyder Python IDE (included)
CATIA can be automated using win32com (quick Google search on how to do it: http://code.activestate.com/recipes/347243-automate-catia-v5-with-python-and-pywin32/)
Note: to give you some sort of development time-frame, what you're asking will probably take at least two weeks to develop.
I hope this helps.
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Closed 9 years ago.
I'm looking for ideas for a Neural Networks project that I could complete in about a month or so. I'm doing it for the National Science Fair, so I need something that has some curb appeal as well since it's being judged.
It doesn't necessarily have to be completely new and unique, I'm just looking for ideas, but it should be complex enough that it would impress someone who knows about the field. My first idea was to implement a spam filter of sorts, but I recently found out that NN's aren't a very good way to do it. I've already got a basic NN simulator with Genetic Algorithms, and I'm also adding the the generic back-propagation algorithms as well.
Any ideas?
Look into Numenta's Hierarchical Temporal Memory (HTM) concept. This may be slightly off topic if the expectation is of "traditional" Neural Nets, but it is also an extremely promising avenue for Artificial Intelligence.
Although Numenta introduced HTM and its associated software platform, NuPIC, almost five years ago, the first commercial product based upon this technology was released (in beta) a few weeks ago by Vitamin D. It is called Vitamin D Video and essentially turns any webcam or IP camera into a sophisticated video monitoring system, recognizing classes of items (say persons vs. cats or other animals) in the video feed.
With the proper setup, this type of application could make for an interesting display at the Science Fair, one with much "curb appeal".
To wet your appetite or even get your feet wet with HTM technology you can download NuPIC and check its various sample applications. Chances are that you may find something that meets typical criteria of both geekness and coolness for science fairs.
Generally, HTMs aim at solving problems which are simple for humans but difficult for computers; such a statement is somewhat of a generic/applicable to Neural Nets, but HTMs take this to the "next level".
Although written in C (I think) NuPIC is typically interfaced in Python, which makes it a convenient test bed for simple yet sophisticated proofs of concept applications.
You could always try to play around with a neural network and stock courses, if I had a month of spare time for a neural network implementation, thats what I would play with.
A friend of mine in college wrote a NN to play go on a 9x9 board.
I don't think it ever got very good, but I think it would be fun to try.
Look on how a bidirectional associative memory compare with other classical edit distance algorithms (Levenshtein, Damerau-Levenshtein etc) for typo correction. Also consider the articles on hebbian unlearning while training your NN - it seems that the confabulation phenomena is avoided.
I've done some works on top of NN, mainly an XML based language (Neural XML). See details here
http://amazedsaint.blogspot.com/search/label/Neural%20Network
Also, one interesting .NET Neural network project is Aforge.net - Check out that as well..
You can implement the game Cellz or create a controller for it. It was first created by Simon M Lucas. It's a nice and interesting game, and i'm sure that everyone will love it. I used it also for a school project and it turned out very ok.
You can find in that page some links to other interesting games.
How about applying it to predicting exchange rate (USD - EUR for example for sub minute trading) should be fun to show net gain of money over 1 month.
I doubt this will work for trades longer than a minute... without a lot of extra work.
I like using committee machines so why not apply it to Face-Detection in images / movies or voice print authentication.
Finally you could get it to play pleasing music and use a crowd sourcing fitness function whereby people vote for the best "musicians"
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Closed 10 years ago.
I would be interested in looking at a list of projects that did and did not do unit testing, and other forms of regression testing, to see how those companies turned out.
All test infected developers know it saves them time, but it would be interesting to what correlation there is between code quality/test coverage and business success. Something objective like:
xyz corp, makes operating systems, didnt test, makes $50M
123 corp, makes operating systems, does test, makes $100M
Does anyone know of any studies done?
Microsoft commissioned this internal study not so long ago. It compared teams that did and didn't use TDD. To quote the summary:
Based on the findings of the existing studies, it can be concluded that TDD seems to improve software quality, especially when employed in an industrial context. The findings were not so obvious in the semiindustrial or academic context, but none of those studies reported on decreased quality either. The productivity effects of TDD were not very obvious, and the results vary regardless of the context of the study. However, there were indications that TDD does not necessarily decrease the developer productivity or extend the project leadtimes: In some cases, significant productivity improvements were achieved with TDD while only two out of thirteen studies reported on decreased productivity. However, in both of those studies the quality was improved.
