Software Measurement Activities in Small and Medium Enterprises: an Empirical Assessment

An empirical study for evaluating the proper implementation of measurement/metric programs in software companies in one area of Turkey is presented. The research questions are discussed and validated with the help of senior software managers (more than 15 years’ experience) and then used for interviewing a variety of medium and small scale software companies in Ankara. Observations show that there is a common reluctance/lack of interest in utilizing measurements/metrics despite the fact that they are well known in the industry. A side product of this research is that internationally recognized standards such as ISO and CMMI are pursued if they are a part of project/job requirements; without these requirements, introducing those standards to the companies remains as a long-term target to increase quality

Improving utility of brain tumor confocal laser endomicroscopy: objective value assessment and diagnostic frame detection with convolutional neural networks

Confocal laser endomicroscopy (CLE), although capable of obtaining images at cellular resolution during surgery of brain tumors in real time, creates as many non-diagnostic as diagnostic images. Non-useful images are often distorted due to relative motion between probe and brain or blood artifacts. Many images, however, simply lack diagnostic features immediately informative to the physician. Examining all the hundreds or thousands of images from a single case to discriminate diagnostic images from nondiagnostic ones can be tedious. Providing a real-time diagnostic value assessment of images (fast enough to be used during the surgical acquisition process and accurate enough for the pathologist to rely on) to automatically detect diagnostic frames would streamline the analysis of images and filter useful images for the pathologist/surgeon. We sought to automatically classify images as diagnostic or non-diagnostic. AlexNet, a deep-learning architecture, was used in a 4-fold cross validation manner. Our dataset includes 16,795 images (8572 nondiagnostic and 8223 diagnostic) from 74 CLE-aided brain tumor surgery patients. The ground truth for all the images is provided by the pathologist. Average model accuracy on test data was 91% overall (90.79 % accuracy, 90.94 % sensitivity and 90.87 % specificity). To evaluate the model reliability we also performed receiver operating characteristic (ROC) analysis yielding 0.958 average for the area under ROC curve (AUC). These results demonstrate that a deeply trained AlexNet network can achieve a model that reliably and quickly recognizes diagnostic CLE images.Comment: SPIE Medical Imaging: Computer-Aided Diagnosis 201

How reliable are systematic reviews in empirical software engineering?

BACKGROUND – the systematic review is becoming a more commonly employed research instrument in empirical software engineering. Before undue reliance is placed on the outcomes of such reviews it would seem useful to consider the robustness of the approach in this particular research context. OBJECTIVE – the aim of this study is to assess the reliability of systematic reviews as a research instrument. In particular we wish to investigate the consistency of process and the stability of outcomes. METHOD – we compare the results of two independent reviews under taken with a common research question. RESULTS – the two reviews find similar answers to the research question, although the means of arriving at those answers vary. CONCLUSIONS – in addressing a well-bounded research question, groups of researchers with similar domain experience can arrive at the same review outcomes, even though they may do so in different ways. This provides evidence that, in this context at least, the systematic review is a robust research method

Bringing Relationship Marketing Theory into B2B Practice: The B2B-RP Scale and the B2B-RELPERF Scorecard

This study presents a new measurement scale to assess the performance of a relationship between two firms. The Business-to-Business Relationship Performance (B2B-RP) scale is presented as a high order concept. When tested in a sample of nearly 400 SMEs purchasing managers operating in a B2B e-marketplace, our findings reveal that greater relationship performance results in better 1) relationship policies and practices, 2) relationship commitment, 3) trust in the relationship, 4) mutual cooperation, as well as 5) satisfaction with the relationship. The multi-dimensional scale shows strong evidence of reliability as well as convergent, discriminant and nomological validity. Findings also reveal that B2B relationship performance is positively and significantly associated with loyalty. While building on this scale, the authors develop the B2B-RP Scorecard intended to be included in periodic reports. At the managerial level, both the scale and the scorecard are expected to help disclose relationship performance, and act as useful instruments for periodic planning, management, controlling, and improvement of B2B relationships.Relationship Performance; Relationship Marketing; B2B-RP Scale; B2B-RELPERF Scorecard; Electronic Markets

A Tripartite Framework for Leadership Evaluation

The Tripartite Framework for Leadership Evaluation provides a comprehensive examination of the leadership evaluation landscape and makes key recommendations about how the field of leadership evaluation should proceed. The chief concern addressed by this working paper is the use of student outcome data as a measurement of leadership effectiveness. A second concern in our work with urban leaders is the absence or surface treatment of race and equity in nearly all evaluation instruments or processes. Finally, we call for an overhaul of the conventional cycle of inquiry, which is based largely on needs analysis and leader deficits, and incomplete use of evidence to support recurring short cycles within the larger yearly cycle of inquiry