SWLT short dumps during check of SCI inspection - abap

I use SWLT tool to check for inefficient SQL statements and experience a dump every time I start it by SCI inspection created with DEFAULT check variant. No matter which input object I pass to it.
But if I choose PERFORMANCE_DB variant all goes fine during SWLT run.
Yes, I aware that in recommendations they say that this variant is recommended
however, in my opinion it shouldn't throw such ugly dump anyway.
Anybody encountered such an error? Is it release-dependent and was fixed already in higher releases? I am on ABAP 750 SP00.

Related

How to find the size of a reg in verilog?

I was wondering if there were a way to compute the size of a reg in Verilog. I researched it quite a bit, and found $size(a), but it's only in SystemVerilog, and it won't work in my verilog program.
Does anyone know an alternative for this??
I also wanted to ask as a side note; I'm having some trouble with my test bench in the sense that when I update a value in the file, that change is not taken in consideration when I simulate. I've been told I might have been using an old test bench but the one I am continuously simulating is the only one available in this project.
EDIT:
To give you an idea of what's the problem: in my code there is a "start" signal and when it is set to 1, the operation starts. Otherwise, it stays idle. I began writing the test bench with start=0, tested it and simulated it, then edited the test bench by setting start to 1. But when I simulate it, the start signal remains 0 in the waveform. I tried to check whether I was using another test bench, but it is the only test bench I am using in this project.
Given that I was on a deadline, I worked on the code so that it would adapt to the "frozen" test bench. I am getting now all the results I want, but I wanted to test some other features of my code, so I created a new project and copy pasted the code in new files (including the same test bench). But when I ran a simulation, the waveform displayed wrong results (even though I was using the exact same code in all modules and test bench). Any idea why?
Any help would be appreciated :)
There is a standardised way to do this, but it requires you to use the VPI, which I don't think you get on Modelsim's student edition. In short, you have to write C code, and dynamically link it to the simulator. In the C code, you can get object properties using routines such as vpi_get. Useful properites might be vpiSize, which is what you want, vpiLeftRange, vpiRightRange, and so on.
Having said all that, Verilog is essentially a static language, and objects have to be declared with a static width using constant expressions. Having a run-time method to determine an object's size is therefore of pretty limited value (since you should already know it), and may not solve whatever problem you actually have. Your question would make more sense for VHDL (and SystemVerilog?), which are much more dynamic.
Note on Icarus: the developers have pushed lots of SystemVerilog stuff back into the main language. If you take advantge of this you may find that your code is not portable.
Second part of your question: you need to be specific on what your problem actually is.

Best practice for writing tests that reproduce bugs

I am struggling a bit with the way how to write tests that reproduce an issue that has not been yet fixed.
Should one write the test and use wrong expectations and once the bug is fixed the developer will see the failure and adjust the expectations or should one just write the test with correct expectations and disable it. Once it is fixed you have to enable it again.
I would prefer the way to define wrong expectations and add the correct ones in comments and once I fix an issue I will immediately get a notification that it fails. If I disable it I won't see it failing and it will probably stay disabled until one will discover this test.
Are there any other ways doing this?
Thanks for your comments.
Martin
Ideally you would write a test that reproduces the bug and then fix said bug.
If for whatever reason that is not currently an option I would say that your approach of having the wrong expectations would be better than having an ignored test. Assuming that you use some clear variable name/ method name / comments that the test is more a placeholder and not the desired outcome.
One thing that I've done is write a test that is a "time bomb" reminder. I pick a date that is a few weeks/months out from now that I expect to be able to get back to it or have it fixed by. If I end up having to push the date out 2 or 3 times I end up deleting the test because it must not be that important.
as #Jarred said, best way is to write a test that express the correct expectations, check if it fails, then fix production code and see the test passes.
if it's not an option then remember that tests are not only to test but also to document. so write a test that document how your program does actually work. if necessary add a comment to the test. and don't write tests that are ignored - it's pointless. in future you can refactor your code many times, you could accidentally fix this test or introduce even more error in this area. writing tests that are intended to be long term ignored is just a waste of time.
don't be afraid that you will forget about that particular bug/test, just create a ticket in your issue tracking system - that's what it's made for.
if you use a testing framework that supports groups, you can add all those tests to be able to instantly exclude those test if needed.
also i really don't like the concept of 'time bomb tests'. your build MUST be reproducible - that's the fundamental assumption of release management, continuous integration, ability to pass your code to another team etc. tests are not meant to track and remind about the issues, it's the job of the issue tracking system. seriously, don't do it
Actually I thought about this again. We are using JUnit and it supports defining expectations on exceptions via #Test(expected=Exception.class).
So what one can do is write the test with the desired expectations and define the test with #Test(expected=AssertionError.class). Once the test will be fixed the test starts failing and the developer has to remove the expectation.

