Benchmarking plays a vital role in evaluating and comparing evolutionary algorithms. Our research addresses this critical need by introducing an innovative approach: rating-based confidence bands. This method serves to evaluate algorithm performance across various execution stages, enabling statistical comparison at different cutpoints of maximum Function Evaluations (maxFEs). Using publicly available results from the IEEE Congress on Evolutionary Computation (CEC) benchmark, we demonstrate the effectiveness of our methodology. Our approach uses the function error values recorded at distinct cutpoints to plot confidence bands. The confidence bands offer a comprehensive and intuitive comparison, revealing statistical significance in algorithm performances at different stages of execution. The method is integrated seamlessly into the EARS framework, facilitating the incorporation of additional algorithm results for a robust comparative analysis. Our results present a detailed analysis of CEC benchmark outcomes through rating-based confidence bands. This approach enables a nuanced evaluation of algorithmic performance, revealing statistical differences between algorithms at various cutpoints that were previously undisclosed. The framework encourages researchers to compare their results directly with state-of-the-art algorithms from benchmark competitions, enhancing result credibility and promoting a standardized evaluation approach within the research community. Our findings highlight the significance of our approach in advancing algorithm benchmarking practices. Furthermore, they emphasize the need for transparent evaluation of algorithms at different stages of execution.

Teaching programming poses countless challenges.One of them is determining the most effective notation to introduce coding concepts to beginners.This paper examines the merits and drawbacks of introducing block-based, text-based, or both notations at the same time when it comes to learning basic programming concepts.By comparing these approaches, the objective of this research is to clarify and assess the learning outcomes related to teaching beginners through different notations.In this empirical study, we report on a controlled experiment during short-term visits that promoted programming in primary schools.Our multinational study divided participants into three groups, one using block-based, one using text-based, and one using both notations.After training, the participants were solving practical programming assignments.The study results revealed that the participants' performance was not influenced by notation usage, as there was no statistical significance between the three groups.However, the performance outcomes were correlated with the duration of the sessions.Our findings from the controlled experiment suggest that educators can utilize different notations confidently while teaching beginners the first steps in programming.

Evolutionary Algorithms have been applied successfully for solving real-world multi-objective problems which explains the influx of newly proposed Multi-Objective Evolutionary Algorithms (MOEAs). In order to determine their performance, comparison with existing algorithms must be conducted. However, conducting a comparison is not a trivial task. Benchmark functions must be selected and the results have to be analyzed using a statistical method. In addition, the results of MOEAs can be evaluated with different Quality Indicators (QIs), which aggravates the comparison additionally. In this paper, we present a chess rating system which was adapted for ranking MOEAs with a Quality Indicator ensemble. The ensemble ensures that different aspects of quality are evaluated of the resulting approximation sets. The chess rating system is compared with an existing method which uses a double-elimination tournament and a quality indicator ensemble. Experimental results show that the chess rating system achieved similar rankings with fewer runs of MOEAs.

Chess Rating System for Evolutionary algorithms (CRS4EAs) is a novel method for comparing evolutionary algorithms which evaluates and ranks algorithms regarding the formula from the Glicko-2 chess rating system. It was empirically shown that CRS4EAs can be compared to the standard method for comparing algorithms - null hypothesis significance testing. The following paper examines the applications of chess rating systems beyond Glicko-2. The results of 15 evolutionary algorithms on 20 minimisation problems obtained using the Glicko-2 system were empirically compared to the Elo rating system, Chessmetrics rating system, and German Evaluation Number (DWZ). The results of the experiment showed that Glicko-2 is the most appropriate choice for evaluating and ranking evolutionary algorithms. Whilst other three systems' benefits were mainly the simple formulae, the ratings in Glicko-2 are proven to be more reliable, the detected significant differences are supported by confidence intervals, the inflation or deflation of ratings is easily detected, and the weight of individual results is set dynamically.

