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Information Technology Problem Solving – The 6 Principles of Scientific Problem Solving
This paper will explain the scientific approach to problem solving. Although it is written to address issues related to information technology, the concepts can be applied to other disciplines as well. The methods, concepts, and techniques described here are nothing new, but it’s surprising how many “problem solvers” fail to use them. In between I will include some real life examples.
Why do problem solvers make guesses instead of following a scientific approach to problem solving? Maybe because it feels faster? Maybe lack of experience in efficient problem solving? Or maybe because it sounds like hard work to do scientifically? Maybe while you’re speculating and not really settled, you generate more income and add some job security? Or maybe because you violated the first principle of problem solving: understand the problem.
Principle number 1. Understand the *real* problem.
Isn’t it obvious that before you can solve it, you need to understand the problem? maybe But, most of the time the solver starts solving without knowing the real problem. What a customer or user describes as a “problem” is usually just a symptom! “My computer doesn’t want to turn on” is a symptom. The real problem may be that the entire building is without power. “Every time I try to add a new product, I get an error message” is the symptom. The real problem here might be “The last 2 products I tried to add gave a ‘product already exists’ error”. Another classic example: “Nothing is working”…
You begin your research by defining the “real problem.” It involves asking questions (and sometimes verifying them) and doing some basic tests. Ask the user questions like “When was the last time it worked successfully?”, “How long have you been using the system?”, “Does it work on another PC or another user?”, “What is the exact error message?” etc. Ask for a screen-print of the error if possible. Your basic test will be to make sure the end-to-end devices are running. Check the user’s PC, network, web server, firewall, file server, database back-end, etc. Best-case scenario you’ll pinpoint the problem beforehand. In the worst case scenario you may end up removing multiple areas for the cause of the problem.
A real life example. Symptom according to user: “System hangs at random times when I order”. Environment: User enters order details in a form in mainframe application. When all the details are completed, the user will close the form tab. The mainframe then sends this information to the plant’s Oracle client/server system via communication software. The Oracle system will create a capacity plan and return either the error or the expected order date back to the mainframe system. This problem is quite serious, because you can leave customers if they try to place an order and the system does not accept them! To try to solve this problem, people started by researching: 1) the load and capacity of the mainframe hardware 2) monitoring the network load between the mainframe and the Oracle system 3) hiring a consultant to debug the communication software 4) debugging the Oracle capacity. Even after two months of the planning system, the problem has not been resolved.
Called “scientific problem solvers”. It took less than a day and the problem was solved! how? The solver spends the day seeing what the “real problem” was with the user. It has been found that there is a problem only in export orders. By investigating the capture screen and user actions, it was found that the last field of the form with the export commands was always left blank and the user did not tab this field. The system did not hang, it simply waited for the user to press “tab” the next time. Problem solved. It may be noted that the “scientific problem solver” had very limited knowledge of mainframes, order capturing systems, communications software and the Oracle capacity planning system. And that brings us to principle #2.
Principle number 2. Even if you don’t understand the system, don’t be afraid to start the solution process.
How many times have you heard “I can’t touch that code, because it was developed by someone else!”, or “I can’t help because I’m an HR consultant and that’s a financial problem”? If you don’t want to turn on the washing machine, you don’t need to be an electrical engineer, washing machine repair specialist, technician, or any other expert to find some basic fault. Make sure the plug is working. Check the trip-switch, etc. “I’ve never seen this error before” shouldn’t stop you from trying to fix it. With error messages and internet search engines, you can get several starting points.
Every complex system has some basic working principles. System A that reads data from System B can be extremely complex (perhaps a laboratory spectrometer that reads data from a programmable logic computer via an RS-232 port). But, some basics to test: Do both systems have power? Does one of these systems have an error message in the event log? Can you trace a “ping” or network packet from one system to another? Try a different communication cable. Search the Internet for error messages.
Once you’ve established what the problem is, you need to start fixing it. Sometimes initial research will point you directly to the solution (turn the power on; replace the faulty cable, etc.). However, sometimes the real problem itself is complex, so another principle is to solve it simply.
Principle number 3. Win it simple.
Let’s start this section with a real-life example. Under certain conditions, a stored procedure will hang. A stored procedure usually takes about an hour to run (when it’s not hanging). So, the developer tried to debug. Make a few changes and then wait another hour or so to see if the problem is resolved. After a few days the developer quit and a “troubleshooter” took over. The “problem solver” had to dispose of the knowledge that the stored procedure hangs under the witch condition. So, it was a simple exercise to make a copy of the process, and then remove all unnecessary code with this copy. All parameters are changed with hard-coded values. Bits of code were executed one at a time and result-sets were again hard-coded into a copy of the process. The problem was solved within 3 hours. Infinite-loop detected.
