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Faheem Ahmed

Publications and source records attributed to Faheem Ahmed.

23 records · Page 2Linked to original sources

Myths and Realities about Online Forums in Open Source Software Development: An Empirical Study

The use of free and open source software (OSS) is gaining momentum due to the ever increasing availability and use of the Internet. Organizations are also now adopting open source software, despite some reservations, in particular regarding the provision and availability of support. Some of the biggest concerns about free and open source software are post release software defects and their rectification, management of dynamic requirements and support to the users. A common belief is that there is no appropriate support available for this class of software. A contradictory argument is that due to the active involvement of Internet users in online forums, there is in fact a large resource available that communicates and manages the provision of support. The research model of this empirical investigation examines the evidence available to assess whether this commonly held belief is based on facts given the current developments in OSS or simply a myth, which has developed around OSS development. We analyzed a dataset consisting of 1880 open source software projects covering a broad range of categories in this investigation. The results show that online forums play a significant role in managing software defects, implementation of new requirements and providing support to the users in open source software and have become a major source of assistance in maintenance of the open source projects.

cs.SE↗

Soft Skills and Software Development: A Reflection from the Software Industry

We review the literature relating to soft skills and the software engineering and information systems domain before describing a study based on 650 job advertisements posted on well-known recruitment sites from a range of geographical locations including, North America, Europe, Asia and Australia. The study makes use of nine defined soft skills to assess the level of demand for each of these skills related to individual job roles within the software industry. This work reports some of the vital statistics from industry about the requirements of soft skills in various roles of software development phases. The work also highlights the variation in the types of skills required for each of the roles. We found that currently although the software industry is paying attention to soft skills up to some extent while hiring but there is a need to further acknowledge the role of these skills in software development. The objective of this paper is to analyze the software industry soft skills requirements for various software development positions, such as system analyst, designer, programmer, and tester. We pose two research questions, namely, (1) What soft skills are appropriate to different software development lifecycle roles, and (2) Up to what extend does the software industry consider soft skills when hiring an employee. The study suggests that there is a further need of acknowledgment of the significance of soft skills from employers in software industry.

cs.SE↗

Security Issues in Data Warehouse

Data Warehouse provides storage for huge amounts of historical data from heterogeneous operational sources in the form of multidimensional views, thus supplying sensitive and useful information which help decision-makers to improve the organizations business processes. A data warehouse environment must ensure that data collected and stored in one big repository are not vulnerable. A review of security approaches specifically for data warehouse environment and issues concerning each type of security approach have been provided in this paper.

cs.CR↗

Business Process Mining Approaches: A Relative Comparison

Recently, information systems like ERP, CRM and WFM record different business events or activities in a log named as event log. Process mining aims at extracting information from event logs to capture business process as it is being executed. Process mining is an important learning task based on captured processes. In order to be competent organizations in the business world; they have to adjust their business process along with the changing environment. Sometimes a change in the business process implies a change into the whole system. Process mining allows for the automated discovery of process models from event logs. Process mining techniques has the ability to support automatically business process (re)design. Typically, these techniques discover a concrete workflow model and all possible processes registered in a given events log. In this paper, detailed comparison among process mining methods used in the business process mining and differences in their approaches have been provided.

cs.SE↗

Benchmarking Machine Learning Technologies for Software Defect Detection

Machine Learning approaches are good in solving problems that have less information. In most cases, the software domain problems characterize as a process of learning that depend on the various circumstances and changes accordingly. A predictive model is constructed by using machine learning approaches and classified them into defective and non-defective modules. Machine learning techniques help developers to retrieve useful information after the classification and enable them to analyse data from different perspectives. Machine learning techniques are proven to be useful in terms of software bug prediction. This study used public available data sets of software modules and provides comparative performance analysis of different machine learning techniques for software bug prediction. Results showed most of the machine learning methods performed well on software bug datasets.

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