Applying Forensic Analysis Factors to Construct a Systems Dynamics Model for Failed Software Projects

Forensic analysis of failed software projects can aid in managerial understanding of the issues and challenges of delivering a successful project. The factors and their interrelationships causing software project failure are not well understood or researched with a strong forensic-analytic approach. Previous papers have not adequately explored how dynamic interaction of multiple factors can lead to critical events that ultimately portend eventual failure. This paper proposes the development of a System Dynamics (SD) model that will represent the key factors, their dynamic interactions, and the influence of exogenous events in causing software project failure. Forensic data will be used as inputs to the SD model to assist managers in understanding the factor interactions, the importance of individual factor metrics, as well as the sequence of interactions in causing possible software project failure. Outcomes from the model will include a likelihood of software project failure, possible factor sequences leading to failure, and suggestions of remediation activities that might mitigate eventual failure

15 Years of Enterprise Architecting at HICSS: Revisiting the Critical Problems

The Enterprise Architecture (EA) minitrack has been a mainstay of HICSS for the past 15 years. The methodology, tools, and processes of enterprise architecting have evolved during that period. In 2005, Kaisler and Armour identified some critical challenges in modeling, management, and maintenance for EA that needed attention to ensure a viable technical discipline. Over 15 years, we have accepted 93 papers for presentation. Reviewing these papers and drawing up on our experience over the past 15 years, we conclude that some progress has been made, some challenges remain to be addressed, and some new challenges have emerged. This paper revises existing challenges and identifies additional challenges to be addressed in the next 10 years

Introduction to Big Data and Analytics: Concepts, Methods, Techniques, and Application Minitrack

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Big Data and Analytics: Issues and Challenges for the Past and Next Ten Years

In this paper we continue the minitrack series of papers recognizing issues and challenges identified in the field of Big Data and Analytics, from the past and going forward. As this field has evolved, it has begun to encompass other analytical regimes, notably AI/ML systems. In this paper we focus on two areas: continuing main issues for which some progress has been made and new and emerging issues which we believe form the basis for near-term and future research in Big Data and Analytics. The Bottom Line: Big Data and Analytics is healthy, is growing in scope and evolving in capability, and is finding applicability in more problem domains than ever before

Big Data Redux: New Issues and Challenges Moving Forward

As of the time of this writing, our HICSS-46 proceedings article has enjoyed over 520 Google Scholar citations. We have published several HICSS proceedings, articles and a book on this subject, but none of them have generated this level of interest. In an effort to update our findings six years later, and to understand what is driving this interest, we have downloaded the first 500 citations to our article and the corresponding citing article, when available. We conducted an in-depth literature review of the articles published in top journals and leading conference proceedings, along with articles with a high volume of citations. This paper provides a brief summary of the key concepts in our original paper and reports on the key aspects of interest we found in our review, and also updates our original paper with new directions for future practice and research in big data and analytics

Birthing the computer: from relays to vacuum tubes

Birthing the Computer: From Relays to Vacuum Tubes is the first in a multi-volume series on historical computing machines. This series will span the development of computer systems from the Zuse machines of the early 1930s to about 1995 when microprocessors began to be commoditized. Each volume will focus on a range of technologies, or a class of machines or a particular vendor, and will describe the hardware of the machines and its peripherals, the operating system and system software, and its influence upon programming languages. This volume begins with the Zuse machines which were constructed from relays, but contained the basic elements of a computer system, namely input, computing engine, and output. Early machines from Atanasoff and Berry, Aiken, Stibitz, and IBM are described. The transition from relays to vacuum tubes increased speed and performance significantly, and led to the first true computers in ENIAC, EDSAC, and EDVAC which used paper tape and Williams tubes for I/O and storage. These machines were built by universities.Several early machines were purpose built such as Colossus and BINAC, and created with government support and industrial know-how. By the mid-to-late '50s, computing machines were being built by universities (the SSEM, Whirlwind, and IAS machines), governments (the NBS SEAC and SWAC, and several other machines), and industry (the UNIVAC series and the English Electric DEUCE). Most of these machines were constructed using the von Neumann architecture, and represent an evolution of thinking in how computing machines were to operate along with some innovative ideas in software and programming languages. By the end of the 1950s, the design, development, programming and use of computing machines were in full ferment as many new ideas were proposed, many different machines were designed and some were constructed. Computing machines became a commercial enterprise. Governments receded from building machines to levying requirements and funding construction, while universities continued to explore new architectures, new operating systems, and new programming languages