Software Testing Tool Integration of Personnel Safety System
Personnel Safety System or PSS system required fully automated testing for the integration of four tools of software-testing on two split computer platforms. The tools of software testing provided the functions as following:
1) PLC real-time I/O simulation,
2) HMI to the panels of users control,
3) GUI testing for applications of Windows-based,
4) Tracking of defect, test planning of graphical, and testing of batch,
5) PLCs of Allen Bradley verification of fault code, and
6) GE PLCs fault code verification.
The tools of software chosen to perform the system functions as above were:
1. HMI application of Programmable Industrial Control Simulation (PICS),
2. A functional test tool of WinRunner,
3. A graphical test planning tool of Test Director,
4. An download tool of Allen Bradley software and PLC5/30 fault code verifier of RSLogic, and
5. The software of Eclipse State logic of GE Fanuc PLC90/70 fault code verifier.
Modeling of Statistical
This article is not modeling software reliability but rather an application of some methods of SRE (software reliability engineering). Although the practitioner’s flag has been increased, it is still required to affirm some basic assumptions and situations that are typical of the SRE analysis. The analysis of reliability is efficiently possibility theory used to the failures modeling. The random variable concept is essential to possibility. The mainly general random changeable of interest to the reliability engineering field is the time to failure.
Usually, failure data is collected in two main formats: failures number per unit time and time between failures. The data gathered for this article falls in the count category of failure. These attributes are as follows:
• Domain is Time, either continuous or discrete.
• Category is the total failures number that can be practiced in immeasurable time is either limited or unlimited. The number distribution of the failures practiced by time “t”.
• Type is 2 vital types of statistical model that you reflect on are binomial and poisson.
The distribution of binomial failure has a permanent number of faults at the beginning, N, while for the alpha of Poisson type is the faults concluding number that could be exposed over an unlimited amount of time. It should be declared that for this analysis to have a realistic presentation, the software has to have developed to the point that extended changes are not being regularly finished. Appropriate any model to a specified data set engages definite limitations, not the smallest amount of which is being responsive of the theory underlying the fundamental model builds.