Designing Software Debuggingwith Multimedia Application

In this paper using the main feature of our proposed Model in its inflection point, we propose a software reliability growth model, which relatively early in the testing and debugging phase, provides accurate parameters estimation, gives a very good failure behavior prediction and enable software developers to predict when to conclude testing, release the software and avoid over testing in order to cut the cost during the development and the maintenance of the software. Two real world experimental data previously analyzed have been used to compare our proposed Early Estimation Logistic Model effectiveness with several pre-existing models.

Program understanding is an important aspect in Software Maintenance and Reengineering. Understanding the program is related to execution behaviour and relationship of variable involved in the program. The task of finding all statements in a program that directly or indirectly influence the value for an occurrence of a variable gives the set of statements that can affect the value of a variable at some point in a program is called a program slice. Program slicing is a technique for extracting parts of computer programs by tracing the programs' control and data flow related to some data item. This technique is applicable in various areas such as debugging, program comprehension and understanding, program integration, cohesion measurement, re-engineering, maintenance, testing where it is useful to be able to focus on relevant parts of large programs. This paper focuses on the various slicing techniques (not limited to) like static slicing, quasi static slicing, dynamic slicing and conditional slicing. This paper also includes various methods in performing the slicing like forward slicing, backward slicing, syntactic slicing and semantic slicing. The slicing of a program is carried out using Java which is a object oriented programming language.

Fixing failed computer programs involves completing two fundamental debugging tasks: first, the programmer has to reproduce the failure; second, s/he has to find the failure cause. Software debugging is the process of locating and correcting erroneous statements in a faulty program as a result of testing. It is extremely time consuming and very expensive. The term debugging collectively refers to fault localization, understanding and correction. Automated tools to locate and correct the erroneous statements in a program can significantly reduce the cost of software development and improve the overall quality of the software. This paper discusses fault localization, program slicing and delta debugging techniques. It identifies statistical fault localization tools such as Tarantula, GZoltar and others such as dbx and Microsoft Visual C++ debugger that provides a snapshot of the program state at various break points along an execution path. In conclusion we note that most software development companies spend a huge amount of resources in testing and debugging. A lot more research need to be conducted to fully automate the debugging process thereby reducing software production cost, time and improve quality.

Fixing failed computer programs involves completing two fundamental debugging tasks: first, the programmer has to reproduce the failure; second, s/he has to find the failure cause. Software debugging is the process of locating and correcting erroneous statements in a faulty program as a result of testing. It is extremely time consuming and very expensive. The term debugging collectively refers to fault localization, understanding and correction. Automated tools to locate and correct the erroneous statements in a program can significantly reduce the cost of software development and improve the overall quality of the software. This paper discusses fault localization, program slicing and delta debugging techniques. It identifies statistical fault localization tools such as Tarantula, GZoltar and others such as dbx and Microsoft Visual C++ debugger that provides a snapshot of the program state at various break points along an execution path. In conclusion we note that most software development companies spend a huge amount of resources in testing and debugging. A lot more research need to be conducted to fully automate the debugging process thereby reducing software production cost, time and improve quality.

—According To current technology there is lots of future scope in area of internet of things, Video/audio processing etc. For these are there is need of lots of sensor and multimedia design which is use full in these area. We also know in present era every system work on battery power only. So there is need of fast and energy aware system which will reduce the battery consumption issue and run system for long time. As we know in present stage ever one doing real time image/video transmission. Due to real time may be some time there is image quality will decrease so for improvement of those real time image there is need of De-noising approach which is well known as Smooth filter. In this paper basically we did a comparative study about the existing different types of De-noising filter.