Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration

Testing in Continuous Integration (CI) involves test case prioritization, selection, and execution at each cycle. Selecting the most promising test cases to detect bugs is hard if there are uncertainties on the impact of committed code changes or, if traceability links between code and tests are not available. This paper introduces Retecs, a new method for automatically learning test case selection and prioritization in CI with the goal to minimize the round-trip time between code commits and developer feedback on failed test cases. The Retecs method uses reinforcement learning to select and prioritize test cases according to their duration, previous last execution and failure history. In a constantly changing environment, where new test cases are created and obsolete test cases are deleted, the Retecs method learns to prioritize error-prone test cases higher under guidance of a reward function and by observing previous CI cycles. By applying Retecs on data extracted from three industrial case studies, we show for the first time that reinforcement learning enables fruitful automatic adaptive test case selection and prioritization in CI and regression testing.Comment: Spieker, H., Gotlieb, A., Marijan, D., & Mossige, M. (2017). Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration. In Proceedings of 26th International Symposium on Software Testing and Analysis (ISSTA'17) (pp. 12--22). AC

Early events in ovarian oncogenesis

Ovarian cancer represents the most lethal of the gynecological neoplasms. The molecular and genetic events associated with early ovarian oncogenesis are still largely unknown, thus contributing to the lack of reliable biomarkers for disease detection. Since the majority of ovarian tumors are diagnosed at an advanced stage, the availability of early ovarian cancer tissue samples for molecular analyses is very limited. In this review, problems encountered in the study of early ovarian cancer are presented, along with the controversies concerning precursor lesions and stepwise progression towards ovarian malignancy. Experimental modeling in the development of ovarian cancer is also described, as well as genetic and epigenetic alterations associated with early ovarian cancer. Lastly, examples of technological advances in the study of early ovarian cancer are discussed. Hopefully, the increasing knowledge about molecular and genetic events involved in the early stages of ovarian tumorigenesis will provide the basis for management of ovarian cancer in the future

On Silence and the Reestablishment of Non-Western Connections

In Forum: Chinese Feminism under (Self-)Censorship: Practice and Knowledge Production.Non peer reviewe

Master of Science

thesisComparison of data gathered in an electronic medical record (EMR) database on Type 2 Diabetes Mellitus (T2DM) patients age 65 years and older with oral antidiabetics (OAD) agent prescription and recorded body mass index (BMI)/weight was performed. A retrospective review of the General Electric Centricity Medical Quality Improvement Consortium (MQIC) research database containing the ambulatory health records of US patients was conducted. T2DM patients age 65 and older were identified by diagnosis, OAD prescription or both. Sixmonths of continuous OAD activity was required; 395 days pre-index-date (index datewas defined by first OAD prescription) clinical activity was required. Two BMI and weight readings were mandated, at baseline, closest to index date and follow-up, closest to 6 months after initiation of OAD activity. A historical, longitudinal cohort design was used and data were analyzed using analysis of variance (ANOVA) with Tukey test for adjustment of the differences in the means between the groups for continuous variables; Pearson's Chi-square test was used to test association for categorical variables. The overall mean age for all of the OAD groups was 72.7 years. The values of the baseline diastolic blood pressure (DBP) differed (p=0.0009), as well as age (p< 0.001); DBP indicated patients were in Hypertension Stage 1. The baseline A1C level was shown to be statistically significant between the groups (p< 0.001) with the highest mean value in sulfonylureas group (7.7). Significant differences between the OAD groups were also found in respect to race and smoking status (p=0.004 and < 0.0001). In comparison between the baseline and the follow-up values, statistical significance was found in both of the outcomes and a drop of 0.7 BMI units was initiated among all of the OAD groups. The overall mean BMI value among all of the OAD groups was 29.08 kg/m². The change in BMI after 6 months of monotherapy demonstrated that meglitinides had the biggest decrease in BMI (-1.27), followed by the metformin group (-1.06) and the sulfonylureas showed the least BMI drop (-0.14). Weight as the secondary outcome variable demonstrated an average 3.97 lb weight loss between all of the OAD groups. Major weight loss was found in the meglitinides users (-7.82lb), pursued by the metformin group (-6.41lb); the sulfonylureas group reported the least weight loss (-0.89lb). EMR data demonstrated an association between the OAD user and BMI/weight and associated conditions consistent with elderly T2DM patients in a real-world setting. The likelihood of weight loss was somewhat consistent with the previous literature, except in the case of the TZD group, where the literature showed the expected weight gain and this study does not support these findings

Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach

Using game theory we investigate a new approach to formulate and solve optimal tolls with a focus on different policy objectives of the road authority. The aim is to gain more insight into determining optimal tolls as well as into the behavior of users after tolls have been imposed on the network. The problem of determining optimal tolls is stated and defined using utility maximization theory, including elastic demand on the travelers’ side and different objectives for the road authority. Game theory notions are adopted regarding different games and players, rules and outcomes of the games played between travelers on the one hand and the road authority on the other. Different game concepts (Cournot, Stackelberg and monopoly game) are mathematically formulated and the relationship between players, their payoff functions and rules of the games are defined for very simplistic cases. The games are solved for different scenarios and different objectives for the road authority, using the Nash equilibrium concept. Using the Stackelberg game concept as being most realistic for road pricing, a few experiments are presented illustrating the optimal toll design problem subject to different pricing policies considering different objectives of the road authority. Results show different outcomes both in terms of optimal tolls as well as in payoffs for travelers. There exist multiple optimal solutions and objective function may have a non- continuous shape. The main contribution is the two-level separation between of the users from the road authority in terms of their objectives and influences.

Metabolic engineering of Corynebacterium glutamicum for the production of succinate and 2,3-butanediol

The depletion of fossil raw materials and the environmental pollution associated with their processing motivated the development of alternative methods for production of fuels and bulk chemicals. The solution offered by White Biotechnology is to produce these chemicals from biomass, a renewable resource rich in carbohydrates, using microorganisms as biocatalysts. Corynebacterium glutamicum is a well-known industrial bacterium employed for decades in the large scale production of L-amino acids. In this work, the potential of C. glutamicum as a bio-platform for the production of succinate and 2,3-butanediol was explored.(...

Proinflammatory Effects of C-Peptide in Different Tissues

Atherosclerosis is well known as an inflammatory disease that can lead to clinical complications such as heart attack or stroke. C-peptide as a cleavage product of proinsulin is in the last few decades known as an active peptide with a number of different effects on microvascular and macrovascular complications in type 2 diabetic patients. Patients with insulin resistance and early type 2 diabetes show elevated levels of C-peptide in blood. Several last findings demonstrated deposition of C-peptide in the vessel wall in ApoE-deficient mice and induction of local inflammation. Besides that, C-peptide has proliferative effects on human mesangial cells. This review discusses recently published proinflammatory effects of C-peptide in different tissues

Industry–Academia Research Collaboration and Knowledge Co-creation: Patterns and Anti-patterns

Increasing the impact of software engineering research in the software industry and the society at large has long been a concern of high priority for the software engineering community. The problem of two cultures, research conducted in a vacuum (disconnected from the real world), or misaligned time horizons are just some of the many complex challenges standing in the way of successful industry–academia collaborations. This article reports on the experience of research collaboration and knowledge co-creation between industry and academia in software engineering as a way to bridge the research–practice collaboration gap. Our experience spans 14 years of collaboration between researchers in software engineering and the European and Norwegian software and IT industry. Using the participant observation and interview methods, we have collected and afterwards analyzed an extensive record of qualitative data. Drawing upon the findings made and the experience gained, we provide a set of 14 patterns and 14 anti-patterns for industry–academia collaborations, aimed to support other researchers and practitioners in establishing and running research collaboration projects in software engineering.publishedVersio

C-Peptide: A New Mediator of Atherosclerosis in Diabetes

Diabetes type 2 and insulin resistance are the risk factors for cardiovascular disease. It is already known that atherosclerosis is an inflammatory disease, and a lot of different factors are involved in its onset. C-peptide is a cleavage product of proinsulin, an active substance with a number of effects within different complications of diabetes. In this paper we discuss the role of C-peptide and its effects in the development of atherosclerosis in type 2 diabetic patients