Uzma Raja

Modeling software evolution defects: a time series approach

A robust model reference controller which supplies manipulated variables for controlling a multi-input multi-output process of the type which may not be modelled perfectly consists of a pre-compensator, a diagonal filter, and a post-compensator. The input signals to the robust model reference controller are first projected dynamically into decoupled signals by the pre-compensator. The diagonal filters then filter the decoupled signals individually. The filtered signals are projected back dynamically to the manipulated variables for the controlled process. The filter can easily be tuned to attain the optimal response of the closed-loop system with a given bound of model uncertainty.

Realignment of the physical distribution process in omni-channel fulfillment

Purpose – The purpose of this paper is to identify the realignment of the physical distribution process for store-based retailers in their efforts to integrate the online channel into their business model. Multiple attributes of the physical distribution process are evaluated to identify associations with order fulfillment methods adopted by omni-channel retailers. Design/methodology/approach – A multi-method approach is used which includes qualitative evaluation of 50 interviews of supply chain executives from large retailers. Additionally, secondary data about firm size, store and distribution networks, online sales, distribution configuration, and order delivery options are used. The findings of qualitative analysis are incorporated into a quantitative classification-tree analysis to identify associations among distribution attributes, order fulfillment methods and order delivery services. Findings – Retailers are developing a consistent omni-channel physical distribution process in which stores undert...

Defining and Evaluating a Measure of Open Source Project Survivability

In this paper, we define and validate a new multidimensional measure of Open Source Software (OSS) project survivability, called Project Viability. Project viability has three dimensions: vigor, resilience, and organization. We define each of these dimensions and formulate an index called the Viability Index (VI) to combine all three dimensions. Archival data of projects hosted at SourceForge.net are used for the empirical validation of the measure. An Analysis Sample (n=136) is used to assign weights to each dimension of project viability and to determine a suitable cut-off point for VI. Cross-validation of the measure is performed on a hold-out Validation Sample (n=96). We demonstrate that project viability is a robust and valid measure of OSS project survivability that can be used to predict the failure or survival of an OSS project accurately. It is a tangible measure that can be used by organizations to compare various OSS projects and to make informed decisions regarding investment in the OSS domain.

All complaints are not created equal: text analysis of open source software defect reports

As the use of Open Source Software (OSS) systems increases in the corporate environment, it is important to examine the maintenance process of these projects. OSS projects allow end users to directly submit reports in case of any operational issues. Timely resolution of these defect reports requires effective management of maintenance resources. This study analyzes the usefulness of the textual content of the defect reports as an early indicator of their resolution time. Text Mining techniques are used to categorize defect reports of five OSS projects. Significant variation in the defect resolution time amongst the resulting categories, for each of the sample projects, indicates that a text based classification of defect reports can be useful in early assessment of resolution time before source code level analysis. Such technique can assist in allocation of sufficient maintenance resources to targeted defects and also enable project teams to manage customer expectations regarding defect resolution times.

Managing Resource Allocation and Task Prioritization Decisions in Large Scale Virtual Collaborative Development Projects

Business rules guide information system development and maintenance in the organization. The issue of business rules for enterprise information systems has recently received considerable attention. However, as yet little research has been reported on a systematic approach to business rules management. This paper proposes a business rules management model. In this model, business rules are supported by three types of independent information system components: system setting, database, and procedural module. A business rule can be formalized into one or more elementary rule, and a formalized elementary rule is associated with one and only one information system component. Business rules, system components, and their interconnected relationships can be organized into an XML enabled repository for the system development, customization, and maintenance. An example of artifact of business rules management system can be found in an apartment rental management system. This example is used to illustrate the concept of business rules management. DOI: 10.4018/irmj.2010102604 IGI PUBLISHING This paper appears in the publication, Resources Management Journal, Volume 23, Issue 1 edited by Mehdi Khosrow-Pour

Antecedents of open source software defects: A data mining approach to model formulation, validation and testing

