Use of IBM Collaborative Lifecycle Management Solution to Demonstrate Traceability for Small, Real-World Software Development Project

The Standish Group Study of 1994 showed that 53 percent of software projects failed outright and another 31 percent were challenged by extreme budget and/or time overrun. Since then different responses to the high rate of software project failures have been proposed. SEI’s CMMI, the ISO’s 9001:2000 for software development, and the IEEE’s JSTD-016 are some examples of such responses. Traceability is the one common feature that these software development standards impose. Over the last decade, software and system engineering communities have been researching subjects such as developing more sophisticated tooling, applying information retrieval techniques capable of semi-automating the trace creation and maintenance process, developing new trace query languages and visualization techniques that use trace links, applying traceability in specific domains such as Model Driven Development, product line systems and agile project environment. These efforts have not been in vain. The 2012 CHAOS results show an increase in project success rate of 39% (delivered on time, on budget, with required features and functions), and a decrease of 18% in the number of failures (cancelled prior to completion or delivered and never used). Since research has shown traceability can improve a project’s success rate, the main purpose of this thesis is to demonstrate traceability for a small, real-world software development project using IBM Collaborative Lifecycle Management. The objective of this research was fulfilled since the case study of traceability was described in detail as applied to the design and development of the Value Adjustment Board Project (VAB) of City of Jacksonville using the scrum development approach within the IBM Rational Collaborative Lifecycle Management Solution. The results may benefit researchers and practitioners who are looking for evidence to use the IBM CLM solution to trace artifacts in a small project

Toward an Effective Automated Tracing Process

Traceability is defined as the ability to establish, record, and maintain dependency relations among various software artifacts in a software system, in both a forwards and backwards direction, throughout the multiple phases of the project’s life cycle. The availability of traceability information has been proven vital to several software engineering activities such as program comprehension, impact analysis, feature location, software reuse, and verification and validation (V&V). The research on automated software traceability has noticeably advanced in the past few years. Various methodologies and tools have been proposed in the literature to provide automatic support for establishing and maintaining traceability information in software systems. This movement is motivated by the increasing attention traceability has been receiving as a critical element of any rigorous software development process. However, despite these major advances, traceability implementation and use is still not pervasive in industry. In particular, traceability tools are still far from achieving performance levels that are adequate for practical applications. Such low levels of accuracy require software engineers working with traceability tools to spend a considerable amount of their time verifying the generated traceability information, a process that is often described as tedious, exhaustive, and error-prone. Motivated by these observations, and building upon a growing body of work in this area, in this dissertation we explore several research directions related to enhancing the performance of automated tracing tools and techniques. In particular, our work addresses several issues related to the various aspects of the IR-based automated tracing process, including trace link retrieval, performance enhancement, and the role of the human in the process. Our main objective is to achieve performance levels, in terms of accuracy, efficiency, and usability, that are adequate for practical applications, and ultimately to accomplish a successful technology transfer from research to industry

Blockchain for requirements traceability: A qualitative approach

Blockchain technology has emerged as a “disruptive innovation” that has received significant attention in academic and organizational settings. However, most of the existing research is focused on technical issues of blockchain systems, overlooking the organizational perspective. This study adopted a grounded theory to unveil the blockchain implementation process in organizations from the lens of blockchain experts. The results revealed three main categories: key activities, success factors, and challenges related to blockchain implementation in organizations, the latter being identified as the core category, along with 17 other concepts. Findings suggested that the majority of blockchain projects stop at the pilot stage and outlined organizational resistance to change as the core challenge. According to the experts, the following factors contribute to the organizational resistance to change: innovation–production gap, conservative management, and centralized mentality. The study aims to contribute to the existing blockchain literature by providing a holistic and domain-agnostic view of the blockchain implementation process in organizational settings. This can potentially encourage the development and implementation of blockchain solutions and guide practitioners who are interested in leveraging the inherent benefits of this technology. In addition, the results are used to improve a blockchain-enabled requirements traceability framework proposed in our previous paper.publishedVersio

Modelling Fresh Strawberry Supply "From-Farm-to-Fork" as a Complex Adaptive Network

 The purpose of this study is to model and thereby enable simulation of the complete business entity of fresh food supply. A case narrative of fresh strawberry supply provides basis for this modelling. Lamming et al. (2000) point to the importance of discerning industry-specific product features (or particularities) regarding managing supply networks when discussing elements in "an initial classification of a supply network" while Fisher (1997) and Christopher et al. (2006, 2009) point to the lack of adopting SCM models to variations in products and market types as an important source of SCM failure. In this study we have chosen to move along a research path towards developing an adapted approach to model end-to-end fresh food supply influenced by a combination of SCM, system dynamics and complex adaptive network thinking...