Awais Rashid

Lancaster University, Lancaster, England, United Kingdom

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Publications (183)32.66 Total impact

  • Matthew Edwards · Awais Rashid · Paul Rayson
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    ABSTRACT: As an increasing amount of crime takes on a digital aspect, law enforcement bodies must tackle an online environment generating huge volumes of data. With manual inspections becoming increasingly infeasible, law enforcement bodies are optimising online investigations through data-mining technologies. Such technologies must be well designed and rigorously grounded, yet no survey of the online data-mining literature exists which examines their techniques, applications and rigour. This article remedies this gap through a systematic mapping study describing online data-mining literature which visibly targets law enforcement applications, using evidence-based practices in survey making to produce a replicable analysis which can be methodologically examined for deficiencies.
    No preview · Article · Sep 2015 · ACM Computing Surveys
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    ABSTRACT: Since the environment for businesses is becoming more competitive by the day, business organizations have to be more adaptive to environmental changes and are constantly in a process of optimization. Fundamental parts of these organizations are their business processes. Discovering and understanding the actual execution flow of the processes deployed in organizations is an important enabler for the management, analysis, and optimization of both, the processes and the business. This has become increasingly difficult since business processes are now often dynamically changing and may produce hundreds of events per second. The basis for this paper is the Constructs Competition Miner (CCM): A divide-and-conquer algorithm which discovers block-structured processes from event logs possibly consisting of exceptional behaviour. In this paper we propose a set of modifications for the CCM to enable dynamic business process discovery of a run-time process model from a stream of events. We describe the different modifications with a particular focus on the influence of individual events, i.e. ageing techniques. We furthermore investigate the behaviour and performance of the algorithm and the ageing techniques on event streams of dynamically changing processes.
    Full-text · Chapter · Jan 2015
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    Nathan Weston · Francois Taiani · Awais Rashid
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    ABSTRACT: The key contribution of Aspect-Oriented Programming (AOP) is the encapsulation of crosscutting concerns in aspects, which facilities modular reasoning. However, common methods of introducing aspects into the system, incorporating features such as implicit control-flow, mean that the ability to discover interactions between aspects can be compromised. This has profound implications for developers working on fault-tolerant systems. We present an analysis for aspects which can re- veal these interactions, thus providing insight into positioning of error detection mechanisms and outlining candidate containment units. We also present Aida, an implementation of this analysis for the AspectJ language.
    Preview · Article · Jan 2015
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    ABSTRACT: Business processes of some domains are highly dynamic and increasingly complex due to their dependencies on a multitude of services provided by various providers. The quality of services directly impacts the business process's efficiency. A first prerequisite for any optimization initiative requires a better understanding of the deployed business processes. However, the business processes are either not documented at all or are only poorly documented. Since the actual behaviour of the business processes and underlying services can change over time it is required to detect the dynamically changing behaviour in order to carry out correct analyses. This paper presents and evaluates the integration of the Dynamic Construct Competition Miner (DCCM) as process monitor in the TIMBUS architecture. The DCCM discovers business processes and recognizes changes directly from an event stream at run-time. The evaluation is carried out in the context of an industrial use-case from the eHealth domain. We will describe the key aspects of the use-case and the DCCM as well as present the relevant evaluation results.
    Full-text · Conference Paper · Jan 2015
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    Matthew Edwards · Awais Rashid · Paul Rayson
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    ABSTRACT: Public user profile information is a common feature of modern websites. These profiles can provide a valuable resource for investigators tracing digital artefacts of crime, but current approaches are limited in their ability to link identities across different platforms. We address this through a service-independent model of user profile information, grounded in the details visible on a number of the most-frequented sites on the web. Building on this, we report the details most widespread across platforms and the number of features visible on each site, thus highlighting details of use to both privacy researchers and investigators attempting to cross-link profiles.
    Full-text · Conference Paper · Sep 2014
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    Full-text · Conference Paper · Sep 2014
