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Wednesday, 16 May 2012
Software Challenge
When looking at the history of anything it is very tempting to focus on the competitive aspects only, e.g. the great wars, the clash of civilizations, etc. Unfortunately, all too often this is presented as the essence of history, and although that may be a story that is easy to understand or remember (or memorize), it may also miss the underlying fundamental changes that are happening all the time, in times of war and peace. Software history is no exception, as this picture attests:
But are there any other stories to tell besides the epic battle between the Microsoft empire and the open-source barbarians? It is hard to believe that all significant advances in computing come from hardware alone. Can you find any data measuring the improvement in software over time? This question is intentionally vague and because of that I'll have to accept any metric you can find. Examples could include measuring software quality (lack of bugs or defects) or productivity: are those who write the software become more productive over time either individually or as a group?
What is the impact of new operating systems, programming languages, scripting languages, etc. on productivity or quality? In other words, is there any evidence that they enable software developers to produce more or better code? Has anyone figured out a way to quantify this? Send me any document that has numbers in it in the form of tables or figures (published or unpublished).
Another point of view is from algorithmic efficiency or computational complexity. Can we trace the improvement of algorithms from the early days of computing to the present? And how does that compare to the improvement in hardware, e.g. would you rather have an old (and very slow) computer running a modern (fast) algorithm or the latest (and fastest) machine running a primitive algorithm?
Of course, there are many different algorithms for all kinds of tasks, having different tradeoffs. But to keep things simple, what can we see if we just focus on one attribute, say, speed (which is also called "time complexity"). For example, consider sorting algorithms (arranging a bunch of numbers in increasing order). This website has some demos illustrating that the speed difference can be quite substantial! Could we plot their performance (speed) versus the time they were invented? If yes, can we see a trend?
Of course, sorting algorithms may not be the most interesting ones. There are many other kinds of algorithms in computer science, machine learning, data mining, pattern recognition, or artificial intelligence. The coolest thing is that one doesn't have to understand all the technical details in order to research this, only a few key concepts and the notation. If you are interested in these questions, I'll gladly bring you up to speed on that! :)
When looking at the history of anything it is very tempting to focus on the competitive aspects only, e.g. the great wars, the clash of civilizations, etc. Unfortunately, all too often this is presented as the essence of history, and although that may be a story that is easy to understand or remember (or memorize), it may also miss the underlying fundamental changes that are happening all the time, in times of war and peace. Software history is no exception, as this picture attests:
But are there any other stories to tell besides the epic battle between the Microsoft empire and the open-source barbarians? It is hard to believe that all significant advances in computing come from hardware alone. Can you find any data measuring the improvement in software over time? This question is intentionally vague and because of that I'll have to accept any metric you can find. Examples could include measuring software quality (lack of bugs or defects) or productivity: are those who write the software become more productive over time either individually or as a group?
What is the impact of new operating systems, programming languages, scripting languages, etc. on productivity or quality? In other words, is there any evidence that they enable software developers to produce more or better code? Has anyone figured out a way to quantify this? Send me any document that has numbers in it in the form of tables or figures (published or unpublished).
Another point of view is from algorithmic efficiency or computational complexity. Can we trace the improvement of algorithms from the early days of computing to the present? And how does that compare to the improvement in hardware, e.g. would you rather have an old (and very slow) computer running a modern (fast) algorithm or the latest (and fastest) machine running a primitive algorithm?
Of course, there are many different algorithms for all kinds of tasks, having different tradeoffs. But to keep things simple, what can we see if we just focus on one attribute, say, speed (which is also called "time complexity"). For example, consider sorting algorithms (arranging a bunch of numbers in increasing order). This website has some demos illustrating that the speed difference can be quite substantial! Could we plot their performance (speed) versus the time they were invented? If yes, can we see a trend?
Of course, sorting algorithms may not be the most interesting ones. There are many other kinds of algorithms in computer science, machine learning, data mining, pattern recognition, or artificial intelligence. The coolest thing is that one doesn't have to understand all the technical details in order to research this, only a few key concepts and the notation. If you are interested in these questions, I'll gladly bring you up to speed on that! :)
Tuesday, 15 May 2012
These tips not only survive but also advance you in your software testing career. Make sure you follow them:
Tip #1) Written communication
– I repeatedly saying this on many occasions that keep all things in written communication. No verbal communication please. This is applicable to all instructions or tasks given to you by your superior. No matter how friendly your lead or manager is but keep things in emails or documents.
Tip #2) Try to automate daily routine tasks
– Save time and energy by automating daily routine task no matter how small those tasks are.
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Like in any other software development life cycle, Testing too requires some important factors to develop and maintain for continuous process improvement. One such factor is Team Building. While building a right team, focus should be on the following key elements:
Roles and Responsibilities
It is very important for the team members to understand what they are supposed to do. This was quite often not communicated or discussed with the team. Before start of a project, the team members must be explained on the typical tasks which they will be performing on a daily basis for their respective roles. Be it a tester or a test lead, setting the expectations and explaining what is expected out of them will give correct results without unnecessary delays or errors.
This article explains what are CMM levels and how to achieve these CMM levels for QA processes, explained with best examples.
For any process whether it is a QA process, development process or any non-technical process, there are levels of its maturity. By levels of maturity we mean that the level of formality and processes improvement, like ad-hoc processes – to formally defined steps – to managed result metrics – to optimization of the processes.
CMM (Capability Maturity Model)
is process based model which is used to assess the maturity of an organization for different domains. Although this model is normally termed as the software development model but eventually it was used for other processes as well like QA and testing.
I am glad to share
“Manual Testing Help” eBook prepared by one of our readers. The content of this eBook is very useful to understand manual testing concepts, testing methodologies and preparing for software testing interviews.
Here are some of the topics covered in this book:
- Fundamentals
of software testing
- When
defects gets introduced in SDLC?
- Why does
software have defects?
- What is
Verification?
- What is
Validation?
- Software
Testing Techniques
- Continue
reading →
A couple of months ago, I wrote about
database testing strategies. It covered the aspect that is entirely related to the execution of test cases. It was all about black-box testing of a database. There is another important aspect of DB testing activity which we will cover in this article.
As a tester, you have to test the ‘Examination Results’ module of the website of a university. Consider the whole application has been integrated and it is in ‘Ready for Testing’ state. ‘Examination Module’ is linked with ‘Registration’, ‘Courses’ and ‘Finance’ modules. Assume that you have adequate information of
Continue reading →
In
previous articlewe discussed on how WAPT pro performance testing tool can be used for website performance testing. But if you want to generate much higher load on web site you must use the latest x64 Load Engine release from WAPT team. This article and ultimately the testing tool is very useful for performance testers.
This is in fact most crucial test for time critical applications such as stock management systems which gets refreshed every minute creating huge load on
Continue reading →
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