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search-based software engineering for constructing covering arrays

IET software 2018年第4期12卷 324-332页

作者： Torres-Jimenez, Jose Izquierdo-Marquez, Idelfonso Avila-George, Himer CINVESTAV Tamaulipas Ciudad Victoria Tamaulipas Mexico Univ Guadalajara Ctr Univ Valles Ameca Jalisco Mexico

search-based software engineering involves the application of optimisation methods to solve software engineering problems. One of the most significant difficulties in testing software systems is the effort needed to build the test suites required to validate a software system, which efficiently exposes faults. Given the importance of the software testing stage, a specific sub-area known as search-based software testing has become relevant in recent years. In this work, a search-based software testing algorithm for constructing covering arrays is proposed. A covering array is a combinatorial structure that can be used as a set of test cases. By utilising this algorithm, the authors reduce the size of 893 test suites.

关键词： software engineering program testing optimisation combinatorial mathematics search problems test cases optimisation methods software engineering problems software testing stage test suites covering arrays search-based software engineering software system testing search-based software testing algorithm combinatorial structure

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search-based software engineering for optimising usability of user interfaces within model transformations

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IET software 2019年第5期13卷 368-378页

作者： Hentati, Marwa Trabelsi, Abdelwaheb Benammar, Lassaad Mahfoudhi, Adel Univ Sfax Natl Sch Engn CES Lab Sfax Tunisia Saudi Elect Univ Coll Computat & Informat Dammam Saudi Arabia Prince Sattam Bin Abdulaziz Univ Coll Sci & Humanities Aflaj Saudi Arabia Taif Univ Coll Comp & Informat Technol At Taif Saudi Arabia

search-based software engineering stands for an important area of research which involves finding optimal solutions for software engineering problems according to a set of conflicting objectives. One of these problems is improving the software quality such as usability of user interfaces following the model-driven engineering (MDE) paradigm. Transforming models consist of a set of transformation rules that describe how a component from a source model can be transformed into one or several target models. Although alternative target models may be equivalent from the functional viewpoint, they may differ from the non-functional perspectives. Besides, they do not fulfil the same usability aspects. In this context, search-based algorithms aim to identify which alternative transformation will produce a highly-usable target model. This study addresses this issue by combining the power of model transformations engine and search-based techniques. Specifically, the proposed approach defines model transformation as a usability optimisation problem. It allows the search of the optimal alternative transformation from a large search space taking into account a set of required usability attributes and using an evolutionary algorithm.

关键词： optimisation evolutionary computation user interfaces search problems software architecture software quality highly-usable target model model transformation usability optimisation problem optimal alternative transformation search space user interfaces software quality model-driven engineering transformation rules source model alternative target models nonfunctional perspectives usability attributes search-based software engineering evolutionary algorithm

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Incorporating user preferences in search-based software engineering: A systematic mapping study

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INFORMATION AND software TECHNOLOGY 2017年第Oct.期90卷 55-69页

作者： Ferreira, Thiago Nascimento Vergilio, Silvia Regina de Souza, Jerffeson Teixeira DInf Fed Univ Parana CP 19081 BR-81531980 Curitiba Parana Brazil Univ Estadual Ceara 1700 Dr Silas Munguba Ave Fortaleza Ceara Brazil

Context: search-based algorithms have been successfully applied to solve software engineering problems in the field known as search-based software engineering (SBSE). However, in practice, the user may reject the obtained solutions, since many characteristics of the problem cannot be mathematically modeled. To cope with this situation, preference-based algorithms have been investigated and raised interest in the SBSE field. Objective: To identify the quantity and type of research on SBSE preference-based approaches and to contribute to this new research subject, named here Preference and search-based software engineering (PSBSE), Method: We conducted a systematic mapping, following a research plan to locate, assess, extract and group the outcomes from relevant studies. Results: Few software engineering activities have been addressed. The most used algorithms are evolutionary and single-objective. In most studies the preferences are provided interactively and, in many cases, the user preferences are incorporated in the fitness functions. We observe a lack of evaluation measures and works comparing existing approaches. Conclusions: The use of preference-based algorithms in SBSE is an underexplored subject, and many research opportunities exist. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Preference-based algorithms search-based software engineering Systematic mapping

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A Systematic Review of Interaction in search-based software engineering

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IEEE TRANSACTIONS ON software engineering 2019年第8期45卷 760-781页

作者： Ramirez, Aurora Raul Romero, Jose Simons, Christopher L. Univ Cordoba Dept Comp Sci & Numer Anal E-14071 Cordoba Spain Univ West England Dept Comp Sci & Creat Technol Bristol BS16 1QY Avon England

search-based software engineering (SBSE) has been successfully applied to automate a wide range of software development activities. Nevertheless, in those software engineering problems where human evaluation and preference are crucial, such insights have proved difficult to characterize in search, and solutions might not look natural when that is the expectation. In an attempt to address this, an increasing number of researchers have reported the incorporation of the 'human-in-the-loop' during search and interactive SBSE has attracted significant attention recently. However, reported results are fragmented over different development phases, and a great variety of novel interactive approaches and algorithmic techniques have emerged. To better integrate these results, we have performed a systematic literature review of interactive SBSE. From a total of 669 papers, 26 primary studies were identified. To enable their analysis, we formulated a classification scheme focused on four crucial aspects of interactive search, i.e., the problem formulation, search technique, interactive approach, and the empirical framework. Our intention is that the classification scheme affords a methodological approach for interactive SBSE. Lastly, as well as providing a detailed cross analysis, we identify and discuss some open issues and potential future trends for the research community.