Error checking overkill?

What error checking do you do? What error checking is actually necessary? Do we really need to check if a file has saved successfully? Shouldn't it always work if it's tested and works ok from day one?
I find myself error checking for every little thing, and most of the time if feels overkill. Things like checking to see if a file has been written to a file system successfully, checking to see if a database statement failed.......shouldn't these be things that either work or don't?
How much error checking do you do? Are there elements of error checking that you leave out because you trust that it'll just work?
I'm sure I remember reading somewhere something along the lines of "don't test for things that'll never really happen".....can't remember the source though.
So should everything that could possibly fail be checked for failure? Or should we just trust those simpler operations? For example, if we can open a file, should we check to see if reading each line failed or not? Perhaps it depends on the context within the application or the application itself.
It'd be interesting to hear what others do.
UPDATE: As a quick example. I save an object that represents an image in a gallery. I then save the image to disc. If the saving of the file fails I'll have to image to display even though the object thinks there is an image. I could check for failure of the the image saving to disc and then delete the object, or alternatively wrap the image save in a transaction (unit of work) - but that can get expensive when using a db engine that uses table locking.
Thanks,
James.
if you run out of free space and try to write file and don't check errors your appliation will fall silently or with stupid messages. i hate when i see this in other apps.
I'm not addressing the entire question, just this part:
So should everything that could
possibly fail be checked for failure?
Or should we just trust those simpler
operations?
It seems to me that error checking is most important when the NEXT step matters. If failure to open a file will allow error messages to get permanently lost, then that is a problem. If the application will simply die and give the user an error, then I would consider that a different kind of problem. But silently dying, or silently hanging, is a problem that you should really do your best to code against. So whether something is a "simple operation" or not is irrelevant to me; it depends on what happens next, or what would be the result if it failed.
I generally follow these rules.
Excessively validate user input.
Validate public APIs.
Use Asserts that get compiled out of production code for everything else.
Regarding your example...
I save an object that represents an image in a gallery. I then save the image to disc. If the saving of the file fails I'll have [no] image to display even though the object thinks there is an image. I could check for failure of the the image saving to disc and then delete the object, or alternatively wrap the image save in a transaction (unit of work) - but that can get expensive when using a db engine that uses table locking.
In this case, I would recommend saving the image to disk first before saving the object. That way, if the image can't be saved, you don't have to try to roll back the gallery. In general, dependencies should get written to disk (or put in a database) first.
As for error checking... check for errors that make sense. If fopen() gives you a file ID and you don't get an error, then you don't generally need to check for fclose() on that file ID returning "invalid file ID". If, however, file opening and closing are disjoint tasks, it might be a good idea to check for that error.
This may not be the answer you are looking for, but there is only ever a 'right' answer when looked at in the full context of what you're trying to do.
If you're writing a prototype for internal use and if you get the odd error, it doens't matter, then you're wasting time and company money by adding in the extra checking.
On the other hand, if you're writing production software for air traffic control, then the extra time to handle every conceivable error may be well spent.
I see it as a trade off - extra time spent writing the error code versus the benefits of having handled that error if and when it occurs. Religiously handling every error is not necessary optimal IMO.

