Is it time to rethink project success?

The notion of success and failure in software projects are confusing. Failure is often considered in the context of the iron triangle as the inability to meet time, cost and performance constraints. Yet, while there is a consensus around the prevalence of project failure, new projects seem destined to repeat past mistakes. This paper tries to advance the discussion by offering a new perspective for reasoning about the meaning of success and the different types of software project failures. The paper advocates rising beyond the fixation with internal parameters of efficiency. It begins by discussing the limited insights from existing project failure surveys, before offering a four level model addressing the essence of successful delivery and operation in software projects and considering the different measures required in order to utilise richer measurements of success

A good practice guide on the sources and magnitude of uncertainty arising in the practical measurement of environmental noise

A brief introduction to measurement uncertainty, uncertainty budgets, and inter-comparison exercises (repeated measurements), is provided in Chapter 2. The procedure forformulating an uncertainty budget and evaluating magnitudes is outlined in greater detail in Chapter 3. A flow chart summarising this process, and a checklist for the identification of sources of measurement uncertainty are included at the end of the chapter. Two example measurement exercises with corresponding uncertainty budgets are presented in Chapter 4. Some of the more commonly encountered sources of measurement uncertainty are outlined in Chapter5. Where possible, information on magnitudes or pointers to where that information can be found are included. The more important sources of uncertainty are highlighted, and “good practice guidelines” provided to help the practitioner identify means of reducing their effect. Case studies illustrating some of the points made in Chapter 5,and listing of relevant guidelines and further reading are provided in the Appendices

Working Paper: Measuring Job Creation in Private Sector Development

The Donor Committee for Enterprise Development (DCED) Standard offers a best practice by outlining the key elements for practically and credibly estimating the results of Private Sector Development programmes, in a process which can be managed by programmes internally. It involves a few common impact indicators to ensure that donors will be able to add up their results across country programmes. The Standard is being piloted on a multi-agency basis; the DCED invites new programmes to join in adopting the approach

A Systematic Mapping of Factors Affecting Accuracy of Software Development Effort Estimation

Software projects often do not meet their scheduling and budgeting targets. Inaccurate estimates are often responsible for this mismatch. This study investigates extant research on factors that affect accuracy of software development effort estimation. The purpose is to synthesize existing knowledge, propose directions for future research, and improve estimation accuracy in practice. A systematic mapping study (a comprehensive review of existing research) is conducted to identify such factors and their impact on estimation accuracy. Thirty-two factors assigned to four categories (estimation process, estimator’s characteristics, project to be estimated, and external context) are identified in a variety of research studies. Although the significant impact of several factors has been shown, results are limited by the lack of insight into the extent of these impacts. Our results imply a shift in research focus and design to gather more in-depth insights. Moreover, our results emphasize the need to argue for specific design decisions to enable a better understanding of possible influences of the study design on the credibility of the results. For software developers, our results provide a useful map to check the assumptions that undergird their estimates, to build comprehensive experience databases, and to adequately staff design projects

ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information

Requirements elicitation requires extensive knowledge and deep understanding of the problem domain where the final system will be situated. However, in many software development projects, analysts are required to elicit the requirements from an unfamiliar domain, which often causes communication barriers between analysts and stakeholders. In this paper, we propose a requirements ELICitation Aid tool (ELICA) to help analysts better understand the target application domain by dynamic extraction and labeling of requirements-relevant knowledge. To extract the relevant terms, we leverage the flexibility and power of Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural language processing tasks. In addition to the information conveyed through text, ELICA captures and processes non-linguistic information about the intention of speakers such as their confidence level, analytical tone, and emotions. The extracted information is made available to the analysts as a set of labeled snippets with highlighted relevant terms which can also be exported as an artifact of the Requirements Engineering (RE) process. The application and usefulness of ELICA are demonstrated through a case study. This study shows how pre-existing relevant information about the application domain and the information captured during an elicitation meeting, such as the conversation and stakeholders' intentions, can be captured and used to support analysts achieving their tasks.Comment: 2018 IEEE 26th International Requirements Engineering Conference Workshop

Determining the difference between measured and calculated dose to canine oral mucosa during stereotactic radiation therapy using gafchromic™ film

2011 Fall.Includes bibliographical references.Among the therapeutic approaches available to manage canine nasal tumors, radiation therapy is considered the standard of care for achieving improved quality of life and overall survival time for these patients. Long-term local tumor control remains the goal for many radiation therapy protocols applied to patients with canine nasal tumors. Stereotactic radiation therapy (SRT), utilized by Colorado State University Animal Cancer Center (CSU-ACC), delivers maximum dose to the tumor volume, while preferentially sparing the surrounding normal structures. When treating dogs with nasal SRT, there is uncertainty with regard to the actual dose delivered to the oral mucosa due to the anatomical proximity of the tumor and the inherent error of most algorithms in calculating doses at air-tissue interfaces. A canine head phantom, dogs with spontaneously-occurring tumors, and the Gafchromic EBT film analysis system were utilized to measure radiation dose. Further comparison between measured film dose and dose calculated by the Varian Eclipse inverse planning algorithm was conducted. The results from this study demonstrate the high variability of the Analytical Anisotropic Algorithm (AAA) in calculating doses for this particular geometry. The high degree of variability results in uncertainty with regard to the prediction of delivered dose. The differences between measured and calculated doses in both the phantom (mean difference of 104 cGy per fraction, p-value of <0.0001) and the dogs (mean difference of 74 cGy per fraction, p-value of 4.2 x 10-5), suggest that the AAA underestimates the dose delivered to oral mucosa of dogs treated with SRT to manage their nasal tumors. Based upon a dose prescription of 10 Gy tumor dose per fraction in this population of dogs, an oral mucosa dose range of 3.5-6.5 Gy per fraction was measured in 88% of the cases, this range might be considered by clinicians in an effort to estimate the dose delivered to the oral mucosa while treating canine nasal tumors with SRT