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teaching:reverse:2018:references
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teaching:reverse:2018:references [2018/12/07 16:25] blay [Etudes] |
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| - http://blog.cleancoder.com/ relativement au livre : Clean Code: A Handbook of Agile Software Craftsmanship | - http://blog.cleancoder.com/ relativement au livre : Clean Code: A Handbook of Agile Software Craftsmanship | ||
| by Robert C. Martin | by Robert C. Martin | ||
| + | - [[http://www.allitebooks.com/your-code-as-a-crime-scene/|Your Code as a Crime Scene ; Use Forensic Techniques to Arrest Defects, Bottlenecks, and Bad Design in Your Programs (The Pragmatic Programmers)]] Adam Tornhill | ||
| </panel> | </panel> | ||
| </accordion> | </accordion> | ||
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| - [[http://salt.ece.ubc.ca/publications/docs/icse18-sabalan.pdf|Inferring Hierarchical Motifs from Execution Traces]] | - [[http://salt.ece.ubc.ca/publications/docs/icse18-sabalan.pdf|Inferring Hierarchical Motifs from Execution Traces]] | ||
| - {{:teaching:reverse:2017:mobilesoft_2018.pdf|}} | - {{:teaching:reverse:2017:mobilesoft_2018.pdf|}} | ||
| - | - Anas Shatnawi, Abdelhak-Djamel Seriai, Houari Sahraoui, Zakarea Alshara, [[https://www.sciencedirect.com/science/article/pii/S016412121630098X/pdfft?md5=35ec8afa03a7cc2a6d5a3ee77af0dee6&pid=1-s2.0-S016412121630098X-main.pdf|Reverse engineering reusable software components from object-oriented APIs,]] Journal of Systems and Software, Volume 131, 2017, Pages 442-460, ISSN 0164-1212, | + | - "Reverse engineering reusable software components from object-oriented APIs", |
| - | https://doi.org/10.1016/j.jss.2016.06.101 | + | * journal = "Journal of Systems and Software", |
| + | * volume = "131", | ||
| + | * pages = "442 - 460", | ||
| + | * year = "2017", | ||
| + | * issn = "0164-1212", | ||
| + | * doi = "https://doi.org/10.1016/j.jss.2016.06.101", | ||
| + | * url = "http://www.sciencedirect.com/science/article/pii/S016412121630098X", | ||
| + | * author = "Anas Shatnawi and Abdelhak-Djamel Seriai and Houari Sahraoui and Zakarea Alshara", | ||
| + | * keywords = "Software reuse, Software component, Object-oriented, API, Reverse engineering, Frequent usage pattern", | ||
| + | * Object-oriented Application Programing Interfaces (APIs) support software reuse by providing pre-implemented functionalities. Due to the huge number of included classes, reusing and understanding large APIs is a complex task. Otherwise, software components are accepted to be more reusable and understandable entities than object-oriented ones. Thus, in this paper, we propose an approach for reengineering object-oriented APIs into component-based ones. We mine components as a group of classes based on the frequency they are used together and their ability to form a quality-centric component. To validate our approach, we experimented on 100 Java applications that used four APIs." | ||
| + | - [[https://www.researchgate.net/publication/325176682_Architectural_Technical_Debt_Identification_the_Research_Landscape|Architectural Technical Debt Identification: the Research Landscape]], | ||
| + | * author = {Verdecchia, Roberto and Malavolta, Ivano and Lago, Patricia}, | ||
| + | * year = {2018}, | ||
| + | * month = {05}, | ||
| + | * doi = {10.1145/3194164.3194176} | ||
| + | * Architectural Technical Debt (ATD) regards sub-optimal design decisions that bring short-term benefits to the cost of long-term gradual deterioration of the quality of the architecture of a software system. The identification of ATD strongly influences the technical and economic sustainability of software systems and is attracting growing interest in the scientific community. During the years several approaches for ATD identification have been conceived, each of them addressing ATD from different perspectives and with heterogeneous characteristics. In this paper we apply the systematic mapping study methodology for identifying, classifying, and evaluating the state of the art on ATD identification from the following three perspectives: publication trends, characteristics, and potential for industrial adoption. Specifically, starting from a set of 509 potentially relevant studies, we systematically selected 47 primary studies and analyzed them according to a rigorously-defined classification framework. The analysis of the obtained results supports both researchers and practitioners by providing (i) an assessment of current research trends and gaps in ATD identification, (ii) a solid foundation for understanding existing (and future) research on ATD identification, and (iii) a rigorous evaluation of its potential for industrial adoption. | ||
| + | - [[ https://www.cs.drexel.edu/~lx52/LuXiao/papers/FSE-TD-14.pdf|Titan: A Toolset That Connects Software Architecture with Quality Analysis]] | ||
| + | * Lu Xiao, Yuanfang Cai, and Rick Kazman. | ||
| + | * 2014. | ||
| + | * ACM SIGSOFT International Symposium on Foundations of Software Engineering. | ||
| + | * 763–766 | ||
| + | - [[http://aircconline.com/ijsea/V9N5/9518ijsea01.pdf|[INVESTIGATE,IDENTIFY AND ESTIMATE THE TECHNICAL DEBT: A SYSTEMATIC MAPPING STUDY]] | ||
| + | * Benidris, M., Ammar, H., & Dzielski, D. | ||
| + | * 2018 | ||
| + | * International Journal of Software Engineering & Applications (IJSEA). | ||
| + | * https://doi.org/10.5121/ijsea.2018.9501 | ||
| </panel> | </panel> | ||
| </accordion> | </accordion> | ||
teaching/reverse/2018/references.txt · Last modified: 2018/12/16 17:40 by blay
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