This is the actual datasheet for the game details table and it shows all the data being structured neatly so it can be shown easily on the user interface.
Test 2
This is the screenshot that shows my user interface for my member details. These are important details as it allows the employees to get in touch with members for example to inform about a new game.
This is the actual datasheet for the members and as the datasheet has a lot of fields and records it is much more efficient to have a user interface to store and present the data.
Test 3
This is my third user interface which shows the details of he employee’s which are important for the system to recognise and also other people can search for the information about the staff that they require.
This is the datasheet of the employee’s table and shows that again there is a lot of information and this is also shown on the user interface so the user interface is correct in displaying all of the information.
Test 4
This is the user interface for my Sales form and this is the table that is the main table which is connected to everything else. As you can see the data can be entered easily enough and shows on the interface.
As you can also see on the datasheet the data is shown there and is shown correctly so that the user can identify and search the data for their certain needs.
Test 5
This is my last user interface for the system and it is the Stock Form where it shows all the details about the stock.
This is the datasheet of the stock table and you can see that the user interface works because the data is the same on the datasheet as on the form.
Labelled printouts of all reports
Reports- Test 1
This is a screenshot of my first report which shows the results of my query of Xbox 360 games. This report shows that the query has worked because it is actually displaying the results.
Test 2
This is the second report showing results of the query that was searching for members that lived in Greenford and ealing. Again you can see that this report works along with the query because the results of the query are displayed on the report.
This is the report that shows the query on employees that are males and shows the exact data.
Test 3
This is a report showing the results of a query that is searching for all the sales of games that have a quantity of 10 sales.
Labelled printouts of all Mail Merge
This is the start of the mail merge where i have selected all the fields that i need in order to send the mail merge letter.
I then choose the list of mailings that i want to send to and then choose the data. Then i click on preview results , and then should get me exactly what i need for my mail merge.
Labelled printouts of all Mailing Labels
This is the start of my mailing labels where i put the fields that i want like forname and surname which i can then use for the mailing labels.
When i have chosen my data sources that i want , i can then preview the results and if the right information comes up then that means the data is right.
Evidence of Input Testing [3]
Provide evidence in the form of printouts of the testing that you have done on validation. This should include:
Labelled printouts of all error messages
This is the validation rule that doesn’t not allow the user to enter in data like the age that is under 18 for members.
As you can see when i have entered in correct data no error message comes up saying the data typed is wrong.
When i have entered in the data that is wrong against the validation rule that is set, a message comes up telling me the message i had customly put there which says age not valid. So this was wrong data.
This validation rule is done on male and female t check that all the data entered in the Gender Column is either male or female and nothing else. It check to see if my data is correct.
This is a screenshot that shows when the correct data has been entered, no error message comes up and the data is allowed.
This is a screenshot that shows when the wrong data is entered into the Gender column, a error message comes up saying that the Gender is not recognized which is the own personal message that comes up. It tells me that the data is not valid.
Critical Feedback [4]
Describe the Results [2 marks]
Expected Results [1]
- Games that are on Xbox 360
By just looking visually at the data, i can expect to see at least 9 games that are on xbox 360 which are: correct
Fifa 09
Call of duty 4
Pro evolution soccer
Halo 3
Need for speed
Harry potter
The sims 2
Battlefield
Bioshock
- Members who live in certain place.
As i just look at the data of the member details i expect to see members that live in Greenford come up. These should be: wrong
Mounisha Alwaheedy
Meena Byrant
Yasmin Begum
Aimee Crashaw
Rhys Lewis
Michael Lynch
- Employees That are of a certain gender
When i looked at the employee table and looked at the employees that were of a certain gender as male i expected at least 17 results to come out in the query or test. wrong
- Sales of games with the same quantity.
As i looked at the sales table, i expected to see at least 7 games with the same quantity of 10 sales each. These sale of games were: correct
Harry Potter
The sims 2
Battlefield
Fifa 08
Tiger woods 09
Championship Manager 09
Fifa 09
- Employees who make a sale.
I wanted to see which employees made which sale with which game using a relational query. By just looking at the data i expected to see at least 17 results. Wrong
- Games that were sold on ps3
I looked at this data and saw that there should be 10 games that were sold on ps3 all for the same price. c
Far cry 2
Grand theft auto IV
Saints row 2
Resistance 2
Fifa 08
Need for speed pro
Nba live 09
Hellboy
Mercenaries 2
Wwe smackdown 2009
- Games that had the same amount of quantity
I was looking visually at all the games in the stock table that had the same number of stock and i expected these games:
Fifa 09
Bioshock
Fifa street 3
Farcry 2
Wwe smackdown 2009
Mario kart
Age of empires II
Actual vs Expected Results [2]
You need to compare the Actual Results with the Expected Results.
- Games that are on xbox 360
My actual results matched the expected results that i expected because it was a simple query with not a large amount of data.
- Members who live in certain place
I expected 6 names to come up, however i was wrong as 12 came up. I was wrong because when i looked at the data i only saw members living in Greenford but i had set the query to Greenford and Ealing so there was more names to come up.
- Employees that are of a certain gender
When i looked at the data i expected 17 results to come up but only 16 did. This was because there was another criteria set which only allowed employees over 22 to be in the test so as a result one name who was another 22 was omitted from the results.
- Sales of games with the same quantity
The actual results matched the expected results because there wasn’t any other criteria set and the data was quite a small list.
- Employees who make a sale
When i visually looked at all the data i saw that there should have been 17 employees but there were only 6 because criteria had been added so that made the data decrease.
- Games that were sold on ps3
I looked at the data that had games that were sold on os3 and the actual results matched the expected results because again there was no criteria set or any validations.
- Games that had the same amount of quantity
The actual results matched the expected results because again there was no criteria was set and the data was quite unique and small meaning it was easy to expect what data would come up.
Choice of Test Data [3]
Normal data: I entered in normal data into the data that was being entered in for price value. I entered in a currency of £29.99 and the system expected it. I expected the system to expect it because the data type was set to currency so the data i entered was correct in this value.
Invalid data: In the members data table, i entered a value for a member which was under 18 and was 15. When i entered this data in, a error message came up saying that incorrect data had been entered and told me to type in a new value. The message was due to the validation rule that had been set.
Extreme Data: In the members data table, i entered in a value of 18 for age when the validation rule was set for <18. I chose this data because it was a extreme value for checking if ages up to 18 were allowed for the members and i expected it to be allowed which it was.
Normal Data In the games table, i entered a value in the quantity column of 35. The validation rule on this column was set to 20<Quantity<80, so i expected the system to allow the data that i entered because it was include within the range of values.
Extreme Data: In the stock table, i entered a value for the quantity field that was 5. The validation rule would only me to put data from above 5 so i decided to choose this data because it was an extreme value for checking if all games with quantity of 5 or above were listed there.
Invalid Data: In the members table i entered in a value that wasn’t value for the gender field like “man”. I chose this value because it was invalid data and it should generate the error message which was set by the validation rule.
Normal Data: In the members table, in the gender fields i entered a value that was either male or female. Seeing as my validation rules were primed only to accept male and female values, i expected the system to accept my data which it did.
Invalid Data: In the employee table, i entered a text value in the age and because the age field only takes number data values, the error message came up saying the data entered was incorrect.
Extreme Data: In the game table, a validation rules was set for games not to be higher then 35 in quantity, and when i entered this data because i wanted to see if this value was accepted, the system did accept it.
Normal Data: When entering prices i entered just the 4 digits, e.g 40.00, as i set the data type to currency it would recognize and automatically change it, as it was normal data
GCSE ICT - Coursework Task 2 Name: Ashley Koya