Tomaž Kosar

Program comprehension of domain-specific and general-purpose languages: comparison using a family of experiments

Domain-specific languages (DSLs) are often argued to have a simpler notation than general-purpose languages (GPLs), since the notation is adapted to the specific problem domain. Consequently, the impact of domain relevance on the creation of the problem representation is believed to improve programmers’ efficiency and accuracy when using DSLs compared with using similar solutions like application libraries in GPLs. Most of the common beliefs have been based upon qualitative conclusions drawn by developers. Rather than implementing the same problem in a DSL and in a GPL and comparing the efficiency and accuracy of each approach, developers often compare the implementation of a new program in a DSL to their previous experiences implementing similar programs in GPLs. Such a conclusion may or may not be valid. This paper takes a more skeptical approach to acceptance of those beliefs. By reporting on a family of three empirical studies comparing DSLs and GPLs in different domains. The results of the studies showed that when using a DSL, developers are more accurate and more efficient in program comprehension than when using a GPL. These results validate some of the long- held beliefs of the DSL community that until now were only supported by anecdotal evidence.

Domain-Specific Languages

Context: In this study we report on a Systematic Mapping Study (SMS) for Domain-Specific Languages (DSLs), based on an automatic search including primary studies from journals, conferences, and workshops during the period from 2006 until 2012.Objective: The main objective of the described work was to perform an SMS on DSLs to better understand the DSL research field, identify research trends, and any possible open issues. The set of research questions was inspired by a DSL survey paper published in 2005.Method: We conducted a SMS over 5 stages: defining research questions, conducting the search, screening, classifying, and data extraction. Our SMS included 1153 candidate primary studies from the ISI Web of Science and ACM Digital Library, 390 primary studies were classified after screening.Results: This SMS discusses two main research questions: research space and trends/demographics of the literature within the field of DSLs. Both research questions are further subdivided into several research sub-questions. The results from the first research question clearly show that the DSL community focuses more on the development of new techniques/methods rather than investigating the integrations of DSLs with other software engineering processes or measuring the effectiveness of DSL approaches. Furthermore, there is a clear lack of evaluation research. Amongst different DSL development phases more attention is needed in regard to domain analysis, validation, and maintenance. The second research question revealed that the number of publications remains stable, and has not increased over the years. Top cited papers and venues are mentioned, as well as identifying the more active institutions carrying DSL research.Conclusion: The statistical findings regarding research questions paint an interesting picture about the mainstreams of the DSL community, as well as open issues where researchers can improve their research in their future work.

Ontology driven development of domain-specific languages

Domain-specific languages (DSLs) are computer (programming, modeling, specification) languages devoted to solving problems in a specific domain. The development of a DSL includes the following phases: decision, analysis, design, implementation, testing, deployment, and maintenance. The least-known and least examined are analysis and design. Although various formal methodologies exist, domain analysis is still done informally most of the time. A common reason why formal methodologies are not used as often as they could be is that they are very demanding. Instead of developing a new, less complex methodology, we propose that domain analysis could be replaced with a previously existing analysis in another form. A particularly suitable form is the use of ontologies. This paper focuses on ontology-based domain analysis and how it can be incorporated into the DSL design phase. We will present the preliminary results of the Ontology2DSL framework, which can be used to help transform ontology to a DSL grammar incorporating concepts from a domain.

On the use of a domain-specific modeling language in the development of multiagent systems

The study of Multiagent Systems (MASs) focuses on those systems in which many intelligent agents interact with each other. The agents are considered to be autonomous entities which contain intelligence that serves for solving their selfish or common problems, and to achieve certain goals. However, the autonomous, responsive, and proactive natures of agents make the development of agent-based software systems more complex than other software systems. Furthermore, the design and implementation of a MAS may become even more complex and difficult to implement when considering new requirements and interactions for new agent environments like the Semantic Web. We believe that both domain-specific modeling and the use of a domain-specific modeling language (DSML) may provide the required abstraction, and hence support a more fruitful methodology for the development of MASs. In this paper, we first introduce a DSML for MASs called SEA_ML with both its syntax and semantics definitions and then show how the language and its graphical tools can be used during model-driven development of real MASs. In addition to the classical viewpoints of a MAS, the proposed DSML includes new viewpoints which specifically support the development of software agents working within the Semantic Web environment. The methodology proposed for the MAS development based on SEA_ML is also discussed including its example application on the development of an agent-based stock exchange system.

From DCOM interfaces to domain-specific modeling language : a case study on the sequencer

Software development is a demanding process, since it involves different parties to perform a desired task. The same case applies to the development ofmeasurement systems - measurement system producers often provide interfaces to their products, after which the customersc programming engineers use them to build software according to the instructions and requirements of domain experts from the field of data acquisition. Until recently, the customers of the measurement system DEWESoft were building measuring applications, using prefabricated DCOM objects. However, a significant amount of interaction between customersc programming engineers and measurement system producers is necessary to use DCOM objects. Therefore, a domain-specific modeling language has been developed to enable domain experts to program or model their own measurement procedures without interacting with programming engineers. In thispaper, experiences gained during the shift from using the DEWESoft productas a programming library to domain-specific modeling language are provided together with the details of a Sequencer, a domain-specific modeling language for the construction of measurement procedures.