关键词： search-based software engineering interaction systematic literature review optimization

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A survey of many-objective optimisation in search-based software engineering

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JOURNAL OF SYSTEMS AND software 2019年 149卷 382-395页

作者： Ramirez, Aurora Raul Romero, Jose Ventura, Sebastian Univ Cordoba Dept Comp Sci & Numer Anal E-14071 Cordoba Spain

search-based software engineering (SBSE) is changing the way traditional software engineering (SE) activities are carried out by reformulating them as optimisation problems. The natural evolution of SBSE is bringing new challenges, such as the need of a large number of objectives to formally represent the many decision criteria involved in the resolution of SE tasks. This suggests that SBSE is moving towards many-objective optimisation, an emerging area that provides advanced techniques to cope with high dimensional optimisation problems. To analyse this phenomenon, this paper surveys relevant SBSE literature focused on the resolution of many-objective problems. From the gathered knowledge, current limitations regarding problem formulation, algorithm selection, experimental design and industrial applicability are discussed. Through the analysis of observed trends, this survey provides a historical perspective and future lines of research concerning the adoption of many-objective optimisation within SBSE. (C) 2018 Elsevier Inc. All rights reserved.

关键词： search-based software engineering Many-objective optimisation Multi-objective optimisation Evolutionary algorithms Literature survey

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Quality Indicators in search-based software engineering: An Empirical Evaluation

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ACM TRANSACTIONS ON software engineering AND METHODOLOGY 2020年第2期29卷 10-10页

作者： Ali, Shaukat Arcaini, Paolo Pradhan, Dipesh Safdar, Safdar Aqeel Yue, Tao Simula Res Lab Martin Linges Vei 25 N-1364 Fornebu Norway ERATO Hasuo Project Palace Side Bldg 3F Hitotsubashi 1-1-1 Tokyo 1000003 Japan Nanjing Univ Aeronaut & Astronaut Nanjing Peoples R China NUAA Coll Comp Sci & Technol 29 Jiangjun Ave Nanjing 211100 Peoples R China

search-based software engineering (SBSE) researchers who apply multi-objective search algorithms (MOSAs) often assess the quality of solutions produced by MOSAs with one or more quality indicators (QIs). However, SBSE lacks evidence providing insights on commonly used QIs, especially about agreements among them and their relations with SBSE problems and applied MOSAs. Such evidence about Qls agreements is essential to understand relationships among QIs, identify redundant QIs, and consequently devise guidelines for SBSE researchers to select appropriate QIs for their specific contexts. To this end. we conducted an extensive empirical evaluation to provide insights on commonly used QIs in the context of SBSE, by studying agreements among QIs with and without considering differences of SBSE problems and MOSAs. In addition, by defining a systematic process based on three common ways of comparing MOSAs in SBSE, we present additional observations that were automatically produced based on the results of our empirical evaluation. These observations can be used by SBSE researchers to gain a better understanding of the commonly used QIs in SBSE, in particular, regarding their agreements. Finally, based on the results, we also provide a set of guidelines for SBSE researchers to select appropriate QIs for their particular context.

关键词： search-based software engineering quality indicator agreement multi-objective search algorithm

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Multimedia in search-based software engineering: challenges and opportunities within a new research domain

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第25期81卷 35671-35691页

作者： Prajapati, Amarjeet Parashar, Anshu Sunita Chhabra, Jitender Kumar Jain, Chakresh Kumar JIIT Noida India Thapar Inst Engn & Technol Comp Sci & Engn Dept Patiala Punjab India CCET Chandigarh India NIT Kurukshetra Haryana India

search-based software engineering (SBSE) is an emerging research sub-area in the field of software engineering. The concept of SBSE is based on the idea of formulation of software engineering problem as a search-based optimization problem and effective exploitation of metaheuristic search optimizers to solve it. The complex nature of software engineering problems and complex computational behaviour of the metaheuristic search algorithms makes the SBSE approaches challenging to understand and analyze. A variety of multimedia technologies are generally used to make the problem formulation and their computational method more understandable and analyzable. Even after wide application of multimedia in science and engineering, the SBSE got little attention in this direction. To explore and exploit the potential of the multimedia in the SBSE, this work first conducted a research study on the current trends of multimedia in SBSE, then based on this study, the various challenges and opportunities are presented. More specifically, our work mainly focusses on current multimedia trends in various forms of SBSE approaches (e.g., single, multi, and many-objective SBSE). Apart from that, we also explore the various opportunities and challenges in SBSE from the perspective of visualization of software artefacts, software quality metrics, problem formulation, search trajectory, Pareto optimal set and front.

