Khaironi Yatim Sharif

Exploring Key Factors of Pilot Projects in Agile Transformation Process Using a Grounded Theory Study

Changing development approach from disciplined to agile methods is an organizational mutation that requires many issues to be considered to increase its chance of success. Selecting an appropriate pilot project as initial project that is going to be done through an Agile method is a critical task. Due to the impact of such a pilot project on successful Agile transformation, understanding its critical factors helps organizations choose the most suitable project to start Agile transition. Conducting a Grounded Theory, showed that organization should considered some key factors of a pilot: Criticality, Duration, Size and Required resources. Besides these factors, the results showed that organization should be aware of the risk of successful pilot project in their next Agile projects. The study also showed that pilot selection mostly is done by Agile coaches or is forced by customer.

An Exploratory Study on Managing Agile Transition and Adoption

Software companies are replacing traditional software development methods with Agile methods due to coping with inherent problems of traditional methods. Due to the different nature of traditional and Agile methods, adaptation to Agile methods is not a simple process and needs to be managed in a sustainable way. In recent years, several studies have conducted on investigation of Agile migration journey, but less effort on identifying the serious managerial attentions in Agile transition process. Conducting a Grounded Theory in context of Agile software development, showed various aspects of the transition to be considered in order to having a successful change management process. This paper shows the important role of the emergent managerial attentions on success of Agile transition and adoption process.

Wi-fi fingerprint database construction using Chebyshev wavelet functions

In this research we propose a new approach of constructing Wi-Fi fingerprints database using Chebyshev wavelet functions. Proposed algorithm combines the reference data collection procedure with path-loss prediction. Our algorithm requires only a few samples to be collected in a given region, and thus significantly reduces the calibration time. Next, the collected reference samples are used to construct area specific path-loss prediction function using Chebyshev wavelets. Once we have the path-loss function, we can predict the signal strength values at any point of the target area. One of the advantages of proposed algorithm is that it does not require any detailed information about target area, i.e. location of wireless access points, number of walls (floors, obstructions) between the transmitter and reference points and etc.