Yes, pick up a copy of Code Complete or even Rapid Development by Steve McConnell. He cites a number of studies.
Any realistic study would have to include thousands of companies. There are far too many factors other than does/doesn't unit test that affect the bottom line. I doubt Microsoft's profit changes all that much whether or not they release an amazing OS every year or one that's as buggy as hell. Just listing a few companies is anecdotal evidence.
Perl is big on testing and regression testing.
I always associate Unit testing with Agile development (XP in particular); you might find that any link between project success and unit testing is influenced by use of agile as well.
I don't know of any surveys specifically, but I did find this just now:
http://people.engr.ncsu.edu/txie/testingresearchsurvey.htm which has around 30 llinks to stuff such as: "Qualitative methods in empirical studies of software engineering. Seaman, C.B, Software Engineering, IEEE Transactions on , Volume: 25 , Issue: 4 , July-Aug. 1999"
Not wanted to sound rude - I assume you've already done bit of a search online?
I seem to remember that Code Complete might have references to research into unit testing and project success - but I'm not sure.
Another option would be to approach some software testing companies and see if they had any useful data.
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Closed 9 years ago.
Here are the estimates the system should handle:
3000+ end users
150+ offices around the world
1500+ concurrent users at peak times
10.000+ daily updates
4-5 commits per second
50-70 transactions per second (reads/searches/updates)
This will be internal only business application, dedicated to help shipping company with worldwide shipment management.
What would be your technology choice, why that choice and roughly how long would it take to implement it? Thanks.
Note: I'm not recruiting. :-)
So, you asked how I would tackle such a project. In the Smalltalk world, people seem to agree that Gemstone makes things scale somewhat magically.
So, what I'd really do is this: I'd start developing in a simple Squeak image, using SandstoneDB. Then, this moment would come where a single image begins being too slow.
GemStone then takes care of copying your public objects (those visible from a certain root) back and forth between all instances. You get sessions and enhanced query functionalities, plus quite a fast VM.
It shares data with C, Java and Ruby.
In fact, they have their own VM for ruby, which is also worth a look.
wikipedia manages much more demanding requirements with MySQL
Your volumes are significant but not likely to strain any credible RDBMS if programmed efficiently. If your team is sloppy (i.e., casually putting SQL queries directly into components which are then composed into larger components), you face the likelihood of a "multiplier" effect where one logical requirement (get the data necessary for this page) turns into a high number of physical database queries.
So, rather than focussing on the capacity of your RDBMS, you should focus on the capacity of your programmers and the degree to which your implementation language and environment facilitate profiling and refactoring.
The scenario you propose is clearly a 24x7x365 one, too, so you should also consider the need for monitoring / dashboard requirements.
There's no way to estimate development effort based on the needs you've presented; it's great that you've analyzed your transactions to this level of granularity, but the main determinant of development effort will be the domain and UI requirements.
Choose the technology your developers know and are familiar with. All major technologies out there will handle such requirements with ease.
Your daily update numbers vs commits do not add up. Four commits per second = 14,400 per hour.
You did not mention anything about expected database size.
In any case, I would concentrate my efforts on choosing a robust back end like Oracle, Sybase, MS etc. This choice will make the most difference in performance. The front end could either be a desktop app or WEB app depending on needs. Since this will be used in many offices around the world, a WEB app might make the most sense.
I'd go with MySQL or PostgreSQL. Not likely to have problems with either one for your requirements.
I love object-databases. In terms of commits-per-second and database-roundtrip, no relational database can hold up. Check out db4o. It's dead easy to learn, check out the examples!
As for the programming language and UI framework: Well, take what your team is good at. Dynamic languages with fewer meta-time wasting will probably save time.
There is not enough information provided here to give a proper recommendation. A little more due diligence is in order.
What is the IT culture like? Do they prefer lots of little servers or fewer bigger servers or big iron? What is their position on virtualization?
What is the corporate culture like? What is the political climate like? The open source offerings may very well handle the load but you may need to go with a proprietary vendor just because they are already used to navigating the political winds of a large company. Perception is important.
