Technical Report: Feedback-Based Generation of Hardware Characteristics

ABSTRACT In large complex server-like computer systems it is difficult to characterise hardware usage in early stages of system development. Many times the applications running on the platform are not ready at the time of platform deployment leading to postponed metrics measurement. In our study we seek answers to the questions: (1) Can we use a feedbackbased control system to create a characteristics model of a real production system? (2) Can such a model be sufficiently accurate to detect characteristics changes instead of executing the production application? The model we have created runs a signalling application, similar to the production application, together with a PIDregulator generating L1 and L2 cache misses to the same extent as the production system. Our measurements indicate that we have managed to mimic a similar environment regarding cache characteristics. Additionally we have applied the model on a software update for a production system and detected characteristics changes using the model. This has later been verified on the complete production system, which in this study is a large scale telecommunication system with a substantial market share

Explainability Design Patterns in Clinical Decision Support Systems

This paper reports on the ongoing PhD project in the field of explaining the clinical decision support systems (CDSSs) recommendations to medical practitioners. Recently, the explainability research in the medical domain has witnessed a surge of advances with a focus on two main methods: The first focuses on developing models that are explainable and transparent in its nature (e.g. rule-based algorithms). The second investigates the interpretability of the black-box models without looking at the mechanism behind it (e.g. LIME) as a post-hoc explanation. However, overlooking the human-factors and the usability aspect of the explanation introduced new risks following the system recommendations, e.g. over-trust and under-trust. Due to such limitation, there is a growing demand for usable explanations for CDSSs to enable the integration of trust calibration and informed decision-making in these systems by identifying when the recommendation is correct to follow. This research aims to develop explainability design patterns with the aim of calibrating medical practitioners trust in the CDSSs. This paper concludes the PhD methodology and literature around the research problem is also discussed

On Test Design

Testing is the dominating method for quality assurance of industrial software. Despite its importance and the vast amount of resources invested, there are surprisingly limited efforts spent on testing research, and the few industrially applicable results that emerge are rarely adopted by industry. At the same time, the software industry is in dire need of better support for testing its software within the limited time available. Our aim is to provide a better understanding of how test cases are created and applied, and what factors really impact the quality of the actual test. The plethora of test design techniques (TDTs) available makes decisions on how to test a difficult choice. Which techniques should be chosen and where in the software should they be applied? Are there any particular benefits of using a specific TDT? Which techniques are effective? Which can you automate? What is the most beneficial way to do a systematic test of a system? This thesis attempts to answer some of these questions by providing a set of guidelines for test design, including concrete suggestions for how to improve testing of industrial software systems, thereby contributing to an improved overall system quality. The guidelines are based on ten studies on the understanding and use of TDTs. The studies have been performed in a variety of system domains and consider several different aspects of software test. For example, we have investigated some of the common mistakes in creating test cases that can lead to poor and costly testing. We have also compared the effectiveness of different TDTs for different types of systems. One of the key factors for these comparisons is a profound understanding of faults and their propagation in different systems. Furthermore, we introduce a taxonomy for TDTs based on their effectiveness (fault finding ability), efficiency (fault finding rate), and applicability. Our goal is to provide an improved basis for making well-founded decisions regarding software testing, together with a better understanding of the complex process of test design and test case writing. Our guidelines are expected to lead to improvements in testing of complex industrial software, as well as to higher product quality and shorter time to market

Is Common Test Data the Solution to Poor Quality? : Solving the Right Problem – An Analysis of a Public Health Information System

This paper reports our initial findings regarding the state of testing of software in the Swedish public health information system. At present, the system is only available through a black-box interface, i.e. through the GUI. This and other issues related to politics, management and organization indicate that much work is needed in order for the software to have the quality level expected by a safety-critical system. The proposed solution by the public health organization for raising the quality is to use an independent test database. Based on our initial understanding of the problem, we argue that there might be other solutions that would perhaps be more cost-effective and have a stronger impact on the quality of the system. Our main contribution lies in the data analysis, where we have collected the problems and suggested alternative cost-saving solutions.CBIC II

Experiments with Component Tests to Improve Software Quality

Abstract I

Impediments in Agile Software Development: An Empirical Investigation

Abstract. In this paper, we report on a case study on development impediments encountered in the early phase of a transformation to agile methods in a software development organization. Drawing from literature and anecdotal evidence, it was assumed that the majority of the impediments were related to software testing. To investigate this, we performed a case study seeking qualitative and quantitative evidence from task boards, interviews, and observations. Our analysis indicates that the major challenge in the transformation undertaken by the studied organization was coordination and communication in the large, and that testing was the major challenge only when the unit of analysis was restricted to the teams in the department