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    ABSTRACT: Today’s fast and competitive markets require businesses to react faster to changes in its environment, and sometimes even before the changes actually happen. Changes can occur on almost every level, e.g. change in demand of customers, change of law, or change of the corporate strategy. Not adapting to these changes can result in financial and legal consequences for any business organisation. IT-controlled business processes are essential parts of modern organisations which motivates why business processes are required to efficiently adapt to these changes in a quick and flexible way. This requirement suggests a more dynamic handling of business processes and their models, moving from design-time business process models to run-time business process models. One general approach to address this problem is provided by the community of models@run.time, in which models reflect the system’s current state at any point in time and allow immediate reasoning and adaptation mechanisms. This paper examines the potential role of business process models at run-time by: (1) discussing the state-of the art of both, business process modelling and models@run.time, (2) reflecting on the nature of business processes at run-time, and (3) most importantly, highlighting key research challenges that need addressing to make this step.
    Full-text · Chapter · Jun 2014
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    ABSTRACT: Businesses are becoming increasingly globally interconnected and need to continuously adapt to global market changes and trends in order to stay competitive. Business processes are fundamental parts and drivers of these globally connected organizations which is why their management, analysis, and optimization are of utmost importance. Discovering and understanding the actual execution flow of processes deployed in your organization is an important enabler for these tasks. However, this has become increasingly difficult since business processes are now mostly distributed over different systems, highly dynamic, and may produce thousands of events per second which may conform to a number of different formats. These particular challenges are currently not specifically accounted for in the research field of Process Discovery. In order to address these challenges, this paper presents a concept for scalable dynamic process discovery, which is a scalable solution for identifying and keeping up with the evolution of dynamic, collaborative business processes. Furthermore, a framework for this concept is proposed along with the requirements and implementation details for the involved components and models.
    Full-text · Conference Paper · May 2014
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    ABSTRACT: The increasing levels of child sex abuse (CSA) media being shared in peer-to-peer (P2P) networks pose a significant challenge for law enforcement agencies. Although a number of P2P monitoring tools to detect offender activity in such networks exist, they typically rely on hash value databases of known CSA media. Such an approach cannot detect new or previously unknown media being shared. Conversely, identifying such new previously unknown media is a priority for law enforcement - they can be indicators of recent or on-going child abuse. Furthermore, originators of such media can be hands-on abusers and their apprehension can safeguard children from further abuse. The sheer volume of activity on P2P networks, however, makes manual detection virtually infeasible. In this paper, we present a novel approach that combines sophisticated filename and media analysis techniques to automatically flag new previously unseen CSA media to investigators. The approach has been implemented into the iCOP toolkit. Our evaluation on real case data shows high degrees of accuracy while hands-on trials with law enforcement officers highlight iCOP's usability and its complementarity to existing investigative workflows.
    No preview · Conference Paper · May 2014
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    ABSTRACT: Since the environment for businesses is becoming more competitive by the day, business organizations have to be more adaptive to environmental changes and are constantly in a process of optimization. Fundamental parts of these organizations are their business processes. Discovering and understanding the actual execution flow of the processes deployed in organizations is an important enabler for the management, analysis, and optimization of both, the processes and the business. This has become increasingly difficult since business processes are now often dynamically changing and may produce hundreds of events per second. The basis for this paper is the Constructs Competition Miner (CCM): A divide-and-conquer algorithm which discovers block-structured processes from event logs possibly consisting of exceptional behaviour. In this paper we propose a set of modifications for the CCM to enable scalable dynamic business process discovery of a run-time process model from a stream of events. We describe the different modifications and carry out an evaluation, investigating the behaviour of the algorithm on event streams of dynamically changing processes.
    Full-text · Conference Paper · Jan 2014