What is the maturity level of the organization? Do they already have an Enterprise Architecture team in place? Do they even know what EA is?
You've described the operational side but what about the analytical side? What OLAP technology are they expecting to use or already have in place?
Speaking of integration, what other systems will you need to integrate with?
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Closed 10 years ago.
I would like to track metrics that can be used to improve my team’s software development process, improve time estimates, and detect special case variations that need to be addressed during the project execution.
Please limit each answer to a single metric, describe how to use it, and vote up the good answers.
(source: osnews.com)
ROI.
The total amount of revenue brought in by the software minus the total amount of costs to produce the software. Breakdown the costs by percentage of total cost and isolate your poorest performing and most expensive area in terms of return-on-investment. Improve, automate, or eliminate that problem area if possible. Conversely, find your highest return-on-investment area and find ways to amplify its effects even further. If 80% of your ROI comes from 20% of your cost or effort, expand that particular area and minimize the rest by comparison.
Costs will include payroll, licenses, legal fees, hardware, office equipment, marketing, production, distribution, and support. This can be done on a macro level for a company as whole or a micro level for a team or individual. It can also be applied to time, tasks, and methods in addition to revenue.
This doesn't mean ignore all the details, but find a way to quantify everything and then concentrate on the areas that yield the best (objective) results.
Inverse code coverage
Get a percentage of code not executed during a test. This is similiar to what Shafa mentioned, but the usage is different. If a line of code is ran during testing then we know it might be tested. But if a line of code has not been ran then we know for sure that is has not been tested. Targeting these areas for unit testing will improve quality and takes less time than auditing the code that has been covered. Ideally you can do both, but that never seams to happen.
"improve my team’s software development process": Defect Find and Fix Rates
This relates to the number of defects or bugs raised against the number of fixes which have been committed or verified.
I'd have to say this is one of the really important metrics because it gives you two things:
1. Code churn. How much code is being changed on a daily/weekly basis (which is important when you are trying to stabilize for a release), and,
2. Shows you whether defects are ahead of fixes or vice-versa. This shows you how well the development team is responding to defects raised by the QA/testers.
A low fix rate indicates the team is busy working on other things (features perhaps). If the bug count is high, you might need to get developers to address some of the defects.
A low find rate indicates either your solution is brilliant and almost bug free, or the QA team have been blocked or have another focus.
Track how long is takes to do a task that has an estimate against it. If they were well under, question why. If they are well over, question why.
Don't make it a negative thing, it's fine if tasks blow out or were way under estimated. Your goal is to continually improve your estimation process.
Track the source and type of bugs that you find.
The bug source represents the phase of development in which the bug was introduced. (eg. specification, design, implementation etc.)
The bug type is the broad style of bug. eg. memory allocation, incorrect conditional.
This should allow you to alter the procedures you follow in that phase of development and to tune your coding style guide to try to eliminate over represented bug types.
Velocity: the number of features per given unit time.
Up to you to determine how you define features, but they should be roughly the same order of magnitude otherwise velocity is less useful. For instance, you may classify your features by stories or use cases. These should be broken down so that they are all roughly the same size. Every iteration, figure out how many stories (use-cases) got implemented (completed). The average number of features/iteration is your velocity. Once you know your velocity based on your feature unit you can use it to help estimate how long it will take to complete new projects based on their features.
[EDIT] Alternatively, you can assign a weight like function points or story points to each story as a measure of complexity, then add up the points for each completed feature and compute velocity in points/iteration.
Track the number of clones (similar code snippets) in the source code.
Get rid of clones by refactoring the code as soon as you spot the clones.
Average function length, or possibly a histogram of function lengths to get a better feel.
The longer a function is, the less obvious its correctness. If the code contains lots of long functions, it's probably a safe bet that there are a few bugs hiding in there.
number of failing tests or broken builds per commit.
interdependency between classes. how tightly your code is coupled.
Track whether a piece of source has undergone review and, if so, what type. And later, track the number of bugs found in reviewed vs. unreviewed code.
This will allow you to determine how effectively your code review process(es) are operating in terms of bugs found.
