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Thanks Arlan. You solved my doubt.
Thanks Arlan, my doubt was because the information of the catalog is harded-coded, and changes to move that catalog to a BD aren’t permited, so it is needed to get the information (Catalog) from hard-code, which I counted as a read. Is it correct?
It sound easy nevertheless, It is not as simple, for example:
I have 2 measurements, both of them will be developed using the same technology (COBOL) the first one “inquiry the name of the user”
* Receive the UserId (E)
* Read the name of the user (R)
* Show the name of the user (X)
Apparently 3 CFP
Nevertheles with the same technology It is required a complex report
* Receive an file with 100 fields about transations (E)
* Calculate a lot of values to conciliate the information for the new report, it is necesary apply at least 25 rules, it is not necesary to read additional information (0 CFP)
* As the calculations are made they are saved in a temporary file.
* When the report is ready it is send to another application. At the end the file has 120 fields with the new information and data transformation, all the fields describe the same object (transactions), so apparetly is only one exit (X)
Apparently 2 CFP
As far as we know the reason for which the measurement are very important for the industry is because allows us use it for estimations, I mean to be able to convert the CFPs in hours, one option could be have a value (in hours) for the simple CFP and another for complex CFP with the same technology (what someone proposed at the last conference of metrics in Mexico). Nevertheless we fall again in the dilemma about which is funtionality simple and which is complex. I would like to know your comments? Thanks for advance!
First of all thanks for your answere. I understand, nevertheless, it seems that we could find in the same functional process CFPs which correspond to difficult software and other which correspond to moderate software, for instance:
It is necessary to show the following report, where:
The “large Name” is Calculated like this:
* Large Name = Name + Last Name + mother’s last name
The CURP is calculated like this:
* the 2 first characters of the name
* plus the first character of the last name
* plus the first character of the mother’s last name
* plus the birthdate* plus the Number of the City of birth
The email is calculated like this:
* the name
* plus the character “.”
* plus the last name
* plus the phase “@empresa.com”
The Salary is calculated like this:
SalaryWithoutTaxes = Salary – (Salary * 0.16)
Period to get a report (Start Date, Finish Date) => Entry
Information of the Employee (Name, Last Name, mother’s last name, Birthdate, number of City of Birth, Salary) => Read
Manipulation to get Large Name => There is not CFP
Manipulation to get CURP => There is not CFP
Manipulation to get email => There is not CFP
Manipulation to get SalaryWithoutTaxes => There is not CFP
Show the Period (Start Date, Finish Date) => Exit
Show report (Large Name, CURP, email, SalaryWithoutTaxes) => Exit
The last two exit will not have the same degree of dificulty when the software must be developed
Could you help me with your comments?29/07/2019 at 19:05 in reply to: Data groups with the same attibutes in the same funtional process #12219
I still have a doubt about the entry for this functional process, because it is a process which must be executed in a specific time (date, and hour) which the business user indicated, the process must not be execute in other time, because that could impact the server operation, and no other input data is necessary. In fact, this is the case of example 2, pp. 64
E Entry to start the process
R IdTransaction, Description, Amount [Transaction]
X IdTransaction, Description, Amount [Transaction]02/07/2019 at 03:07 in reply to: Data groups with the same attibutes in the same funtional process #12206
First of all, Thanks for your answere.
In this case the information with the transactions are in a table in a Data base.
So, I suppose the entry with the time is correct, right?
Thanks Arlan. I understand that to obtain the measurement of the FURs, I must consider only the movements of data and the time to create tables, add or delete fields must be considered independently.13/05/2019 at 18:37 in reply to: Different calculations for different values of a data attribute #11640
Yes, thanks you very much Symons07/05/2019 at 19:05 in reply to: Different calculations for different values of a data attribute #11632
Not, only change the Formula, if indicator is equal to “B” must be different that if the indicator is equal to “C” or if indicator is equal to “D” using differents attributes of the data group that previusly was read.
It is clear, thanks for your answere
It is not clear for me why an Entry is counted
E Output to PDF or Printer (don’t count X for PDF or Printer, since it is the same for screen output)
As far as I know, an entry is from a Funtional User to a Functional Process. So, in order to count an entry my functional Process needs to be a Functional user from another Functional Process, What could be the other functional process? And Given that a functional Process has as minimal 2 movements, what could be the other movement?
In advance thank you for your answer
Only an aditional question, Is it the the same in the entry?
For example: IdEmployee, IdDepartment, Cedula are atributes of the table “Employee”
The functional user gives IdEmployee, IdDepartment (1 Entry)
If IdDeparment = “System” ask for Cedula (1 Message, 1 Exit)
The funcional user gives Cedula (doesn’t count)
The funcional process save the Cedula (1 Write)
Must be count IdEmploye, IdDepartment and Cedula as the same group?
Yes it is clear, thank you very much for your answere!
I didn’t write my doubt correctly, I try again.
I have a table which name is “Candidates”, it has the following attributes: IdEmployee, Marker1, Marker2 and Marker3
I need to measure the following:
• A functional user provides the information about an employee (IdEmployee, Name, Salary, City, Department)
1 Entry, data group Employee
• If Salary > 1000 then Marker1 = 1 (in a persistent storage, table “Candidate”)
1 Write, data group “Candidate with salary > 1000” with attributes IdEmpoyee, Marker1
• If City=”CDMX” then Marker2 = 1 (in a persistent storage, table “Candidate”)
1 Write, data group “Candidate from CDMX” with attributes IdEmpoyee, Marker2
• If Department = “System” then Marker3 = 1 (in a persistent storage, table “Candidate”)
1 Write, data group “Candidate from System Deparment” with attributes IdEmpoyee, Marker3
Based in the Measurement Manual 4.0.2, pp. 52, point a) sets of data attributes that have different frequencies of occurrence describe different objects of interest. The measure could be 1 Entry and 3 writes, which means 4 CFP ¿Is that correct?
Or due to Marker1, Marker2 and Marker3 are fields of the table “Candidate”, I should count only one write, even when they save in different moment?