报告时间： 2018年11月27日9：30- 11：30，13：30- 16：30
Prof. dr. MarjanMernik, University of Maribor, Faculty of Electrical Engineering and Computer Science, Slovenia
Title: Formal and Practical Aspects of Domain-Specific Languages: Recent Developments
Domain-specific languages (DSLs) assist a software developer (or end-user) in writing a program using idioms that are similar to the abstractions found in a specific problem domain. Indeed, the enhanced software productivity and reliability benefits that have been reported from DSL usage are hard to ignore and DSLs are flourishing. However, tool support for DSLs is lacking when compared to the capabilities provided for standard General-Purpose Languages (GPLs). For example, support for unit testing of a DSL program, as well as DSL debuggers, are rare. A Systematic Mapping Study (SMS) has been performed to better understand the DSL research field, identify research trends, and any possible open issues. In this talk I will first introduce DSLs by discussing when and how to develop DSLs, then results from SMS will be presented. In the second part I will discuss some open DSL problems such as difficulties of combining DSLs.
MarjanMernik received the M.Sc. and Ph.D. degrees in computer science from the University of Maribor in 1994 and 1998 respectively. He is currently a professor at the University of Maribor, Faculty of Electrical Engineering and Computer Science. He is also a visiting professor at the University of Alabama at Birmingham, Department of Computer and Information Sciences, and at the University of Novi Sad, Faculty of Technical Sciences, Serbia. His research interests include programming languages, compilers, domain-specific (modeling) languages, grammar-based systems, grammatical inference, and evolutionary computations. He is a member of the IEEE, ACM and EAPLS. Dr. Mernik is the Editor-In-Chief of Visual Languages and Computing, the Editor-in-Chief of Computer Languages, Systems and Structures journal, as well as Associate Editor of Applied Soft Computing journal. He is being named a Highly Cited Researcher for 2017 by Clarivate Analytics.
Assist. Prof. dr. TomazKosar, University of Maribor, Faculty of Electrical Engineering and Computer Science, Slovenia
Title: Program Comprehension of Domain-Specific and General-Purpose Languages: Replication of Experiments
Domain-specific languages (DSLs) are an increasingly popular software development technique that use concepts from the problem domain rather than the solution domain. DSLs allow developers to write code at a higher level of abstraction compared with general-purpose languages (GPLs). Our study found that developers performed program comprehension tasks more accurately and efficiently with DSLs than with corresponding APIs in GPLs. Due to the lack of availability of integrated development environments (IDEs) for all the DSLs in our original study, participants did not use IDEs when performing program comprehension tasks. The lack of IDEs introduced a threat to validity in the original study related to the realism of the environment. This presentation describes the replication of our earlier
study with the goal of validated the original results and extending those results to understand the impacts of IDEs on program comprehension tasks using DSLs and GPLs. We performed a dependent replication of a family of experiments in which each participant reviewed a segment of DSL or GPL code and answered a series of questions to measure his or her understanding of that code.
TomazKosar received the Ph.D. degree in computer science at the University of Maribor, Slovenia in 2007. His research is mainly concerned with design and implementation of domain-specific languages. Other research interest in computer science include also domain-specific modelling languages, empirical software engineering, generative programming, compiler construction, object-oriented programming, object-oriented design, refactoring, and unit testing. He is currently an Assistant Professor at the University of Maribor, Faculty of Electrical Engineering and Computer Science.
ŽigaLeber, University of Maribor, Faculty of Electrical Engineering and Computer Science, Slovenia
Connecting block-based programming with textual programming
Block-based programming languages have been successfully applied to introduce programming to children. These block-based programming languages are fun and motivating to start programming computer games (Scratch), interactive multimedia (Pixly), robotic control (RoboScratch), mobile phone applications (MIT AppInventor), and many more. However the transition from block-based programming to textual programming is hard. Dual modality environments reduce the gap between textual and visual programming world, connecting both notations, which enables children to edit code both ways. In my junior research program, I will try to develop a tool which will enable effortless creation of such environments.
ŽigaLeber received the MSc degree in computer science at the University of Maribor, Slovenia in 2018. He is currently a Juniour Researcher at the University of Maribor, Faculty of Electrical Engineering and Computer Science. His research is mainly concerned with design and implementation of programming languages. Other research interest in computer science include also domain-specific languages, compiler construction and machine learning.
Title: Introduction to Evolutionary Computation with Evolutionary Algorithms Rating System framework
Assist. Prof. dr. Matej Črepinšek, University of Maribor, Faculty of Electrical Engineering and Computer Science, Slovenia
Evolutionary algorithms are one of the hot topics in different research fields, from economics, medicine to engineering. Their main strengths are easy to implement (little knowledge is needed about a problem), adapt or reuse source code, fast convergence to optimum and ability to avoid local optima. The goals of the lecture are:
A short introduction to evolutionary algorithms.
Introduction tutorial in Evolutionary Algorithms Rating System framework (https://github.com/UM-LPM/EARS).
How to implement a simple problem.
How to use different algorithms.
How to interpret the solution.
Matej Črepinšek received the Ph.D. degree in computer science at the University of Maribor, Slovenia in 2007. His research interests include evolutionary computations, grammatical inference, object-oriented programming, compilers and grammar-based systems. He is currently an assistant professor at the University of Maribor, Faculty of Electrical Engineering and Computer Science.
dr. MihaRavber, University of Maribor, Faculty of Electrical Engineering and Computer Science, Slovenia
Title: Tuning Multi-Objective Optimization Algorithms for the Integration and Testing Order Problem
Multi-Objective Evolutionary Algorithms (MOEAs) are one of the most used search techniques in Search-Based Software Engineering (SBSE). However, MOEAs have many control parameters which must be configured for the problem at hand. This can be a very challenging task by itself. To make matters worse, in Multi-Objective Optimization (MOO) different aspects of quality of the obtained Pareto front need to be taken in to account. A novel method called MOCRS-Tuning is proposed to address this problem. MOCRS-Tuning is a meta-evolutionary algorithm which uses a chess rating system with quality indicator ensemble. The chess rating system enables us to determine the performance of an MOEA on different problems easily. The ensemble of quality indicators ensures that different aspects of quality are considered. The tuning was carried out on five different MOEAs on the Integration and Test Order Problem (ITO). The experimental results show significant improvement after tuning of all five MOEAs used in the experiment.
MihaRavber received the M.Sc. and Ph.D. degrees in computer science from the University of Maribor in 2015 and 2018 respectively. He is currently an assistant at the University of Maribor, Faculty of Electrical Engineering and Computer Science. His research interests include evolutionary computation and Multi-objective optimization.
报告六： 16：00 -16：30
Marjan Horvat, M.Sc. University of Maribor, Faculty of Electrical Engineering and Computer Science, Slovenia
Title: What is Hyper-Heuristic and using Hyper-Heuristics for evaluation of operators in evolutionary algorithms
Development in the field of evolutionary algorithms is still on the rise and it does not seems to calm down soon. Field of evolutionary algorithms is growing with new and better algorithms on daily basis. The practical application of new algorithms are used in the difficult and demanding environments. Expectations of general and professional public are high. Latest family of algorithms is known as hyper-heuristics. Characteristics for this group of algorithms is the simultaneous use of a large number of algorithms for solving single problem. The aim is to combine knowledge of multiple algorithms into one cohesive environment.
Marjan Horvat received his M.Sc. degree in computer science from the University of Maribor in 2016. He is currently working as technical staff in Programming methodologies laboratory. His research interests among other include evolutionary computations and internet of things.