@article {Simula.approve.66,
	title = {Empirical Principles and an Industrial Case Study in Retrieving Equivalent Requirements Via Natural Language Processing Techniques},
	journal = {IEEE Transactions on Software Engineering},
	volume = {39},
	number = {1},
	year = {2012},
	pages = {18-44},
	publisher = {IEEE},
	abstract = {Though very important in software engineering, linking artifacts of the same type (clone detection) or different types (traceability recovery) is extremely tedious, error-prone and requires significant effort. Past research focused on supporting analysts with mechanisms based on Natural Language Processing (NLP) to identify candidate links. Because a plethora of NLP techniques exists, and their performances vary among contexts, it is important to define and use reliable approaches for selecting the right NLP for the task at hand. In this paper we propose a novel analysis procedure to evaluate the performance of NLP techniques; the procedure aims at alleviating the influence of the adopted dataset on the results and is independent of both the type of artifacts being linked and the type of analyzed NLP. The paper presents a case study that applies the analysis procedure to characterize a large number of NLP techniques for identifying equivalent requirements in the context of an Italian company in the defense and aerospace domain. Major results from the case study include: i) the performances among NLP techniques vary significantly; ii) NLP techniques that are able to detect similarity even when the terms are not identical resulted in worst performances; iii) the combination of NLP techniques significantly improves the benefits of adopting any single NLP; iv) only the 12\% of NLP provide different information.},
	doi = {10.1109/TSE.2011},
	author = {Falessi, Davide and Cantone, Giovanni and Canfora, Gerardo}
}
@inproceedings {Simula.approve.24,
	title = {A Comprehensive Characterization of NLP Techniques for Identifying Equivalent Requirements},
	journal = {International Symposium on Empirical Software Engineering and Measurement (ESEM 2010)},
	year = {2010},
	publisher = {ACM},
	type = {Conference},
	abstract = {[Context] Though very important in software engineering, linking artifacts of the same type (clone detection) or of different types (traceability recovery) is extremely tedious, error-prone and requires significant effort. Past research focused on supporting analysts with mechanisms based on Natural Language Processing (NLP) to identify candidate links. Because a plethora of NLP techniques exists, and their performances vary among contexts, it is important to characterize them according to the provided level of support. [Objective] The aim of this paper is to characterize a comprehensive set of NLP techniques according to the provided level of support to the human analyst in detecting equivalent requirements. [Method] The characterization consists on a case study, featuring real requirements, in the context of an Italian company in the defense and aerospace domain. [Results] The major result from the case study is that simple NLP are more precise than complex ones.},
	isbn = {978-1-4503-0039-1},
	author = {Falessi, Davide and Cantone, Giovanni and Canfora, Gerardo},
	editor = {Succi, Giancarlo and Morisio, Maurizio and Nagappan, Nachi}
}
@inproceedings {Simula.SE.123,
	title = {Assessing Software System Maintainability Using Structural Measures and Expert Assessments},
	journal = {the 23rd International Conference on Software Maintenance (ICSM 2007, the paper received Best Paper Award)},
	year = {2007},
	month = {October},
	pages = {204-213},
	publisher = {IEEE},
	type = {Conference},
	abstract = {A software client usually has few means of assessing the maintainability of a software system in the acquisition process. Software maintenance is often expensive, hence, strategies for assessing the maintainability of complete software systems are important. Assessing the maintainability of complete systems is difficult due to the influence of many different factors such as the people, tasks and tools, in addition to the code. Most research on maintainability focuses on individual classes of individual systems. This paper describes an empirical study where the maintainability of four functionally equivalent systems was assessed using both structural measures and expert assessments. The results suggest that such a combination may be useful. Although, the assessment based on structural measures mostly corresponded with the expert assessments, there were several examples of potential maintainability problems that were not captured by the structural measures.},
	isbn = {1-4244-1256-0},
	author = {Anda, Bente Cecilie Dahlum},
	editor = {Canfora, Gerardo and Tahvildari, Ladan}
}
