diff --git a/seance5_6h/consignes_BE#5.md b/seance5_6h/consignes_BE#5.md
index 836de08624918b6ab9a405566e7dc6e58cce1e6a..b132ff3cf55b3f6fdb18cdf33d6ed5393e9b125b 100644
--- a/seance5_6h/consignes_BE#5.md
+++ b/seance5_6h/consignes_BE#5.md
@@ -1,16 +1,25 @@
 ### Consignes pour le rendu (BE #5 - INF-TC2)
 
-Ce BE est le second devoir à rendre concernant INF-TC2. Le compte-rendu (CR) de ce travail devra être déposé sur `Pedagogie1`, sur l'espace de dépôt spécifique à votre groupe. Et cela dans un **délai de deux semaines après la dernière séance consacrée** (délai de rigueur, aucun travail accepté au delà de cette date). Ces 2 semaines ne tiennent pas compte d'éventuelles vacances.
+Ce BE est le second devoir à rendre concernant INF-TC2. Le compte-rendu (CR) de votre travail devra être déposé sur `Pedagogie1`, sur l'espace de dépôt spécifique à votre groupe. Et cela dans un **délai d'une (1) semaines après la dernière séance consacrée** (délai de rigueur, aucun travail accepté au delà de cette date). Cette semaine ne tient pas compte d'éventuelles vacances. Si vous avez un doute, le plus simple est de contrôler la date pour votre groupe sur `Pedagogie1`.
 
 **Consignes:**
 
-  - Le travail peut être individuel ou en binôme. Si vous travaillez en binôme, **un seul dépôt suffit !**.   
- - Le dépôt consistera en une unique archive (zip, rar) contenant l'ensemble des fichiers suivants :   
+  - Le travail peut être individuel ou en binôme. Si vous travaillez en binôme, **un seul dépôt suffit !**.    
+  - Le dépôt consistera en une unique archive (zip, rar) contenant l'ensemble des fichiers suivants :     
      - Le fichier _Python_, appelé *Pendu.py*, contenant toutes les classes (**FenPrincipale**, **ZoneAffichage** et **MonBoutonLettre**), et un programme principal permettant de lancer l'application.
      - Le fichier *mots.txt* et la classe *formes.py* (même s'ils n'ont pas été modifiés). 
-     - un rapport (format _word_, _pdf_, ou miex encore _markdown_ !) contenant      
-         - une en-tête où devront figurer le nom des élèves, leur numéro de groupe, le nom de l'encadrant ainsi que le titre du BE.   
-         - un diagramme de classes UML complet de votre application (pensez à utiliser [diagrams](https://app.diagrams.net) !), avec les liens entre les classes, les cardinalités, les attributs (privés ou publics), et les méthodes (elles-mêmes publiques ou privées).  
+     - un rapport (format _word_, _pdf_, ou mieux encore _markdown_ !) contenant     
+         - Une en-tête où devront figurer le nom des élèves, leur numéro de groupe, le nom de l'encadrant ainsi que le titre du BE.   
+         - Un diagramme de classes UML complet de votre application (pensez à utiliser [diagrams](https://app.diagrams.net) !), avec les liens entre les classes, les cardinalités, les attributs (privés ou publics), et les méthodes (elles-mêmes publiques ou privées).  
          - Une présentation du code de la DERNIÈRE PARTIE UNIQUEMENT de votre travail (partie intitulée _Améliorations du jeu_). Vous pouvez utilisez des explications textuelles, des diagrammes, des copies d'écran...
 