This paper develops tests and validates a model for the antecedents of open source software (OSS) defects, using Data and Text Mining. The public archives of OSS projects are used to access historical data on over 5,000 active and mature OSS projects. Using domain knowledge and exploratory analysis, a wide range of variables is identified from the process, product, resource, and end-user characteristics of a project to ensure that the model is robust and considers all aspects of the system. Multiple Data Mining techniques are used to refine the model and data is enriched by the use of Text Mining for knowledge discovery from qualitative information. The study demonstrates the suitability of Data Mining and Text Mining for model building. Results indicate that project type, end-user activity, process quality, team size and project popularity have a significant impact on the defect density of operational OSS projects. Since many organizations, both for profit and not for profit, are beginning to use Open Source Software as an economic alternative to commercial software, these results can be used in the process of deciding what software can be reasonably maintained by an organization.

Teaching Analytics, Decision Support, and Business Intelligence: Challenges and Trends

Companies are increasingly embracing analytics to enhance business value. Academia is responding to this trend, with innovative curricula in DSS/BI/Analytics providing a variety of degree programs, minors, and certificate programs in online, traditional, and hybrid format. With BI field rapidly evolving, more universities are becoming interested in offering BI courses and programs. This necessitates innovations in BI pedagogy and materials that can best prepare students for the industry demands. Teaching material that incorporates real cases with real data from companies into the pedagogy provides the benefit to students to get high-level BI skills that companies need.

Classification of software patches: a text mining approach

Installation of maintenance patches in operational software systems is a source of significant expenditure and resource consumption. Managers often have to find a balance between publicly announced vulnerabilities and/or possible destabilization of existing applications, while making decisions regarding patch roll out to all systems. We propose a classification scheme for maintenance patches and examine the effects of patch category on the internal characteristics of a software system. Text mining the patch releases of 77 successive versions of the Linux operating system, we extend previous categorization schemes to maintenance patches. This granularity level offers a view of the aggregate nature of the tasks performed in each version. An unsupervised learning technique, cluster analysis associated with Text mining, reveals that there are three identifiable categories in Linux patch files. Based on the maintenance keywords in each category, we label them as: corrective, perfective and adaptive patches. Further analysis of the effects of patch category on the structural complexity and the time to next release indicates that perfective patches are associated with a reduction in the complexity and frequency of patch release. Categorization at the patch level is useful for managers, since changes made to operational software systems are through patches. Determining the nature of a patch can assist managers in planning version roll out and testing criterion. Copyright

Taking stock of organisations’ protection of privacy: categorising and assessing threats to personally identifiable information in the USA

Many organisations create, store, or purchase information that links individuals’ identities to other data. Termed personally identifiable information (PII), this information has become the lifeblood of many firms across the globe. As organisations accumulate their constituencies’ PII (e.g. customers’, students’, patients’, and employees’ data), individuals’ privacy will depend on the adequacy of organisations’ information privacy safeguards. Despite existing protections, many breaches still occur. For example, US organisations reported around 4,500 PII-breach events between 2005 and 2015. With such a high number of breaches, determining all threats to PII within organisations proves a burdensome task. In light of this difficulty, we utilise text-mining and cluster analysis techniques to create a taxonomy of various organisational PII breaches, which will help drive targeted research towards organisational PII protection. From an organisational systematics perspective, our classification system provides a foundation to explain the diversity among the myriad of threats. We identify eight major PII-breach types and provide initial literature reviews for each type of breach. We detail how US organisations differ regarding their exposure to these breaches, as well as how the level of severity (i.e. number of records affected) differs among these PII breaches. Finally, we offer several paths for future research.

Temporal Patterns of Software Evolution Defects: A Comparative Analysis of Open Source and Closed Source Projects

This study examines temporal patterns of software systems defects using the Autoregressive Integrated Moving Average (ARIMA) approach. Defect reports from ten software application projects are analyzed; five of these projects are open source and five are closed source from two software vendors. Across all sampled projects, the ARIMA time series modeling technique provides accurate estimates of reported defects during software maintenance, with organizationally dependent parameterization. In contrast to causal models that require extraction of source-code level metrics, this approach is based on readily available defect report data and is less computation intensive. This approach can be used to improve software maintenance and evolution resource allocation decisions and to identify outlier projects—that is, to provide evidence of unexpected defect reporting patterns that may indicate troubled projects.