If you're using Scrum, the backlog. How big is it after each sprint? Is it shrinking at a consistent rate? Or is stuff being pushed into the backlog because of (a) stuff that wasn't thought of to begin with ("We need another use case for an audit report that no one thought of, I'll just add it to the backlog.") or (b) not getting stuff done and pushing it into the backlog to meet the date instead of the promised features.
http://cccc.sourceforge.net/
Fan in and Fan out are my favorites.
Fan in:
How many other modules/classes use/know this module
Fan out:
How many other modules does this module use/know
improve time estimates
While Joel Spolsky's Evidence-based Scheduling isn't per se a metric, it sounds like exactly what you want. See http://www.joelonsoftware.com/items/2007/10/26.html
I especially like and use the system that Mary Poppendieck recommends. This system is based on three holistic measurements that must be taken as a package (so no, I'm not going to provide 3 answers):
Cycle time
From product concept to first release or
From feature request to feature deployment or
From bug detection to resolution
Business Case Realization (without this, everything else is irrelevant)
P&L or
ROI or
Goal of investment
Customer Satisfaction
e.g. Net Promoter Score
I don't need more to know if we are in phase with the ultimate goal: providing value to users, and fast.
number of similar lines. (copy/pasted code)
improve my team’s software development process
It is important to understand that metrics can do nothing to improve your team’s software development process. All they can be used for is measuring how well you are advancing toward improving your development process in regards to the particular metric you are using. Perhaps I am quibbling over semantics but the way you are expressing it is why most developers hate it. It sounds like you are trying to use metrics to drive a result instead of using metrics to measure the result.
To put it another way, would you rather have 100% code coverage and lousy unit tests or fantastic unit tests and < 80% coverage?
Your answer should be the latter. You could even want the perfect world and have both but you better focus on the unit tests first and let the coverage get there when it does.
Most of the aforementioned metrics are interesting but won't help you improve team performance. Problem is your asking a management question in a development forum.
Here are a few metrics: Estimates/vs/actuals at the project schedule level and personal level (see previous link to Joel's Evidence-based method), % defects removed at release (see my blog: http://redrockresearch.org/?p=58), Scope creep/month, and overall productivity rating (Putnam's productivity index). Also, developers bandwidth is good to measure.
Every time a bug is reported by the QA team- analyze why that defect escaped unit-testing by the developers.
Consider this as a perpetual-self-improvement exercise.
I like Defect Resolution Efficiency metrics. DRE is ratio of defects resolved prior to software release against all defects found. I suggest tracking this metrics for each release of your software into production.
Tracking metrics in QA has been a fundamental activity for quite some time now. But often, development teams do not fully look at how relevant these metrics are in relation to all aspects of the business. For example, the typical tracked metrics such as defect ratios, validity, test productivity, code coverage etc. are usually evaluated in terms of the functional aspects of the software, but few pay attention to how they matter to the business aspects of software.
There are also other metrics that can add much value to the business aspects of the software, which is very important when an overall quality view of the software is looked at. These can be broadly classified into:
Needs of the beta users captured by business analysts, marketing and sales folks
End-user requirements defined by the product management team
Ensuring availability of the software at peak loads and ability of the software to integrate with enterprise IT systems
Support for high-volume transactions
Security aspects depending on the industry that the software serves
Availability of must-have and nice-to-have features in comparison to the competition
And a few more….
Code coverage percentage
If you're using Scrum, you want to know how each day's Scrum went. Are people getting done what they said they'd get done?
Personally, I'm bad at it. I chronically run over on my dailies.
Perhaps you can test CodeHealer
CodeHealer performs an in-depth analysis of source code, looking for problems in the following areas:
Audits Quality control rules such as unused or unreachable code,
use of directive names and
keywords as identifiers, identifiers
hiding others of the same name at a
higher scope, and more.
Checks Potential errors such as uninitialised or unreferenced
identifiers, dangerous type casting,
automatic type conversions, undefined
function return values, unused
assigned values, and more.
Metrics Quantification of code properties such as cyclomatic
complexity, coupling between objects
(Data Abstraction Coupling), comment
ratio, number of classes, lines of
code, and more.
Size and frequency of source control commits.