- - L'archive devra nécessairement porter le nom suivant : *nom1-BE5.zip* ou *nom1-nom2-BE5.zip* (pour les étourdis, pensez à remplacer *nom1* et *nom2* par vos propres noms :-) )
+  - L'archive devra nécessairement porter le nom suivant : *nom1-BE5.zip* ou *nom1-nom2-BE5.zip* (pour les étourdis, pensez à remplacer *nom1* et *nom2* par vos propres noms :-) )
+
+**Critères d'évaluation du travail**
+
+Voici une liste (non exhaustive) de critères qui permettront à vos encadrants d'évaluer vos requêtes :
+
+  - **Qualité du rapport** : apparence visuelle globale, orthographe, structure du rapport claire et cohérente. Présence et complétude du diagramme de classes. Qualité des représentations graphiques.       
+  - **Qualité du code** : est-ce qu'il fonctionne sans erreur, le code est-il suffisamment commenté et aéré ? Tests multiples avec des paramètres inattendus ou erronés. Interception des erreurs par des exceptions.   
+  - **Qualité de l'interface** : aspect visuel de l'interface graphique.
+ 
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diff --git a/seance5_6h/figures/Arbre_scene_pendu.drawio b/seance5_6h/figures/Arbre_scene_pendu.drawio
new file mode 100644
index 0000000000000000000000000000000000000000..0ad3608b2925a2eb28df0aae78237fbff7d67a78
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new file mode 100644
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</diagram></mxfile>
\ No newline at end of file
diff --git a/seance5_6h/figures/pendu1.png b/seance5_6h/figures/pendu1.png
new file mode 100644
index 0000000000000000000000000000000000000000..98071a00ef79752523266a8d6dd59ca23c29d2f6
Binary files /dev/null and b/seance5_6h/figures/pendu1.png differ
diff --git a/seance5_6h/formes.py b/seance5_6h/formes.py
index 853690f7512ff4337dbded5a41e5fb5ca1bf78aa..964e35cbe688d0fbd2d88b01dffa8f70f6dc8320 100644
--- a/seance5_6h/formes.py
+++ b/seance5_6h/formes.py
@@ -13,13 +13,10 @@ class Forme:
         self.x += dx
         self.y += dy
 
-    def setState(self, s):
-        self.__canevas.itemconfig(self._item, state=s)
-
 class Rectangle(Forme):
     def __init__(self, canevas, x, y, l, h, couleur):
         Forme.__init__(self, canevas, x, y)
-        self._item = canevas.create_rectangle(x, y, x+l, y+h, fill=couleur, state="hidden")
+        self._item = canevas.create_rectangle(x, y, x+l, y+h, fill=couleur)
         self.__l = l
         self.__h = h
     
@@ -38,15 +35,15 @@ class Rectangle(Forme):
                self.y <= y <= self.y + self.__h
 
     def redimension_par_points(self, x0, y0, x1, y1):
-        self.x   = min(x0, x1)
-        self.y   = min(y0, y1)
+        self.x = min(x0, x1)
+        self.y = min(y0, y1)
         self.__l = abs(x0 - x1)
         self.__h = abs(y0 - y1)
 
 class Ellipse(Forme):
     def __init__(self, canevas, x, y, rx, ry, couleur):
         Forme.__init__(self, canevas, x, y)
-        self._item = canevas.create_oval(x-rx, y-ry, x+rx, y+ry, fill=couleur, state="hidden")
+        self._item = canevas.create_oval(x-rx, y-ry, x+rx, y+ry, fill=couleur)
         self.__rx = rx
         self.__ry = ry
 
diff --git a/seance5_6h/seance5_6h.md b/seance5_6h/seance5_6h.md
index d4749c3584aadc0fab58beead2348a8df96c6fe4..c704c4c959a5514b6d7682fda78ac51711410364 100644
--- a/seance5_6h/seance5_6h.md
+++ b/seance5_6h/seance5_6h.md
@@ -4,8 +4,7 @@
 
 # BE #5 : Le jeu du Pendu
 
-
-L'objectif de ce BE est de réaliser le `jeu du Pendu`. Pour rappel, ce jeu consiste à essayer de découvrir un mot qui est affiché de manière masquée (chacune de ses lettres est remplacée par le caractère _'*'_). Pour cela, le joueur sélectionne une lettre sur le clavier virtuel. Si elle fait partie du mot, alors le mot à découvrir est ré-affiché en laissant apparaître cette lettre en clair. Si par contre le mot ne contient pas la lettre sélectionnée, alors le compteur de coups ratés augmente d'un et l'élément suivant du pendu est ajouté au dessin. Le joueur gagne s’il a pu découvrir le mot avant que le pendu ne soit complètement affiché (au delà de 10 coups manqués). La figure ci-dessous présente l'interface que nous allons construire ; oui, les couleurs piquent un peu aux yeux, mais ça pourra vous aider à répondre à la première question !
+L'objectif de ce BE est de réaliser le `jeu du Pendu`. Pour rappel, ce jeu consiste à essayer de découvrir un mot qui est affiché de manière masquée (chacune de ses lettres est remplacée par le caractère _'*'_). Pour cela, le joueur sélectionne une lettre sur le clavier virtuel. Si elle fait partie du mot, alors le mot à découvrir est ré-affiché en laissant apparaître cette lettre en clair. Si par contre le mot ne contient pas la lettre sélectionnée, alors le compteur de coups ratés augmente d'un et l'élément suivant du pendu est ajouté au dessin. Le joueur gagne s'il a pu découvrir le mot avant que le pendu ne soit complètement affiché (au delà de 10 coups manqués). La figure ci-dessous présente l'interface que nous allons construire ; oui, les couleurs piquent un peu aux yeux, mais ça pourra vous aider à répondre à la première question !
 