关键词： Multimedia software analysis search-based software engineering visualization Representations search-based optimization

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Parameter tuning or default values? An empirical investigation in search-based software engineering

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EMPIRICAL software engineering 2013年第3期18卷 594-623页

作者： Arcuri, Andrea Fraser, Gordon Simula Res Lab Certus Software V&V Ctr Lysaker Norway Univ Sheffield Dept Comp Sci Sheffield S1 4DP S Yorkshire England

Many software engineering problems have been addressed with search algorithms. search algorithms usually depend on several parameters (e.g., population size and crossover rate in genetic algorithms), and the choice of these parameters can have an impact on the performance of the algorithm. It has been formally proven in the No Free Lunch theorem that it is impossible to tune a search algorithm such that it will have optimal settings for all possible problems. So, how to properly set the parameters of a search algorithm for a given software engineering problem? In this paper, we carry out the largest empirical analysis so far on parameter tuning in search-based software engineering. More than one million experiments were carried out and statistically analyzed in the context of test data generation for object-oriented software using the EvoSuite tool. Results show that tuning does indeed have impact on the performance of a search algorithm. But, at least in the context of test data generation, it does not seem easy to find good settings that significantly outperform the "default" values suggested in the literature. This has very practical value for both researchers (e.g., when different techniques are compared) and practitioners. Using "default" values is a reasonable and justified choice, whereas parameter tuning is a long and expensive process that might or might not pay off in the end.

关键词： search-based software engineering Test data generation Object-oriented Unit testing Tuning EvoSuite Java Response surface Design of experiments

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On the use of many quality attributes for software refactoring: a many-objective search-based software engineering approach

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EMPIRICAL software engineering 2016年第6期21卷 2503-2545页

作者： Mkaouer, Mohamed Wiem Kessentini, Marouane Bechikh, Slim Cinneide, Mel O. Deb, Kalyanmoy Univ Michigan Dearborn MI 48128 USA Univ Coll Dublin Dublin Ireland Michigan State Univ E Lansing MI USA

search-based software engineering (SBSE) solutions are still not scalable enough to handle high-dimensional objectives space. The majority of existing work treats software engineering problems from a single or bi-objective point of view, where the main goal is to maximize or minimize one or two objectives. However, most software engineering problems are naturally complex in which many conflicting objectives need to be optimized. software refactoring is one of these problems involving finding a compromise between several quality attributes to improve the quality of the system while preserving the behavior. To this end, we propose a novel representation of the refactoring problem as a many-objective one where every quality attribute to improve is considered as an independent objective to be optimized. In our approach based on the recent NSGA-III algorithm, the refactoring solutions are evaluated using a set of 8 distinct objectives. We evaluated this approach on one industrial project and seven open source systems. We compared our findings to: several other many-objective techniques (IBEA, MOEA/D, GrEA, and DBEA-Eps), an existing multi-objective approach a mono-objective technique and an existing refactoring technique not based on heuristic search. Statistical analysis of our experiments over 31 runs shows the efficiency of our approach.

关键词： search-based software engineering Refactoring software quality Many-objective optimization

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Model transformation testing: a bi-level search-based software engineering approach

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JOURNAL OF software-EVOLUTION AND PROCESS 2015年第11期27卷 821-837页

作者： Sahin, Dilan Kessentini, Marouane Wimmer, Manuel Deb, Kalyanmoy Univ Michigan Dearborn MI 48128 USA Vienna Univ Technol Vienna Austria Michigan State Univ E Lansing MI 48824 USA

The process of writing model transformations is a complex and error-prone one. Thus, efficient techniques and tools for validating model transformations are needed. One of them is model transformation testing. The generation of test cases for model transformations is mainly based on metamodel and rules coverage criteria. In this paper, we propose to treat model transformation testing as a bi-level optimization problem to combine the generation of test cases with mutation testing. In our adaptation, the upper-level problem generates a set of test cases that maximizes the coverage of metamodels and errors introduced by the lower level to the transformation rules. The lower level maximizes the number of generated errors in the rules that cannot be detected by the test cases produced by the upper level. The main advantage of our bi-level formulation is that the evaluation of test cases is not limited to the coverage of metamodels, but it allows evaluating their ability to detect errors. The statistical analysis of our experiments on different transformation mechanisms confirms the outperformance of our bi-level proposal compared with state-of-the-art model transformation testing techniques. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： search-based software engineering software maintenance bi-level optimization

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