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

Ferreira, Thiago do Nascimento; Vergílio, Silvia Regina; Souza, Jerffeson

doi:10.1016/j.infsof.2017.05.003

Cited by 30 publications

(23 citation statements)

References 20 publications

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“…There are several methodologies in SBSE that incorporate the desire of the decision-maker. A more consistent explanation about this method of selection is given in [42]. The black dots shown in Figures 7-10 show that these are the best choices for the decision-maker, or the best solutions to the problem given the decision-maker's particularities and experience.…”

Section: Generational Distance (Gd)mentioning

confidence: 89%

“…All these subjective parameters were considered before the ZAPROS III-i methodology generated a result. SBSE uses similar approaches to this work, such as the one described in [42], in which these Here the decision-maker and his team decided what his preferences were when asked by the tool that presents available solutions for a given context.…”

Section: Application Of Questionnairementioning

confidence: 99%

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Towards the Verbal Decision Analysis Paradigm for Implementable Prioritization of Software Requirements

2018

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The activity of prioritizing software requirements should be done as efficiently as possible. Selecting the most stable requirements for the most important customers of a development company can be a positive factor considering that available resources do not always encompass the implementation of all requirements. There are many quantitative methods for prioritization of software releases in the field of search-based software engineering (SBSE). However, we show that it is possible to use qualitative verbal decision analysis (VDA) methods to solve this type of problem. Moreover, we will use the ZAPROS III-i method to prioritize requirements considering the opinion of the decision-maker, who will participate in this process. Results obtained using VDA structured methods were found to be quite satisfactory when compared to methods using SBSE. A comparison of results between quantitative and qualitative methods will be made and discussed later. The results were reviewed and corroborated with the use of performance metrics.

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Section: Generational Distance (Gd)mentioning

confidence: 89%

Section: Application Of Questionnairementioning

confidence: 99%

Towards the Verbal Decision Analysis Paradigm for Implementable Prioritization of Software Requirements

2018

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“…We make a detailed search string and relevant to our topic to collect a significant number of studies. The construction of these strings are inspired by several literature reviews [17,20,23,26,44,45]. These queries are enough to cover a wide range of articles and match the article title, abstract, and keywords.…”

Section: The Search Strategymentioning

confidence: 99%

Performance Evaluation Metrics for Multi-Objective Evolutionary Algorithms in Search-Based Software Engineering: Systematic Literature Review

et al. 2021

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Many recent studies have shown that various multi-objective evolutionary algorithms have been widely applied in the field of search-based software engineering (SBSE) for optimal solutions. Most of them either focused on solving newly re-formulated problems or on proposing new approaches, while a number of studies performed reviews and comparative studies on the performance of proposed algorithms. To evaluate such performance, it is necessary to consider a number of performance metrics that play important roles during the evaluation and comparison of investigated algorithms based on their best-simulated results. While there are hundreds of performance metrics in the literature that can quantify in performing such tasks, there is a lack of systematic review conducted to provide evidence of using these performance metrics, particularly in the software engineering problem domain. In this paper, we aimed to review and quantify the type of performance metrics, number of objectives, and applied areas in software engineering that reported in primary studies—this will eventually lead to inspiring the SBSE community to further explore such approaches in depth. To perform this task, a formal systematic review protocol was applied for planning, searching, and extracting the desired elements from the studies. After considering all the relevant inclusion and exclusion criteria for the searching process, 105 relevant articles were identified from the targeted online databases as scientific evidence to answer the eight research questions. The preliminary results show that remarkable studies were reported without considering performance metrics for the purpose of algorithm evaluation. Based on the 27 performance metrics that were identified, hypervolume, inverted generational distance, generational distance, and hypercube-based diversity metrics appear to be widely adopted in most of the studies in software requirements engineering, software design, software project management, software testing, and software verification. Additionally, there are increasing interest in the community in re-formulating many objective problems with more than three objectives, yet, currently are dominated in re-formulating two to three objectives.

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“…Some other literature reviews focus on specific tasks, such as mining repositories using SBSE [21], test data generation [5,22], genetic improvement of software [23], software requirements management [8,24,25], re-engineering of legacy applications into SPL [26], software module clustering [27], software project scheduling [28], cloud migration [29], and test resource allocation [30]. Specific techniques are also target of SBSE surveys, such as multi-and many-objective optimisation [31][32][33], hyper-heuristics [34], and interactive algorithms [35,36].…”

Section: Related Workmentioning

confidence: 99%

“…Often the users do not recognise the solutions as feasible because they were not generated considering their needs and preferences. Involving the user in the loop has been investigated in the past [35,36], but it is still an open challenge for the SBSE community. To name a few, these constitute some research opportunities: i) resolution of conflicting opinions provided by different users or different priorities given to the many objectives impacting the problem; ii) selection of the best moment and way to incorporate the preferences; and iii) to avoid human-fatigue in interactive approaches.…”

Section: Sbse Challengesmentioning

confidence: 99%

The Symposium on Search-Based Software Engineering: Past, Present and Future

Colanzi

Assunção

Vergílio

et al. 2020

Information and Software Technology

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Context: Search-Based Software Engineering (SBSE) is the research field where Software Engineering (SE) problems are modelled as search problems to be solved by search-based techniques. The Symposium on Search Based Software Engineering (SSBSE) is the premier event on SBSE, which had its 11 th edition in 2019. Objective: In order to better understand the characteristics and evolution of papers published at SSBSE, this work reports results from a mapping study targeting the proceedings of all SSBSE editions. Despite the existing mapping studies on SBSE, our contribution in this work is to provide information to researchers and practitioners willing to enter the SBSE field, being a source of information to strengthen the symposium, guide new studies, and motivate new collaboration among research groups. Method: A systematic mapping study was conducted with a set of four research questions, in which 134 studies published in all editions of SSBSE, dated from 2009 to 2019, were evaluated. In a fifth question, 32 papers published in the challenge track were summarised. Results: Throughout the years, 290 authors from 25 countries have contributed to the main track of the symposium, with the collaboration of at least two institutions in 46.3% of the papers. SSBSE papers have got substantial external visibility, as most citations are from different venues. The SE tasks addressed by SSBSE are mostly related to software testing, software debugging, software design, and maintenance. Evolutionary algorithms are present in 75% of the papers, being the most common search technique. The evaluation of the SBSE approaches usually includes industrial systems. Conclusions: SSBSE has helped increase the popularity of SBSE in the SE research community and has played an important role on making SBSE mature. There are still problems and challenges to be addressed in the SBSE field, which can be tackled by SSBSE authors in further studies.

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

Cited by 30 publications

References 20 publications

Towards the Verbal Decision Analysis Paradigm for Implementable Prioritization of Software Requirements

Towards the Verbal Decision Analysis Paradigm for Implementable Prioritization of Software Requirements

Performance Evaluation Metrics for Multi-Objective Evolutionary Algorithms in Search-Based Software Engineering: Systematic Literature Review

The Symposium on Search-Based Software Engineering: Past, Present and Future

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