What the “troubleshooter” did was to simulate the problem and at the same time try to isolate the code causing the problem. By doing so, the complex (and time-consuming) storage process became somewhat faster and simpler.
If the problem is within an application, create a new application and try to simulate the problem within the new application if possible. If the problem occurs when a certain method is called for a certain control, then try to just include this control in an empty application and call that method with hard-coded values. If the problem is with the embedded SQL within the C# application, then try replicating the SQL within a database query tool (such as SQL*Plus for Oracle, Query Analyzer for SQL Server, or using ODBC to code databases in MS Excel. ).
When you can restate the problem in a simple way, you are more than 80% of the way to solving it.
If you don’t know where the problem is in the program, then use DEBUG.
Principle number 4. Debug.
Many application development tools come standard with a debugger. Weather it will be some sort of debugger in Macromedia Flash, Microsoft .NET, Delphi, or any development environment. If the tool doesn’t come standard with a debugger, you can simulate one.
The first thing you want to do with the debugger is determine where the problem is. You do this by adding breakpoints to key fields. Then you run the program in debug mode and you will know between which breakpoints the problem occurred. Drill down and you will find the place. Now that you know where the problem is, you can “overcome it simple”.
Another nice feature of most debuggers includes the ability to view variables, values, parameters, etc. as you step through the program. With these values known at certain stages, you can hard-code them into a “simplified version” of the program
If the development tool does not support debugging, you can simulate it. Place variable values and “hello I’m here” messages in steps in the program that output to the screen, to a log file, or to a database table. Remember to eject them after the problem is resolved… you don’t want your file system cluttered or full of log files!
Principle number 5. There is a wealth of information on the database back-end that can help solve the problem.
A “problem solver” was called in to help solve a very complex problem. One project was migrating the system from mainframe to client-server technology. Everything went well during testing, but when the systems went live, suddenly there were very few, and very random “common security errors”. (GPF-error was a common error trap in Windows 95 and 98). Attempts were made to simplify this code, debugging was attempted, but it was impossible to replicate. In a LAB environment, the problem does not arise! The problem appeared very randomly when debugging the trace messages in the log files. Some users experience it more than others, but eventually all users will get them! Interesting problem.
The “problem solver” solved this when he started analyzing the database back-end. Not sure if it was by chance or because of the scientific approach he systematically moved in the right direction. By tracing what was happening at the back-end level, it was discovered that all these applications were creating more and more connections to the database. Each time a user started a new transaction another connection to the database was established. The sum of connections was only released when the application was closed. As the user navigates to new windows within the same application, more and more connections are opened, and after a certain number of connections, the application will have enough and then crash. This was a programming error in the template that was used by all developers. The solution was to first test if the cursor is already open in the database, before opening it again.
How do you trace what is happening in the back-end database? Major database providers have GUI tools that help you discover or analyze queries fired against the database. It will show you when people are connecting, disconnecting or unable to connect due to security violations. Many databases also contain some system dictionary tables that can be queried to obtain this information. These traces can sometimes tell the whole story of why something is failing. The query code you retrieve from the trace can help “simplify the search”. You can see from the trace if the program makes a successful connection with the database. You can see how long it takes to execute the query.
To add to principle #2 (don’t be afraid to start…); You can analyze this trace information, although you may not know anything about the details of the application.
Note that these back-end traces can put stress on back-end resources. Don’t let them run unnecessarily long.
Principle number 6. Use fresh eyes.
This is the last principle. Don’t spend too much time on a problem before you ask for help. Help does not have to come from someone more senior than you. The theory is that all you need is a pair of fresh eyes for a fresh perspective and the occasional break to get some fresh air. The other person will watch and then ask a question or two. Sometimes it is very obvious that was missed. Sometimes by answering a question it forces you to think in a new direction. Also, if you spend hours looking at the same piece of code, it’s very easy to start seeing silly mistakes. Many finance balance problems are solved over beer. It may be a change of scenery, and/or a relaxing environment that will pop out the solution. Maybe it’s the fresh oxygen that went to the brain when walking to the pub. Maybe this problem has been discussed with someone else.
After reading this paper, the author hopes that you will try these next time to solve the problem. Hopefully by applying these six principles you will realize the benefits they bring instead of “guessing” your way to a solution.
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