27th Dec, 2019
Texas A&M University-Commerce
Discussion
Started 12th Sep, 2019
If it isn’t tested, it doesn’t work! Yes/No and Why?
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Your opinion, or anything related to the topics on testing!
I personally believe that testing isn’t just coming up with tests for desired use cases. We need to consider malicious use cases, too. And testing in development isn’t good enough either: we need to test with live systems, in situ. Because if we don’t, something, somewhere, is going to go wrong.
Most recent answer
If we went by that belief then we would never test anything. We would always believe that nothing worked. We can try things and hope that they work but we will never know as there is always a possibility that it might. There is also the chance that the test was a one time thing or completely false. This is like Schrödinger's cat. We will not know until we try but we cannot write off things just because we have not tried yet.
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Popular replies (1)
If we went by that belief then we would never test anything. We would always believe that nothing worked. We can try things and hope that they work but we will never know as there is always a possibility that it might. There is also the chance that the test was a one time thing or completely false. This is like Schrödinger's cat. We will not know until we try but we cannot write off things just because we have not tried yet.
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All replies (23)
Dear all,
Testing is my right arm as I don’t want to be the person telling MY boss that, “well, we thought it might, but we never tested it.”
3 Recommendations
I think, eliminating testing in natural sciences, engineering, and social sciences is suicidal for obvious reasons. However, the question about what testing is necessary and sufficient are quite actual in different domains. Usually, it's a tradeoff between a complete solution's cost and its reliability, and has a particular reasoning in every domain of interest.
Hello Mohammed,
I think most technical people would say that testing is essential, but I agree with Len Leonid Mizrah that there are real questions about whether testing is necessary and sufficient. For example, some systems cannot be tested such that all possible permutations of inputs and outputs can be tried. Software is a good example of a modern system where testing is a necessary condition to demonstrate that it "works", but if it is shown to "work" that does not imply that it was completely tested. Otherwise how can you account for the invariable presence of bugs in most software? And, of course, if the software is coupled to hardware and the hardware, in turn, is coupled to a GUI for human input and output, well, then you really have an insurmountable problem. Think of the fly-by-wire systems in passenger airplanes. You can always say that you tested the system, but what does that really mean?
I would extend Luciano de F. Costa remarks to include both verification and validation. With regard to a system, verification means did you build it right? Validation, on the other hand, means did you build the right thing? You can sometimes test to verify that the system was built to plan or specification, but testing for validation is many times impossible. For example, large scale defense systems are built with the idea of discouraging an attack by an enemy, but how can you be sure that the system you built is the right one to prevent attack? The Cuban missile crisis in the 1960's is a good example of where verification and validation testing could not be done. As the years pass and we learn more and more about the details of what each side was thinking and prepared to do, it seems like a miracle that WWIII did not happen. Think of the three Soviet submarines sent to Cuba with nuclear tipped torpedoes, who were chased down by the US Navy.
Anyway, I really like your question.
Regards,
Tom Cuff
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Dear Thomas Cuff - thank you for your reply! Great points!!
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Dear Shakir Faris Tuleab - thank you for your reply! Great points!!
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Dear Len Leonid Mizrah - thank you for your reply! Excellent points!!
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Dear Ali A. Al-Homaidan - thank you for your reply! Great points!!
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Dear Luciano da F. Costa - You are very welcome and thank you for your reply!!!
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Testing should be done for each and everything before this was kept in use. If one buys a computer one has to test the functioning, working, wiring and configuration. If everything is yes, then the system functions well. If not, the parts are to be replaced or the computer has to be changed.
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Dear Pisipaty Srinivas Kishore ,
Thank you for your reply!!!
2 Recommendations
Hi,
Every phase of a new product development would have involved testing/cross-verification. As humans, we may have committed an error somewhere; IT explains why we have a QA/QC division in well established labs too. So, instead of being prejudiced, it is better to test and establish the functionality.
Dear Mohammed Kemal - I agree!!
An equipment which is purchased has to be tested before it works. Take for example a motor connected to lift the water. This should be connected and tested. If this is not working, then this should be rectified or replaced. The winding problem or wires problem or switch or switch board or mains problem should be known and decision be taken.
One just not know whether something does or does not work. In addition, if the testing is not of high quality, one still does know after testing whether the tested product works or does not work.
Giving people small amounts of the cowpox to keep them from getting smallpox was not tested before the first administration but it worked. You cant say that one thing will or will not work until it's tested. It is like Schrödinger's cat. You don't know if the cat is alive or not until you open the box and look.
9 Recommendations
If it isn’t tested, it doesn’t work! Yes/No and Why?
Testing is important because it provides empirical evidence & assurance whether a particular product / tool / model is meeting its planned objective. However, a test needs consider the following:
- testing objective need to be clear or agreed upon so that the testing is meaningful or serve the purpose
- testing boundary / scope & its width & depth need to be determined and map to the possible outcomes / impacts which are measurable against the testing objective
- always remember an empirical testing outcome provides new research area opportunity
2 Recommendations
If we went by that belief then we would never test anything. We would always believe that nothing worked. We can try things and hope that they work but we will never know as there is always a possibility that it might. There is also the chance that the test was a one time thing or completely false. This is like Schrödinger's cat. We will not know until we try but we cannot write off things just because we have not tried yet.
16 Recommendations
Similar questions and discussions
How do I deal with unbalanced panel data?
Hello everyone:
I have a few questions concerning the choices I have to make with respect to unbalanced panel data. I have prepared this question for Statalist.org, and therefore it is formatted in a way that State users will be most familiar (I am using StataMP 13 on a Macbook Pro).
I am dealing with a large dataset of 181 cases and 44 time-periods (n=7486). When I run the xtset command for designating the panel and time variables I am told that the panel variable is unbalanced. I know that the data is unbalanced because my independent variables have randomly missing data. I am now faced with a number of options from which I don't know how to select.
1. I have read that the use of panel corrected standard errors is suggested for panel data because such standard errors are more reliable (Beck & Katz 1995)*. The issue here, however, is that when I run my model through the xtpcse command I get the following error: "Number of gaps in sample: 70. No time periods are common to all panels, cannot estimate disturbance covariance matrix using casewise inclusion." I know what this means, but I don't know what to do about it. I have tried using the pairwise command which allows me to run the model successfully, but I don't know what types of calculation problems this may be causing. I have also repeated the pairwise approach by removing all cases with less than 5 observations, but I am still not sure as to what the problems may be with this approach. If the pairwise approach is acceptable, then what is the minimum number of observations necessary, and do these observations need to be continuous, e.g. 2001, 2002, 2003, 2004 as opposed to 2000, 2005, 2007, 2010?
2. The second option that I have followed is through the use of the xtreg command. I am familiar with xtreg and the choice between fixed-effect and random-effect models, but I am not sure if the unbalanced dataset is causing problems here as well. My question here is, which approach is better: xtpcse or xtreg, and why?
*Beck, N., & Katz, J. N. (1995). What to do (and not to do) with time-series cross-section data. American Political Science Review, 89(3), 634-647.
If you are interested in seeing the State output and a sample of my dataset please follow the link below to Statalist:
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