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36

Nadjib LAZAAR


Nadjib Lazaar received his Master Sc. and PhD degrees, both in computer science from University of Rennes1, France, in 2008 and 2011 respectively. Following his PhD, he worked as an INRIA postdoctoral researcherat INRIA-Microsoft Research Joint Center Paris-Saclay till September 2012. In 2012/2013, he worked as post-doctoral researcher at the European ICON project FP7 FET-Open in Montpellier, France. He is currently atenured assistant professor at the University of Montpellier, and a co-head of the COCONUT team at LIRMMlab. His research interests are situated at the crossroads of Constraint Programming (CP), Data Mining (DM),Machine Learning (ML) and Software Testing (ST). In particular, He is interested in developing techniquesand tools for: Constraint Acquisition; Declarative Data Mining; Constraint-Based Software Testing; SoftwareVerification and Validation via Artificial Intelligence.


Journal articles3 documents

Conference papers26 documents

  • Mohamed-Bachir Belaid, Christian Bessière, Nadjib Lazaar. Constraint Programming for Association Rules. SDM: SIAM International Conference on Data Mining, May 2019, Calgary, Canada. pp.127-135, ⟨10.1137/1.9781611975673.15⟩. ⟨lirmm-02089719⟩
  • Mathieu Collet, Arnaud Gotlieb, Nadjib Lazaar, Morten Mossige. Stress Testing of Single-Arm Robots Through Constraint-Based Generation of Continuous Trajectories. AiTest: Artificial Intelligence Testing, Apr 2019, San francisco, United States. pp.121-128, ⟨10.1109/AITest.2019.00014⟩. ⟨lirmm-02089742⟩
  • Carlo Ieva, Arnaud Gotlieb, Souhila Kaci, Nadjib Lazaar. Deploying Smart Program Understanding on a Large Code Base. AiTest: Artificial Intelligence Testing, Apr 2019, San Francisco, United States. pp.73-80, ⟨10.1109/AITest.2019.000-4⟩. ⟨lirmm-02089733⟩
  • Noureddine Aribi, Nadjib Lazaar, Yahia Lebbah, Samir Loudni, Mehdi Maamar. A Multiple Fault Localization Approach based on Multicriteria Analytical Hierarchy Process. AiTest: Artificial Intelligence Testing, Apr 2019, San Francisco, United States. pp.1-8, ⟨10.1109/AITest.2019.00-16⟩. ⟨lirmm-02089746⟩
  • Mohamed-Bachir Belaid, Christian Bessière, Nadjib Lazaar. Constraint Programming for Mining Borders of Frequent Itemsets. IJCAI: International Joint Conference on Artificial Intelligence, Aug 2019, Macao, China. pp.1064-1070, ⟨10.24963/ijcai.2019/149⟩. ⟨lirmm-02310629⟩
  • Carlo Ieva, Arnaud Gotlieb, Souhila Kaci, Nadjib Lazaar. Discovering Program Topoi Through Clustering. AAAI Conference on Artificial Intelligence, Feb 2018, New Orleans, United States. ⟨lirmm-01790874⟩
  • Christian Bessière, Nadjib Lazaar, Mehdi Maamar. User's Constraints in Itemset Mining. CP: Principles and Practice of Constraint Programming, Aug 2018, Lille, France. pp.537-553, ⟨10.1007/978-3-319-98334-9_35⟩. ⟨lirmm-01896872⟩
  • Hajar Addi, Christian Bessière, Redouane Ezzahir, Nadjib Lazaar. Time-Bounded Query Generator for Constraint Acquisition. CPAIOR: Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Jun 2018, Delft, Netherlands. pp.1-17, ⟨10.1007/978-3-319-93031-2_1⟩. ⟨lirmm-01897928⟩
  • Mehdi Maamar, Christian Bessière, Patrice Boizumault, Nadjib Lazaar, Yahia Lebbah, et al.. Closed-Pattern : Une contrainte globale pour l’extraction de motifs fréquents fermés. JFPC: Journées Francophones de Programmation par Contraintes, Jun 2017, Montreuil sur Mer, France. ⟨hal-02088910⟩
  • Abderrazak Daoudi, Younes Mechqrane, Christian Bessière, Nadjib Lazaar, El Houssine Bouyakhf. Constraint Acquisition Using Recommendation Queries
. IJCAI: International Joint Conference on Artificial Intelligence, Jul 2016, New York City, United States. pp.720-726. ⟨lirmm-01374716⟩
  • Robin Arcangioli, Christian Bessière, Nadjib Lazaar. Multiple Constraint Aquisition. IJCAI: International Joint Conference on Artificial Intelligence, Jul 2016, New York City, United States. pp.698-704. ⟨lirmm-01374712⟩
  • Nadjib Lazaar, Yahia Lebbah, Samir Loudni, Mehdi Maamar, Valentin Lemière, et al.. A Global Constraint for Closed Frequent Pattern Mining. CP: Principles and Practice of Constraint Programming, Sep 2016, Toulouse, France. pp.333-349, ⟨10.1007/978-3-319-44953-1_22⟩. ⟨lirmm-01374719⟩
