- title = "A Mono-and Multi-objective Approach for Recommending Software Refactoring",
- author = "Ali Ouni",
- year = "2014",
- school = "University of Montreal",
- address = "Canada",
- month = oct,
- keywords = "genetic algorithms, genetic programming, SBSE, Software Maintenance, Code-smells, Refactoring",
-
URL = "
https://sites.google.com/site/ouniaali/ouni_PhD_thesis_2014.pdf",
-
URL = "
http://hdl.handle.net/1866/11613",
-
URL = "https://papyrus.bib.umontreal.ca/xmlui/handle/1866/11613",
-
URL = "https://papyrus.bib.umontreal.ca/xmlui/bitstream/handle/1866/11613/Ouni_Ali_2014_these.pdf",
- size = "245 pages",
- abstract = "Les systemes logiciels sont devenus de plus en plus repondus et importants dans notre societe. Ainsi, il y a un besoin constant de logiciels de haute qualite. Pour ameliorer la qualite de logiciels, l'une des techniques les plus utilisees est le refactoring qui sert A ameliorer la structure d'un programme tout en preservant son comportement externe. Le refactoring promet, s'il est applique convenablement, A ameliorer la comprehensibilite, la maintenabilite et l'extensibilite du logiciel tout en ameliorant la productivite des programmeurs. En general, le refactoring pourra s'appliquer au niveau de specification, conception ou code. Cette these porte sur l'automatisation de processus de recommandation de refactoring, au niveau code, s'appliquant en deux etapes principales: 1) la detection des fragments de code qui devraient a ameliores (e.g., les defauts de conception), et 2) l'identification des solutions de refactoring A appliquer. Pour la premiere etape, nous traduisons des regularites qui peuvent a trouves dans des exemples de defauts de conception. Nous utilisons un algorithme genetique pour generer automatiquement des regles de detection A partir des exemples de defauts. Pour la deuxieme etape, nous introduisons une approche se basant sur une recherche heuristique. Le processus consiste A trouver la sequence optimale d'operations de refactoring permettant d'ameliorer la qualite du logiciel en minimisant le nombre de defauts tout en priorisant les instances les plus critiques. De plus, nous explorons d'autres objectifs A optimiser: le nombre de changements requis pour appliquer la solution de refactoring, la preservation de la semantique, et la consistance avec l'historique de changements. Ainsi, reduire le nombre de changements permets de garder autant que possible avec la conception initiale. La preservation de la semantique assure que le programme restructure est semantiquement coherent. De plus, nous utilisons l'historique de changement pour suggerer de nouveaux refactorings dans des contextes similaires. En outre, nous introduisons une approche multi-objective pour ameliorer les attributs de qualite du logiciel (la flexibilite, la maintenabilite, etc.), fixer les mauvaises a pratiques de conception (defauts de conception), tout en introduisant les bonnes a pratiques de conception (patrons de conception).",
-
abstract = "Software systems have become prevalent and important
in our society. There is a constant need for
high-quality software. Hence, to improve software
quality, one of the most-used techniques is the
refactoring which improves design structure while
preserving the external behaviour. Refactoring has
promised, if applied well, to improve software
readability, maintainability and extendibility while
increasing the speed at which programmers can write and
maintain their code. In general, refactoring can be
performed in various levels such as the requirement,
design, or code level. In this thesis, we mainly focus
on the source code level where automated refactoring
recommendation can be performed through two main steps:
1) detection of code fragments that need to be
improved/fixed (e.g., code-smells), and 2)
identification of refactoring solutions to achieve this
goal. For the code-smells identification step, we
translate regularities that can be found in such
code-smell examples into detection rules. To this end,
we use genetic programming to automatically generate
detection rules from examples of code-smells.
For the refactoring identification step, a search-based approach is used. The process aims at finding the optimal sequence of refactoring operations that improve software quality by minimizing the number of detected code-smells while prioritizing the most critical ones. In addition, we explore other objectives to optimize using a multi-objective approach: the code changes needed to apply refactorings, semantics preservation, and the consistency with development change history. Hence, reducing code changes allows us to keep as much as possible the initial design. On the other hand, semantics preservation insures that the refactored program is semantically coherent, and that it models correctly the domain-semantics. Indeed, we use knowledge from historical code change to suggest new refactorings in similar contexts.
Furthermore, we introduce a novel multi-objective approach to improve software quality attributes (i.e., flexibility, maintainability, etc.), fix bad design practices (i.e., code-smells) while promoting good design practices (i.e., design patterns).",
- notes = "in english",
