Optimization Techniques for Algorithmic Debugging

[EN] Nowadays, undetected programming bugs produce a waste of billions of dollars per year to private and public companies and institutions. In spite of this, no significant advances in the debugging area that help developers along the software development process have been achieved yet. In fact, the same debugging techniques that were used 20 years ago are still being used now. Along the time, some alternatives have appeared, but there still is a long way for them to be useful enough to get into the software development process. One of them is algorithmic debugging, which abstracts the information the user has to investigate to debug the program, allowing them to focus on what is happening instead of how it is happening. This abstraction comes at a price: the granularity level of the bugs that can be detected allows for isolating wrongly implemented functions, but which part of them contains the bug cannot be found out yet. This thesis focusses on improving algorithmic debugging in many aspects. Concretely, the main aims of this thesis are to reduce the time the user needs to detect a programming bug as well as to provide the user with more detailed information about where the bug is located. To achieve these goals, some techniques have been developed to start the debugging sessions as soon as possible, to reduce the number of questions the user is going to be asked about, and to augment the granularity level of those bugs that algorithmic debugging can detect, allowing the debugger in this way to keep looking for bugs even inside functions. As a result of this thesis, three completely new techniques have been defined, an already existent technique has been improved, and two new algorithmic debugging search strategies have been defined that improve the already existent ones. Besides these theoretical results, a fully functional algorithmic debugger has been implemented that contains and supports all these techniques and strategies. This debugger is written in Java, and it debugs Java code. The election of this language is justified because it is currently one of the most widely extended and used languages. Also because it contains an interesting combination of unsolved challenges for algorithmic debugging. To further increase its usability, the debugger has been later adapted as an Eclipse plugin, so it could be used by a wider number of users. These two debuggers are publicly available, so any interested person can access them and continue with the research if they wish so.[ES] Hoy en día, los errores no detectados de programación suponen un gasto de miles de millones al año para las empresas e instituciones públicas y privadas. A pesar de esto, no ha habido ningún avance significativo en el área de la depuración que ayude a los desarrolladores durante la fase de desarrollo de software. De hecho, las mismas técnicas de depuración que se utilizaban hace 20 años se siguen utilizando ahora. A lo largo del tiempo, han surgido algunas alternativas, pero todavía queda un largo camino para que estas sean lo suficientemente útiles como para abrirse camino en el proceso de desarrollo de software. Una de ellas es la depuración algorítmica, la cual abstrae la información que el programador debe investigar para depurar el programa, permitiéndole de este modo centrarse en el qué está ocurriendo en vez de en el cómo. Esta abstracción tiene un coste: el nivel de granularidad de los errores que pueden detectarse nos permite como máximo aislar funciones mal implementadas, pero no averiguar qué parte de estas contiene el error. Esta tesis se centra en mejorar la depuración algorítmica en muchos aspectos. Concretamente, los principales objetivos de esta tesis son reducir el tiempo que el usuario necesita para detectar un error de programación así como proporcionar información más detallada de dónde se encuentra el error. Para conseguir estos objetivos, se han desarrollado técnicas para iniciar las sesiones de depuración lo antes posible, reducir el número de preguntas que se le van a realizar al usuario, y aumentar el nivel de granularidad de los errores que la depuración algorítmica puede detectar, permitiendo así seguir buscando el error incluso dentro de las funciones. Como resultado de esta tesis, se han definido tres técnicas completamente nuevas, se ha mejorado una técnica ya existente, y se han definido dos nuevas estrategias de depuración algorítmica que mejoran las previamente existentes. Además de los resultados teóricos, también se ha desarrollado un depurador algorítmico completamente funcional que contiene y respalda todas estas técnicas y estrategias. Este depurador está escrito en Java y depura código Java. La elección de este lenguaje se justifica debido a que es uno de los lenguajes más ampliamente extendidos y usados actualmente. También debido a que contiene una combinación interesante de retos todavía sin resolver para la depuración algorítmica. Para aumentar todavía más su usabilidad, el depurador ha sido posteriormente adaptado como un plugin de Eclipse, de tal manera que pudiese ser usado por un número más amplio de usuarios. Estos dos depuradores están públicamente disponibles para que cualquier persona interesada pueda acceder a ellos y continuar con la investigación si así lo deseara.[CA] Hui en dia, els errors no detectats de programació suposen una despesa de milers de milions a l'any per a les empreses i institucions públiques i privades. Tot i això, no hi ha hagut cap avanç significatiu en l'àrea de la depuració que ajude als desenvolupadors durant la fase de desenvolupament de programari. De fet, les mateixes tècniques de depuració que s'utilitzaven fa 20 anys es continuen utilitzant ara. Al llarg del temps, han sorgit algunes alternatives, però encara queda un llarg camí perquè estes siguen prou útils com per a obrir-se camí en el procés de desenvolupament de programari. Una d'elles és la depuració algorítmica, la qual abstrau la informació que el programador ha d'investigar per a depurar el programa, permetent-li d'esta manera centrar-se en el què està ocorrent en compte de en el com. Esta abstracció té un cost: el nivell de granularitat dels errors que poden detectar-se ens permet com a màxim aïllar funcions mal implementades, però no esbrinar quina part d'estes conté l'error. Esta tesi es centra a millorar la depuració algorítmica en molts aspectes. Concretament, els principals objectius d'esta tesi són reduir el temps que l'usuari necessita per a detectar un error de programació així com proporcionar informació més detallada d'on es troba l'error. Per a aconseguir estos objectius, s'han desenvolupat tècniques per a iniciar les sessions de depuració com més prompte millor, reduir el nombre de preguntes que se li formularan a l'usuari, i augmentar el nivell de granularitat dels errors que la depuració algorítmica pot detectar, permetent així continuar buscant l'error inclús dins de les funcions. Com resultat d'esta tesi, s'han definit tres tècniques completament noves, s'ha millorat una tècnica ja existent, i s'han definit dos noves estratègies de depuració algorítmica que milloren les prèviament existents. A més dels resultats teòrics, també s'ha desenvolupat un depurador algorítmic completament funcional que conté i protegix totes estes tècniques i estratègies. Este depurador està escrit en Java i depura codi Java. L'elecció d'este llenguatge es justifica pel fet que és un dels llenguatges més àmpliament estesos i usats actualment. També pel fet que conté una combinació interessant de reptes encara sense resoldre per a la depuració algorítmica. Per a augmentar encara més la seua usabilitat, el depurador ha sigut posteriorment adaptat com un plugin d'Eclipse, de tal manera que poguera ser usat per un nombre més ampli d'usuaris. Estos dos depuradors estan públicament disponibles perquè qualsevol persona interessada puga accedir a ells i continuar amb la investigació si així ho desitjara.Insa Cabrera, D. (2016). Optimization Techniques for Algorithmic Debugging [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/68506TESISPremios Extraordinarios de tesis doctorale