 <center><img src="figures/pendu0.png" style="width:60%"/></center>
 
@@ -18,7 +17,8 @@ Ce BE fera l'objet d'un compte-rendu (CR), seul ou en binôme. L'énoncé corres
 
 __Exercice 1 -__ Dessinez l'arbre de scène correspondant à la capture d'écran ci-dessus.    
 
-__Exercice 2 -__ En vous inspirant de l'organisation des classes du BE #4, programmez l'interface statique (_i.e._ sans commande) en distinguant la classe __FenPrincipale__ et la classe __ZoneAffichage__. À ce stade, à la place des 26 boutons du clavier (correspondant aux 26 lettres en majuscule), placez un simple bouton _"A"_  car le dessin du clavier est traité dans l'exercice suivant.
+
+__Exercice 2 -__ En vous inspirant de l'organisation des classes du BE #4, programmez l'interface statique (_i.e._ sans programmer les commandes) en distinguant la classe __FenPrincipale__ et la classe __ZoneAffichage__. À ce stade, à la place des 26 boutons du clavier (correspondant aux 26 lettres en majuscule), placez un simple bouton _"A"_  car le dessin du clavier est traité dans l'exercice suivant.
 
 Testez votre interface et faites les ajustements nécessaires pour obtenir une apparence proche de celle donnée en exemple (mais sans le clavier, et avec les couleurs qui vous conviennent !). Le programme principal se réduira à ces quelques lignes :
 ```python
@@ -56,29 +56,22 @@ Une partie ne pourra commencer que si le joueur appuie sur le bouton "Nouvelle p
 __Exercice 4 -__ L'appuie sur ce bouton doit provoquer une ré-initialisation de toute l'interface : 
 
   - Tirer un nouveau mot au hasard dans le fichier [mots.txt](./mots.txt) (à votre disposition à côté de cet énoncé) et réinitialiser le mot à découvrir;   
-  - Dégriser les boutons-lettres (```state=NORMAL```);    
+  - Dégriser les boutons-lettres (par la commande suivante ```unBouton.config(state=NORMAL)```);    
   - Effacer le dessin du pendu (question traitée dans la partie suivante de cet énoncé).
 
-_Quelques conseils pour l’implémentation_
+_Quelques conseils pour l'implémentation_
 
-  - Au chargement de l'application, pensez à griser toutes les lettres du clavier. 
+  - Au lancement de l'application, pensez à griser toutes les lettres du clavier (l'utilisateur comprend alors qu'il doit appuyer sur le bouton "Nouvelle partie"). 
   - Utilisez la méthode suivante pour charger les mots du fichier _mots.txt_ dans une liste privée appelée _self.\_\_mots_. Cette liste sera chargée une fois pour toute au lancement de l'application, et utilisée à chaque nouvelle partie.   
 ```python
 def chargeMots(self):
-	f = open('mots.txt','r')
+	f = open('mots.txt', 'r')
 	s = f.read()
 	self.__mots = s.split('\n')
 	f.close()
 ```   
   - Pour tirer un nouveau mot au hasard, utilisez la fonction _randint(...)_ (```from random import randint```).
 
-<!--
-_Tip_ Vous pouvez créer des attributs différents pour sauvegarder 
-
-  - le mot à deviner et     
-  - le mot à deviner mais partiellement caché par des étoiles (celui qui sera affiché sur l'interface pour le joueur).
--->
-
 Pensez à vérifier que votre application est bien fonctionnelle à ce stade.
 
 
@@ -89,15 +82,15 @@ Le fait d'appuyer sur une lettre du clavier virtuel doit provoquer un certain no
    - griser le bouton-lettre qui vient d'être cliqué (```state=DISABLED```);    
    - faire apparaître autant de fois que nécessaire la lettre cliquée dans le mot à découvrir;  
    - vérifier si la partie est perdue, gagnée, ou si elle se poursuit;      
-   - éventuellement, compléter le dessin du pendu si la lettre n'est pas présente dans le mot (question traitée dans la partie suivante de cet énoncé).
+   - éventuellement, compléter le dessin du pendu si la lettre n'est pas présente dans le mot (action traitée dans la partie suivante de cet énoncé).
 
