PPM based Bayesian Solution in SW Engineering Based on Real Industry Data

Title:PPM based Bayesian Solution in SW Engineering Based on Real Industry Data

Volume: 8 Issue: 1

Author(s): Balwant R. Sharma*, Rajiv Nag, Munish Makkad and Ramjee Prasad

Affiliation:

• Department of Institute and Technology, HMR Institute of Technology & Management, Hamidpur, Delhi,India

Keywords: Bayesian, process performance model, process capability, non numeric input, control chart, three sigma limit.

Abstract: Background and Objective: The success of IT project managers lies in their ability to plan, execute and implement their project in a time bound manner and within optimum cost. The efficient development of a project also requires a defined process of selection of appropriate development methodology, which is absent as on today with unpredictable results.

Methods: It is proposed by the authors that to achieve predictable success for a project as per the set goals, the concept of process performance models can be very useful. The authors who have worked with many mathematical models suggest that these models can be basis for the development of process performance models for forecasting project success as per goals defined. The process performance models implementation helps to monitor the project parameters as well as improvement of Software processes. This methodology of project development based on process performance models is yet to be adopted in IT industry in a disciplined way.

Results and Discussion: These models help to define relation between project variables and enable prediction of the performance of the proposed solution. The Success of a given project based on Bayesian solution for a given network problem which enables the managers to build process performance model for similar problems. The problem discussed in this paper has real life non numeric data from a project of an Indian IT company. Also, the authors have demonstrated how to assess process capability with non-numeric data input. Different mathematical models proposed by the authors to address a solution for a problem at hand have been tested with real industry data for models like Regression, Time series, Queuing Theory, Fuzzy logic etc. This paper discusses only one model just to prove the concept.

Conclusion: The authors suggest that PPMs may be developed in an IT organization for different emerging areas and a library of models can be built and used for future applications. The authors opine that in future in High Maturity Organizations building Process performance models (PPM) may become a essential part of process of project development.

Cite this article as:

Sharma R. Balwant *, Nag Rajiv , Makkad Munish and Prasad Ramjee, PPM based Bayesian Solution in SW Engineering Based on Real Industry Data, International Journal of Sensors, Wireless Communications and Control 2018; 8 (1) . https://dx.doi.org/10.2174/2210327908666180413155652