The RAISE'13 workshop brought together researchers from the AI and software engineering disciplines to build on the interdisciplinary synergies which exist and to stimulate research across these disciplines. The first part of the workshop was devoted to current results and consisted of presentations and discussion of the state of the art. This was followed by a second part which looked over the horizon to seek future directions, inspired by a number of selected vision statements concerning the AI-and-SE crossover. The goal of the RAISE workshop was to strengthen the AI-and-SE community and also develop a roadmap of strategic research directions for AI and software engineering.

A memetic algorithm, a novel approach for solving NP-hard problems, has been applied in this paper for grammatical inference in the field of domain-specific languages (DSLs). DSLs are often designed by domain experts who have no knowledge about the syntax and semantics of programming languages. However, they are able to write sample programs to accomplish their goals and illustrate the features of their language. Grammatical inference is a technique to infer a context-free grammar from a set of positive (and negative) samples. This paper shows that grammatical inference may assist domain experts and software language engineers in developing DSLs by automatically producing a grammar, which describes a set of sample DSL programs. A memetic-algorithm-based tool is developed, which greatly improves results and robustness of the inference process.

With the rapid development of model-driven engineering (MDE), domain-specific modeling has become a widely used software development technique. In MDE, metamodels represent a schema definition of the syntax and static semantics to which an instance model conforms (i.e., a model conforms to its metamodel in a similar manner to how a program conforms to a grammar). However, in order to address new feature requests of the domain and language, the metamodel often undergoes frequent evolution that may result in the inability of users to load and view previous model instances. MARS is a metamodel recovery system to address the problems of metamodel evolution. This paper presents our extensions to MARS to infer models for multi-tiered domains. A new XSLT translator has been developed to generate a domain-specific language (DSL) called MRL (model representation language) for the XML representation of domain instances. The metamodel inference engine has been revised to translate the MRL back into a metamodel.

Graphical Processing Unit (GPU) programming languages are used extensively for general-purpose computations. However, GPU programming languages are at a level of abstraction suitable only for use by expert parallel programmers. This paper presents a new approach through which `C' or Java programmers can access these languages without having to focus on the technical or language-specific details. A prototype of the approach, named CUDACL, is introduced through which a programmer can specify one or more parallel blocks in a file and execute in a GPU. CUDACL also helps the programmer to make CUDA or OpenCL kernel calls inside an existing program. Two scenarios have been successfully implemented to assess the usability and potential of the tool. The tool was created based on a detailed analysis of the CUDA and OpenCL programs. Our evaluation of CUDACL compared to other similar approaches shows the efficiency and effectiveness of CUDACL.

Although there have been many benefits of Domain-Specific Languages (DSLs) reported from both academia and industry, implementation of DSLs continue to face challenges with respect to frequent evolution of both syntax and semantics. Techniques for implementing DSLs also lack interoperable capabilities among base languages and limited tool support. Such challenges result in increasing DSL development cost and constrain DSL adoption opportunities. This paper introduces a Service-Oriented Architecture (SOA) approach to address such problems. The approach utilizes WSDL to perform lexical and syntax analysis. Web services are used to define the semantics of a DSL, and WS-BPEL is then used to specify a DSL program. We present two case studies representing different DSL categories to show the feasibility of SOA-based DSL implementation. The case studies demonstrate the potential for easing the burden of DSL evolution and offering interoperability and tool support. Improved modularization and removal of tokenization/parsing are two additional advantages. Discussion and comparison among interpreter-based, model-driven and SOA-based DSL implementations are provided, which may raise more research interests in this area.

In model-driven engineering, metamodels may get lost over time resulting in the inability to load and view existing model instances. MARS is a system that recovers metamodels from model instances using grammar inference. This paper discusses advances in MARS that improve accuracy and scalability.