-Chaque bouton doit pouvoir être identifié par la fonction de _callback_ appelée ici _cliquer_. Or il n'est pas possible de passer le numéro du bouton-lettre au _callback_ (aucun argument n'est admis). Nous allons procéder en créant notre propre classe de  boutons, héritant de la classe __Button__.
+Chaque bouton doit pouvoir être identifié par la fonction de _callback_ appelée ici _cliquer_. Or il n'est pas possible de passer le numéro du bouton-lettre au _callback_ (aucun argument n'est permis). Nous allons procéder en créant notre propre classe de boutons, héritant de la classe __Button__.
 
 __Exercice 5 -__ Suivez les étapes proposées
 
-  1. Créez la classe __MonBoutonLettre__, qui hérite de la classe __Button__, et qui sauvegarde, en tant qu'attribut privé, la lettre correspondant au bouton (ou le numéro du bouton).  Modifiez en conséquence le constructeur de la classe __FenPrincipale__ pour que le clavier virtuel soit composé de 26 instances de la classe __MonBoutonLettre__. 
-  1. Créer la fonction de callback _cliquer(self)_ dans la classe __MonBoutonLettre__, qui fera notamment appel à la méthode _traitement(...)_ de la classe __FenPrincipale__.    
-  1. Programmez la méthode _traitement(...)_ dont l'objectif est de mettre à jour l'affichage du mot.    
+  1. Créer la classe __MonBoutonLettre__, qui hérite de la classe __Button__, et qui sauvegarde, en tant qu'attribut privé, la lettre correspondant au bouton (ou le numéro du bouton).  Modifier en conséquence le constructeur de la classe __FenPrincipale__ pour que le clavier virtuel soit composé de 26 instances de la classe __MonBoutonLettre__. 
+  1. Créer la fonction de callback _cliquer(self)_ dans la classe __MonBoutonLettre__, qui fera notamment appel à une méthode _traitement(...)_ de la classe __FenPrincipale__.    
+  1. Programmer cette méthode _traitement(...)_ dont l'objectif est de mettre à jour l'affichage du mot.    
     - Si la partie est gagnée, bloquez l'utilisation du clavier, et affichez un texte qui indique au joueur que c'est gagné !  
     - La partie est perdue quand le nombre de coups dépasse 10 (c'est le nombre d'éléments nécessaires pour dessiner entièrement le pendu). Bloquez alors l'utilisation du clavier, et affichez un texte qui indique au joueur que c'est perdu !  
 
@@ -107,13 +100,25 @@ __Exercice 5 -__ Suivez les étapes proposées
 ---  
 ## Partie 3 - Le dessin du pendu (75 min.)
 
-Cet partie est consacrée au dessin progressif du pendu, au fur et à mesure des échecs du joueur. Ce dessin s'appuie sur les connaissances acquises lors du BE #4 et les classes du fichier [formes.py](./formes.py), disponible à côté de cet énoncé (Attention le fichier utilisé ici est très légèrement différent de celui du BE #4, merci de bien télécharger cette version). 
+Cette partie est consacrée au dessin progressif du pendu, au fur et à mesure des échecs du joueur. Ce dessin s'appuie sur les connaissances acquises lors du BE #4 et les classes du fichier [formes.py](./formes.py), disponible à côté de cet énoncé pour ceux qui le souhaitent. L'idée est de créer le pendu comme une liste de rectangles et d'ellipses (10 pièces doivent suffire).
+
+Le parti pris ici est de créer et de dessiner les 10 pièces du pendu dans le constructeur de la classe __ZoneAffichage__, mais en leur affectant la propriété `state="hidden"`, de telle sorte qu'elles ne soient pas visibles. Ce n'est qu'au fur et à mesure de l'avancement d'une partie que les pièces apparaissent sur le canevas, en passant du statut `"hidden"` au statut `"normal"`. La réinitialisation liée à une nouvelle partie consistera alors à cacher l'ensemble des pièces. 
 
-__Exercice 6 -__
+*Remarque* : Notez qu'il aurait aussi été possible d'adopter un autre point de vue qui consisterait à créer et dessiner chaque pièce lors de chaque partie.
 