Declarative specifications for the development of multi-agent systems

The designing and implementation of a multi-agent system (MAS), where autonomous agents collaborate with other agents for solving problems, constitute complex tasks that may become even harder when agents work in new interactive environments such as the Semantic Web. In order to deal with the complexities of designing and implementing a MAS, a domain-specific language (DSL) can be employed inside the MASs development cycle. In such a manner, a MAS can be completely specified by programs written in a DSL. Such programs are declarative, expressive, and at the right abstraction level. In this way the complexity of MAS development is then partially shifted to DSL development and the task herein can be much more feasible by using a proper DSL development methodology and related tools. This paper presents and discusses our methodology for DSL development based on declarative formal specifications that are easy to compose, and its usage during MAS development. A practical case-study is also provided covering an example of a MASs development for expert finding systems. By using denotational semantics for precisely defining the language, we show that it is possible to generate the language automatically. In addition, using attribute grammars makes it possible to have modular methodology within which evolutionary language development becomes easier. A multi-agent system development language based on declarative specificationsLanguage is defined formally via denotational semantics and attribute grammars.Applying denotational semantics provided precise definitions of the language.We could generate the language automatically from formal semantics.Using attribute grammars made evolutionary language development easier.

Debugging measurement systems using a domain-specific modeling language

Abstract Capturing physical data in the context of measurement systems is a demanding process that often requires many repetitions with different settings. To assist in this activity, a domain-specific modeling language (DSML) called Sequencer has been developed to enable the improved definition of measurement procedures. With Sequencer, the level of abstraction has been raised and sophisticated changes in measurement procedures are now enabled. Although there are numerous DSMLs like Sequencer in the existing literature, there are some obstacles working against the more widespread adoption of DSMLs in practice. One challenge is the lack of supporting tools for DSMLs, which would improve the capabilities of end-users of such languages. For instance, support for debugging a model expressed in a DSML is often neglected. The lack of a debugger at the proper abstraction level limits the domain experts in discovering and locating bugs in a model. In this paper, Sequencer is presented together with debugging facilities (called Ladybird) that are integrated in a modeling environment. Ladybird supports different execution modes (e.g., steps, breakpoints, animations, variable views, and stack traces) that can be helpful during the debugging of a model. Ladybirds primary contribution is in showing the value of error detection in complicated industrial environments, such as data acquisition in automotive testing. The paper contributes to a discussion of the implementation details of DSML debugging facilities and how such a debugger can be reused to support domains other than the measurement context of Sequencer.

A Systematic Mapping Study driven by the margin of error

Abstract Until recently, many Systematic Literature Reviews (SLRs) and Systematic Mapping Studies (SMSs) have been proposed. However, when SMS is performed on a broad topic with a large amount of primary studies, the cost of assessment of all primary studies requires unjustified resources. In this paper, a new approach is introduced for performing SMSs, called SMS driven by the margin of error. The main objective of the described work was to decrease the assessment cost of primary studies by stopping the process of classification of primary studies when enough evidence has been collected. We introduced a statistical approach with random sampling and a margin of error into the design of SMSs when a topic under discussion is broad with a large number of primary studies. In this paper, SMS driven by the margin of error was applied on three different use cases: SMS on Domain-Specific Languages, SMS on Template-based Code Generation, and SMS on Software Reliability Modeling, where it was shown that the proposed approach reduced the cost of assessing primary studies and quantified the reliability of SMS.

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.

Program comprehension of domain-specific and general-purpose languages: replication of a family of experiments using integrated development environments

Domain-specific languages (DSLs) allow developers to write code at a higher level of abstraction compared with general-purpose languages (GPLs). Developers often use DSLs to reduce the complexity of GPLs. Our previous study found that developers performed program comprehension tasks more accurately and efficiently with DSLs than with corresponding APIs in GPLs. This study replicates our previous study to validate and extend the results when developers use IDEs to perform program comprehension tasks. We performed a dependent replication of a family of experiments. We made two specific changes to the original study: (1) participants used IDEs to perform the program comprehension tasks, to address a threat to validity in the original experiment and (2) each participant performed program comprehension tasks on either DSLs or GPLs, not both as in the original experiment. The results of the replication are consistent with and expanded the results of the original study. Developers are significantly more effective and efficient in tool-based program comprehension when using a DSL than when using a corresponding API in a GPL. The results indicate that, where a DSL is available, developers will perform program comprehension better using the DSL than when using the corresponding API in a GPL.