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    ABSTRACT: Conflict identification in Aspect-Oriented Requirements Engineering (AORE) is an integral step toward resolving conflicting dependencies between requirements at an early stage of the software development. However, to date there has been no work supporting detection of conflicts in a large set of textual requirements without converting texts into an alternative representation (such as models or formal specification) or direct stakeholder involvement. Here, we present EA-Analyzer, an automated tool for identifying conflicts directly in aspect-oriented requirements specified in natural language text. This chapter is centered on a case study-based discussion of the accuracy of the tool. EA-Analyzer is applied to the Crisis Management System, a case study used as an established benchmark in several areas of aspect-oriented research. © Springer-Verlag Berlin Heidelberg 2013. All rights are reserved.
    No preview · Article · Nov 2013
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    ABSTRACT: This chapter presents a methodology for identification of crosscutting concerns in textual requirements along with its supporting tool EA-Miner. This chapter discusses how EA-Miner uses natural language processing techniques in aspect identification and structuring using a requirements level feature model as an example. The process is illustrated using the Car Crash case study. © Springer-Verlag Berlin Heidelberg 2013. All rights are reserved.
    No preview · Article · Nov 2013
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    ABSTRACT: Mutation testing is a test selection criterion that relies on the assumption that test cases which can reveal artificial faults in the software are also good to reveal the real ones. It helps to expose faults which would go otherwise unnoticed. This criterion has been shown to be a promising means to deal with testing-related specificities of contemporary programming techniques such as Aspect-Oriented Programming. However, to date the few initiatives for customising mutation testing for aspect-oriented (AO) programs show either limited coverage with respect to the range of simulated faults, or a need for both adequate tool support and proper evaluation in regard to properties like application cost and effectiveness. This article tackles these limitations by describing a comprehensive mutation-based testing approach for programs written in AspectJ, which represents the most investigated AO programming language to date. The approach encompasses the definition of a set of mutation operators for AspectJ-specific constructs and the implementation of a tool that automates the approach. The results of a preliminary evaluation study show that the mutation operators are able to simulate faults that may not be revealed by pre-existing, non-mutation-based test suites. The results also suggest that the approach seems not to overwhelm the testers and hence represents a step towards the practical fault-based testing of AspectJ-like programs.
    No preview · Article · Sep 2013 · Science of Computer Programming
  • Pauline Anthonysamy · Phil Greenwood · Awais Rashid
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    ABSTRACT: A proposed method for mapping privacy policy statements to privacy controls can help providers improve data management transparency, thereby increasing user trust.
    No preview · Article · Jun 2013 · Computer
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    ABSTRACT: The Isis toolkit offers the sophisticated capabilities required to analyze digital personas and provide investigators with clues to the identity of the individual or group hiding behind one or more personas.
    No preview · Article · Apr 2013 · Computer
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    ABSTRACT: When reflecting upon driving system requirements such as security and availability, software architects often face decisions that have a broadly scoped impact on the software architecture. These decisions are the core of the architecting process because they typically have implications intertwined in a multitude of architectural elements and across multiple views. Without a modular representation and management of those crucial choices, architects cannot properly communicate, assess and reason about their crosscutting effects. The result is a number of architectural breakdowns, such as misinformed architectural evaluation, time‐consuming trade‐off analysis and unmanageable traceability. This paper presents an architectural documentation approach in which aspects are exploited as a natural way to capture widely‐scoped design decisions in a modular fashion. The approach consists of a simple high‐level notation to describe crosscutting decisions, and a supplementary language that allows architects to formally define how such architectural decisions affect the final architectural decomposition according to different views. On the basis of two case studies, we have systematically assessed to what extent our approach: (i) supports the description of heterogeneous forms of crosscutting architecture decisions, (ii) improves the support for architecture modularity analysis, and (iii) enhances upstream and downstream traceability of crosscutting architectural decisions. Copyright © 2012 John Wiley & Sons, Ltd.
    No preview · Article · Mar 2013 · Software Practice and Experience
