Revival of Complementary and Alternative Herbal Medicines

Herbal medicines, complementary or alternative medicines is a wide term for the therapies that are not part of standard care but it has many theories regarding efficacy based on personal experiences, history and common knowledge. It has long been used since ancient times since the beginning of human civilization. Its use had caught much attention in the early 1800s, with the development in the science of chemistry, a new era in pharmacotherapeutics and the use of active chemical ingredients in plants which were known to produce favorable therapeutic effects, were explored, active compounds were extracted, purified and their structure was revealed. This advancement paved the way towards modern pharmaceutical therapy. The modern drugs are based on these herbal medicines, after extracting the active and pure chemical compounds. Pharmacokinetics and physicochemical properties of the active ingredients was explored. It lead to the better understanding of efficacy and safety profile of these drugs and first choice for treatment of various diseases. At the same time, the herbal medicines were considered as secondarily important. After approximately two centuries, the use of herbal medicines have seen a revival globally both in developing as well as developed countries. In the past few years, the practice of using herbal medicines as an alternative and complementary health medicine has gained more importance. Herbal medicines are common for treatment of various ailments including cancer, digestive disorders, pain related disorders, neuropathic ailments and cardiac arrhythmias etc. Even it has been used by pregnant females and mostly perceived as safe. Its use has gained more attraction due to its ‘natural’ approach and lesser side effects. Their use if often overlooked but physicians should pay attention to these medicines. There is lack of familiarity, standardization of the drug components, unproven therapeutic effects in various diseases, unexplored toxicology, pharmacokinetics, drug-drug interactions, and compatibility in patients with varying medical, genetic and demographic history. There are serious concerns regarding the safety, efficacy and quality of herbal products and nutraceuticals. Accidental contamination and deliberate adulteration are assumed to be the main cause of the side effects. Much of the herbal medical knowledge is scattered in different regions of the world and mostly available at family, community and local level and mostly in any native languages. There is need of coherent sources, knowledge, and exploration of these medicines across the world. The herbal medicine has varying diversity in different geological regions and they should be investigated. There should be a regional or national body to control and approve the herbal medicines. Proper documentations on these medicines and food supplements should also be done.

Automated Test Data Generation for Model Transformation Testing

Models and their automated transformations play a critical role in Model Driven Engineering (MDE). A significant challenge in testing model transformations is the automated generation of input test models. This involves generating meta-model instances that satisfy constraints defined on the meta-model which includes the constraints on metaelements and the multiplicity constraints. The problem becomes more challenging when the goal is to generate test models that cover specific paths of the transformation code - a common task in structural testing. The thesis proposes a novel search-based test model generation approach for structural testing of model transformations. The approach generates test models to achieve the desired structural coverage of the transformation code. The proposed test model generation strategy considers the constraints specified at the meta-model level and the multiplicity cardinalities of relationships between meta-elements to guide the generation of valid instances of the meta-model. The proposed strategy relies on a fitness function that utilizes the approach level and branch distance to generate instances that can cover the target branch of the transformation code. The approach proposes a number of heuristics as branch distance functions that solve model transformation predicates. A tool Model Transformation Testing Environment (Motter) is developed that automates the proposed approach. Motter takes the source and input meta-models as input and generates instances of test model that provide the required code coverage, for example, branch coverage of the model transformation code. The current implementation of the tool supports two widely used transformation languages, Atlas Transformation Language (ATL) and MOFScript. The thesis empirically evaluates the proposed approach on two transformations case studies, which are implemented in ATL and MOFScript. The case study in ATL is the popular benchmark Class2RDBMS model-to-model transformation case study, and the case study in MOFScript is a model-to-text industrial scale Real-Time Embedded Systems Test Simulation (RTES) code generator. For the empirical evaluation, four different widely search heuristics: Genetic Algorithm (GA), (1+1) Evolutionary Strategy/Algorithm (EA), Alternative Variable Method (AVM), and Random Search (RS) are tested in the comparative study. The result of the empirical evaluation shows that the proposed approach is successful in achieving the desired branch coverage for the selected transformation case studies and that the AVM significantly outperforms other algorithms. AVM has shown promising results in studies focusing on constraints solving, however it has not been used before for the generation of test cases to provide structural testing of model transformations. The result achieved by the AVM in the experiments are aligned with its previously reported performance as it successfully generates test cases and outperforms other algorithms in terms of the number of branches it can cover for both the case studies.