  • Abderrazak Daoudi, Nadjib Lazaar, Younes Mechqrane, Christian Bessière, El Houssine Bouyakhf. Detecting Types of Variables for Generalization in Constraint Acquisition. ICTAI: International Conference on Tools with Artificial Intelligence, Nov 2015, Vietri sul Mare, Italy. pp.413-420, ⟨10.1109/ICTAI.2015.69⟩. ⟨lirmm-01276187⟩
  • Noureddine Aribi, Souhila Kaci, Nadjib Lazaar. Towards an MDD-based representation of preferences. CPCR+ITWP@IJCAI, Jul 2015, Buenos Aires, Argentina. pp.34-34. ⟨lirmm-01276183⟩
  • Mehdi Maamar, Nadjib Lazaar, Samir Loudni, Yahia Lebbah. Localisation de fautes à l’aide de la fouille de données sous contraintes. COSI: Colloque sur l'Optimisation et les Systèmes d'Information, Jun 2015, Oran, Algérie. ⟨lirmm-01276185⟩
  • Christian Bessière, Remi Coletta, Nadjib Lazaar. Solve a Constraint Problem without Modeling It. ICTAI: International Conference on Tools with Artificial Intelligence, Nov 2014, Limasso, Cyprus. pp.1-7, ⟨10.1109/ICTAI.2014.12⟩. ⟨lirmm-01228368⟩
  • Christian Bessière, Remi Coletta, Abderrazak Daoudi, Nadjib Lazaar, Younes Mechqrane, et al.. Boosting Constraint Acquisition via Generalization Queries. ECAI: European Conference on Artificial Intelligence, Aug 2014, Prague, Czech Republic. pp.099-104, ⟨10.3233/978-1-61499-419-0-99⟩. ⟨lirmm-01067472⟩
  • Christian Bessière, Remi Coletta, Emmanuel Hébrard, George Katsirelos, Nadjib Lazaar, et al.. Acquisition de contraintes avec des requêtes partielles. JFPC: Journées Francophones de Programmation par Contraintes, Jun 2014, Angers, France. ⟨lirmm-01229549⟩
  • Christian Bessière, Remi Coletta, Abderrazak Daoudi, Nadjib Lazaar, Younes Mechqrane, et al.. Acquisition de contraintes par requêtes de généralisation. JFPC: Journées Francophones de Programmation par Contraintes, Jun 2014, Angers, France. ⟨lirmm-01229548⟩
  • Christian Bessière, Remi Coletta, Emmanuel Hébrard, George Katsirelos, Nadjib Lazaar, et al.. Constraint Acquisition via Partial Queries. IJCAI: International Joint Conference on Artificial Intelligence, Aug 2013, Beijing, China. pp.475-481. ⟨lirmm-00830325⟩
  • Christian Bessière, Remi Coletta, Emmanuel Hebrard, George Katsirelos, Nadjib Lazaar, et al.. Constraint acquisition via partial queries. IJCAI 2013 - 23rd International Joint Conference on Artificial Inteligence, Aug 2013, Pékin, China. ⟨hal-02749361⟩
  • Said Jabbour, Nadjib Lazaar, Youssef Hamadi, Michèle Sebag. Cooperation control in Parallel SAT Solving: a Multi-armed Bandit Approach. Workshop on Bayesian Optimization & Decision Making, 2012, Lake Tahoe, United States. ⟨hal-00870946⟩
  • Arnaud Gotlieb, Tristan Denmat, Nadjib Lazaar. Constraint-based reachability. Infinity workshop 2012, Aug 2012, Paris, France. ⟨10.4204/EPTCS.107.4⟩. ⟨hal-00807856⟩
  • Nadjib Lazaar, Arnaud Gotlieb, Yahia Lebbah. Fault Localization in Constraint Programs. 22th Int. Conf. on Tools with Artificial Intelligence (ICTAI'2010), 2010, Arras, France. ⟨hal-00699235⟩
  • Nadjib Lazaar, Arnaud Gotlieb, Yahia Lebbah. On Testing Constraint Programs. 16th Int. Conf. on Principles and Practices of Constraint Programming (CP'2010), Sep 2010, St Andrews, Scotland, United Kingdom. ⟨hal-00699237⟩
  • Nadjib Lazaar, Arnaud Gotlieb, Yahia Lebbah. Vers une Théorie du Test des programmes à contraintes. Cinquièmes Journées Francophones de Programmation par Contraintes, Orléans, juin 2009, Jun 2009, France. pp.65-75. ⟨hal-00387850⟩

Book sections1 document

Reports3 documents

  • Nadjib Lazaar, Youssef Hamadi, Said Jabbour, Michèle Sebag. Cooperation control in Parallel SAT Solving: a Multi-armed Bandit Approach. [Research Report] RR-8070, INRIA. 2012, pp.18. ⟨hal-00733282v2⟩
  • Nadjib Lazaar, Nourredine Aribi, Arnaud Gotlieb, Yahia Lebbah. Negation for Free!. [Research Report] RR-7749, INRIA. 2011, pp.16. ⟨inria-00629657⟩
  • Nadjib Lazaar, Arnaud Gotlieb, Lebbah Yahia. On Testing Constraint Programs. [Research Report] RR-7291, INRIA. 2010. ⟨inria-00483410⟩

Software3 documents