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    ABSTRACT: One of the aims of Aspect-Oriented Requirements Engineering is to ad- dress the composability and subsequent analysis of crosscutting and non-crosscutting concerns during requirements engineering. A composition definition explicitly rep- resents interdependencies and interactions between concerns. Subsequent analysis of such compositions helps to reveal conflicting dependencies that need to be resolved in requirements. However, detecting conflicts in a large set of textual aspect-oriented requirements is a difficult task as a large number of explicitly defined interdependen- cies need to be analyzed. This paper presents EA-Analyzer, the first automated tool for identifying conflicts in aspect-oriented requirements specified in natural-language text. The tool is based on a novel application of a Bayesian learning method. We present an empirical evaluation of the tool with three industrial-strength requirements documents from different domains and a fourth academic case study used as a de facto benchmark in several areas of the aspect-oriented community. This evaluation shows that the tool achieves up to 93.90 % accuracy regardless of the documents chosen as the training and validation sets.
    Full-text · Article · Mar 2013 · Automated Software Engineering
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    Matthew Edwards · Awais Rashid
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    ABSTRACT: The volume of illegal material on file-sharing networks poses a challenge for investigators attempting to police such networks. We propose a novel approach that automates the resource intensive task of identifying previously unknown files of interest amongst hundreds of thousands of files shared on such net-works. We also describe how this approach could be used to identify clusters of peers that might be closely related to each other, either as part of a syndicate, or as multiple personae of the same individual. Our approach is based on the collaborative filtering techniques typically used in recommender systems. In this study we find that we can successfully make use of collaborative filtering techniques to find new media belonging to specific categories of interest to an investigation of a peer-to-peer network, without having to examine filenames or file contents. We also find evidence that distance metrics from collaborative filtering could be useful in the clustering and identification of peers on file-sharing networks. Additionally, we describe an unsuccessful attempt at using collaborative filtering to predict the future file-sharing behaviour of peers.
    Full-text · Article · Dec 2012
  • Phil Greenwood · Awais Rashid · James Walkerdine
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    ABSTRACT: Online social networks are now common place in day-to-day lives. They are also increasingly used to drive social action initiatives, either led by government or communities themselves (e.g., SeeClickFix, LoveLewisham.org, mumsnet). However, such initiatives are mainly used for crowd sourcing community views or coordinating activities. With the changing global economic and political landscape, there is an ever pressing need to engage citizens on a large-scale, not only in consultations about systems that affect them, but also involve them directly in the design of these very systems. In this paper we present the UDesignIt platform that combines social media technologies with software engineering concepts to empower communities to discuss and extract high-level design features. It combines natural language processing, feature modelling and visual overlays in the form of “image clouds” to enable communities and software engineers alike to unlock the knowledge contained in the unstructured and unfiltered content of social media where people discuss social problems and their solutions. By automatically extracting key themes and presenting them in a structured and organised manner in near real-time, the approach drives a shift towards large-scale engagement of community stakeholders for system design.
    No preview · Article · Jun 2012 · Proceedings - International Conference on Software Engineering
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    ABSTRACT: The collection of representative corpus samples of both child language and online (CMC) language varieties is crucial for linguistic research that is motivated by applications to the protection of children online. In this paper, we present an extensive survey of corpora available for these two areas. Although a significant amount of research has been undertaken both on child language and on CMC language varieties, a much smaller number of datasets are made available as corpora. Especially lacking are corpora which match requirements for verifiable age and gender metadata, although some include self-reported information, which may be unreliable. Our survey highlights the lack of corpus data available for the intersecting area of child language in CMC environments. This lack of available corpus data is a significant drawback for those wishing to undertake replicable studies of child language and online language varieties.
    No preview · Article · Jan 2012 · International Journal of Corpus Linguistics

Publication Stats

4k Citations
32.66 Total Impact Points

Institutions

  • 1998-2015
    • Lancaster University
      • School of Computing and Communications
      Lancaster, England, United Kingdom
  • 2008
    • Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
      München, Bavaria, Germany
  • 2006
    • Universidade Federal do Rio Grande do Norte
      • Department of Computer Science and Applied Mathematics
      Natal, Rio Grande do Norte, Brazil
  • 2002
    • Universität Paderborn
      • Department of Computer Science
      Paderborn, North Rhine-Westphalia, Germany
  • 1999
    • Technische Universiteit Eindhoven
      • Department of Mathematics and Computer Science
      Eindhoven, North Brabant, Netherlands