Print complete control flow through gdb including values of variables

The idea is that given a specific input to the program, somehow I want to automatically step-in through the complete program and dump its control flow along with all the data being used like classes and their variables. Is their a straightforward way to do this? Or can this be done by some scripting over gdb or does it require modification in gdb?
Ok the reason for this question is because of an idea regarding a debugging tool. What it does is this. Given two different inputs to a program, one causing an incorrect output and the other a correct one, it will tell what part of the control flow differ for them.
So What I think will be needed is a complete dump of these 2 control flows going into a diff engine. And if the two inputs are following similar control flows then their diff would (in many cases) give a good idea about why the bug exist.
This can be made into a very engaging tool with many features build on top of this.
Tell us a little more about the environment. dtrace, for example, will do a marvelous job of this in Solaris or Leopard. gprof is another possibility.
A bumpo version of this could be done with yes(1), or expect(1).
If you want to get fancy, GDB can be scripted with Python in some versions.
What you are describing sounds a bit like gdb's "tracepoint debugging".
See gdb's internal help "help tracepoint". You can also see a whitepaper
here: http://sourceware.org/gdb/talks/esc-west-1999/
Unfortunately, this functionality is not currently implemented for
native debugging, but I believe that CodeSourcery is doing some work
on it.
Check this out, unlike Coverity, Fenris is free and widly used..
How to print the next N executed lines automatically in GDB?

What is soft coding? (Anti-pattern)

I found the Wikipedia entry on the soft coding anti-pattern terse and confusing. So what is soft coding? In what settings is it a bad practice (anti-pattern)? Also, when could it be considered beneficial, and if so, how should it be implemented?
Short answer: Going to extremes to avoid Hard Coding and ending up with some monster convoluted abstraction layer to maintain that is worse than if the hard coded values had been there from the start. i.e. over engineering.
Like:
SpecialFileClass file = new SpecialFileClass( 200 ); // hard coded
SpecialFileClass file = new SpecialFileClass( DBConfig.Start().GetConnection().LookupValue("MaxBufferSizeOfSpecialFile").GetValue());
The main point of the Daily WTF article on soft coding is that because of premature optimization and fear a system that is very well defined and there is no duplicated knowledge is altered and becomes more complex without any need.
The main thing that you should keep in mind is if your changes actually improve your system and avoid to lightly label something as anti-pattern and avoid it by all means. Configuring your system and avoiding hardcoding is a simple cure for duplicated knowledge in your system (see point 11 : "DRY Don't Repeat Yourself" in The Pragmatic Programmer Quick Reference Guide) This is the driving need behind the suggestion of avoiding hardcoding. I.e. there should be ideally only one place in you system (that would be code or configuration) that should be altered if you have to change something as simple as an error message.
Ola, a good example of a real project that has the concept of softcoding built in to it is the Django project. Their settings.py file abstracts certain data settings so that you can make the changes there instead of embedding them within your code. You can also add values to that file if necessary and use them where necessary.
http://docs.djangoproject.com/en/dev/topics/settings/
Example:
This could be a snippet from the settings.py file:
num_rows = 20
Then within one of your files you could access that value:
from django.conf import settings
...
for x in xrange(settings.num_rows):
...
Soft-coding: it is process of inserting values from external source into computer program. like insert values through keyboard, command line interface. Soft-coding considered as good programming practice because developers can easily modify programs.
Hard-coding. Assign values to program during writing source code and make executable file of program.Now, it is very difficult process to change or modify the program source code values. like in block-chain technology, genesis block is hard-code that cannot changed or modified.
The ultimate in softcoding:
const float pi = 3.1415; // Don't want to hardcode this everywhere in case we ever need to ship to Indiana.