-Pour cela, l'idée est de créer le pendu comme une liste de rectangles et d'ellipses (10 pièces doivent suffire), dans le constructeur de la classe __ZoneAffichage__. Pour faire disparaître le pendu (au moment de la création des pièces, ou au moment de la réinitialisation d'une partie p. ex.), on affectera aux pièces l'état caché (```state=hidden```). Pour faire apparaître les pièces progressivement (sur ordre de la méthode _traitement(...)_), on leur affectera l'état normal (```state=normal```).
+__Préliminaires sur le fichier [formes.py](./formes.py)__ 
+
+  - Modifier le fichier [formes.py](./formes.py) de telle manière que les rectangles et les ellipses soient cachés lors leur création.    
+  - Il est nécessaire de prévoir une méthode _setState(s)_ qui permette de changer ce statut. La méthode étant identique pour les rectangles et pour les ellipses, il convient de la factoriser dans la classe __Forme__ :
+```python
+def setState(self, s):
+    self.__canevas.itemconfig(self._item, state=s)
+```
+
+__Exercice 6 -__ Mettez en place la stratégie décrite ci-dessus pour terminer l'application.
+
+Pour gagner un peu de temps, voici un exemple de jeu de pièces (avec leur position et leurs dimensions) qui permettent de dessiner le pendu de la première figure.
 
-Pour gagner un peu de temps, voici un exemple de coordonnées pour les éléments graphiques :
 ```python
 # Base, Poteau, Traverse, Corde
 Rectangle(self, 50,  270, 200,  26, "brown")
@@ -130,21 +135,21 @@ Rectangle(self, 203, 150,  40,  10, "black")
 Rectangle(self, 175, 205,  10,  40, "black")
 Rectangle(self, 191, 205,  10,  40, "black")
 ```
-
+Rien ne vous empêche de customiser votre pendu !
 
 ---
 ## Partie 4 - Améliorations du jeu (autonomie)
 
-Voici quelques améliorations possibles pour le jeu, seule la dernière est considérée comme un bonus.
+Voici quelques améliorations pour le jeu, à rendre compte dans votre CR. Seule la dernière amélioration est considérée comme un bonus.
 
-__Exercice 7 - Apparence__ Développez le code qui permet au joueur de choisir les couleurs principales de l’application (par un  menus, par des boutons...).
+__Exercice 7 - Apparence__ Développez le code qui permet au joueur de choisir les couleurs principales de l'application (par un  menus, par des boutons...).
 
-__Exercice 8 - Bouton Triche__ Implémentez un bouton "Triche" qui permet de revenir en arrière d'un coup, pendant la partie.
+__Exercice 8 - Triche !__ Implémentez une technique "_Undo_" qui permet de revenir de un ou plusieurs coups en arrière, au cours d'une partie.
 
-__Bonus - Score joueur__ Implémentez un système de sauvegarde des parties jouées par un joueur (identifié par un pseudo demandé au joueur). Techniquement, on pourra créer une base de données _SQL_ (_cf_ BE #3), appelée _pendu.db_, qui stockera une table avec les joueurs et une table avec les parties jouées par ces joueurs, selon le schéma suivant :
+__Bonus - Score joueur__ Implémentez un système de sauvegarde des échecs et des succès d'un joueur (identifié par un pseudo demandé au joueur en début de partie). Techniquement, on pourra créer une base de données _SQL_ (_cf_ BE #3), appelée _pendu.db_, qui stockera une table avec les joueurs et une table avec les parties jouées par ces joueurs, selon le schéma suivant :
 
 <center><img src="figures/TableSQLJeuPendu.png" style="width:30%"/></center>
 
 Le score pour chaque mot pourra être défini comme le taux de caractères trouvés (ainsi un score de 1.0 désigne un succès).
 
-_Remarque_ : on ne demande pas ici d'afficher un historique ou des statistiques sur un joueur. Pour consulter la base, on pourra simplement utiliser ```DB Browser for SQLite```.
+Dans un premier temps, pour vérifier que votre programme fonctionne, vous pouvez consulter la base _pendu.db_ à l'aide de ```DB Browser for SQLite```. Si vous le souhaitez, vous pouvez alors intégrer à votre application un affichage de l'historique des parties du joueur et/ou de ses performances.