Abstract 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. Tool support for DSLs is lacking when compared with the capabilities provided for standard general‐purpose languages (GPLs), such as Java and C++. For example, support for debugging a program written in a DSL is often non‐existent. The lack of a debugger at the proper abstraction level limits an end‐user's ability to discover and locate faults in a DSL program. This paper describes a grammar‐driven technique to build a debugging tool generation framework from existing DSL grammars. The DSL grammars are used to generate the hooks needed to interface with a supporting infrastructure constructed for an integrated development environment that assists in debugging a program written in a DSL. The contribution represents a coordinated approach to bring essential software tools (e.g. debuggers) to different types of DSLs (e.g. imperative, declarative, and hybrid). This approach hides from the end‐users the accidental complexities associated with expanding the focus of a language environment to include debuggers. The research described in this paper addresses a long‐term goal of empowering end‐users with development tools for particular DSL problem domains at the proper level of abstraction without depending on a specific GPL. Copyright © 2007 John Wiley & Sons, Ltd.

Aspect-oriented programming (AOP) provides a way to modularize crosscutting concerns. Crosscuting concerns can be found in various representations of software artifacts and in different steps of software life cycle (e.g., source code, models, requirements, language grammars). This paper provides an introduction to the AspectLISA tool and its aspect-oriented specification language for programming language definition and compiler construction. AspectLISA is a mature, well-tested system for automatically generating compilers, interpreters, and other language related tools from formal incremental and reusable aspect-oriented attribute grammar-based specifications. In the paper we discuss about the issues involved in the design and implementation of domain-specific aspect language for compiler construction, as well as some benefits of aspect-oriented specifications.

Optimizing combinations of placements of parts, known as markers, is an important preparatory step in order-based industrial production of clothes. Given a work order in the form of a matrix of pieces in size numbers and designs, the task is to find a list of combinations of size numbers to complete the work order. The outcome of this step influences the number of cut out pieces, the amount of material used in the production phase, and the speed of the work order processing. The optimization task is demanding since a number of factors affect production costs and several conflicting criteria can be involved in marker assessment. We consider minimum number of markers per work order as an optimization criterion and transform the problem into the knapsack problem which is then solved with several variants of an evolutionary algorithm. Numerical experiments are performed on real problem instances from industrial clothes production and the results compare favorably with those produced by the algorithm regularly used in practice.

We describe an efficient technique for adapting control parameter settings associated with differential evolution (DE). The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters, which are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE. We present an algorithm-a new version of the DE algorithm-for obtaining self-adaptive control parameter settings that show good performance on numerical benchmark problems. The results show that our algorithm with self-adaptive control parameter settings is better than, or at least comparable to, the standard DE algorithm and evolutionary algorithms from literature when considering the quality of the solutions obtained.

Refactoring is a way of improving software artifacts after they have been produced to fulfill users' needs. It is a semi-formalized approach that makes software easier to read and modify. A notation for refactorings, systematic search and replace is described. It is shown, that grammar-based notation used in JART (Just Another Refactoring Tool) is much more flexible and readable than the existing ones.

Prolapse is defined as the displacement of a bodily part from its normal position. The term mitral valve prolapse (PMV), therefore, implies that the mitral leaflets are displaced relative to some structure, generally taken to be the mitral annulus. The implications of the PMV are following: disturbed normal laminar blood flow, turbulence of the blood flow, injury of the chordae tendinae, the possibility of thrombus's composition, bacterial endocarditis and finally hemodynamic changes defined as mitral insufficiency and mitral regurgitation. Uncertainty persists about how it should be diagnosed and about its clinical importance. It is our deep belief that the echocardiography enables proper trained experts armed with proper criteria to evaluate PMV almost 100%. Unfortunately there are some problems concerned with the use of echocardiography. We have decided to start a research project aimed to find new criteria and enable general practitioners to evaluate the PMV using conventional methods and to select potential patients from the general population. To empower one to perform needed activities we developed a computer tool called ROSE (Computerised Prolaps Syndrome Determination) based on algorithms of automatic learning. This tool supports the definition of new criteria and the selection of potential PMV-patients.>