Automatic assessment of Java code

[EN] Assessment is an integral part of education often used to evaluate students, but also to provide them with feedback. It is essential to ensure that assessment is fair, objective, and equally applied to all students. This holds, for instance, in multiple-choice tests, but, unfortunately, it is not ensured in the assessment of source code, which is still a manual and error-prone task. In this paper, we present JavAssess, a Java library with an API composed of around 200 methods to automatically inspect, test, mark, and correct Java code. It can be used to produce both black-box (based on output comparison) and white-box (based on the internal properties of the code) assessment tools. This means that it allows for marking the code even if it is only partially correct. We describe the library, how to use it, and we provide a complete example to automatically mark and correct a student's code. We also report the use of this system in a real university context to compare manual and automatic assessment in university courses. The study reports the average error in the marks produced by teachers when assessing source code manually, and it shows that the system automatically assesses around 50% of the work. (C) 2018 Elsevier Ltd. All rights reserved.This work has been partially supported by MINECO/AEI/FEDER (EU) under grants TIN2013-44742-C4-1-R and TIN2016-76843-C4-1-R, by the Generalitat Valenciana under grant PROMETEO-II/2015/013 (SmartLogic), and by the Universitat Politecnica de Valencia under grant PIME B18 and EICE HEGEA.Insa Cabrera, D.; Silva, J. (2018). Automatic assessment of Java code. Computer Languages Systems & Structures. 53:59-72. https://doi.org/10.1016/j.cl.2018.01.004S59725

A Generalized Model for Algorithmic Debugging

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-27436-2_16Algorithmic debugging is a semi-automatic debugging technique that is present in practically all mature programming languages. In this paper we claim that the state of the practice in algorithmic debugging is a step forward compared to the state of the theory. In particular, we argue that novel techniques for algorithmic debugging cannot be supported by the standard internal data structures used in this technique, and a generalization of the standard definitions and algorithms is needed. We identify two specific problems of the standard formulation and implementations of algorithmic debugging, and we propose a reformulation to solve both problems. The reformulation has been done in a paradigm-independent manner to make it useful and reusable in different programming languages.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economía y Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under Grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under Grant PROMETEOII/2015/013. David Insa was partially supported by the Spanish Ministerio de Educación under FPU Grant AP2010-4415.Insa Cabrera, D.; Silva Galiana, JF. (2015). A Generalized Model for Algorithmic Debugging. En Logic-Based Program Synthesis and Transformation. Springer. 261-276. https://doi.org/10.1007/978-3-319-27436-2_16261276Eclipse (2003). http://www.eclipse.org/Barbour, T., Naish, L.: Declarative debugging of a logical-functional language. Technical report, University of Melbourne (1994)Braßel, B., Siegel, H.: Debugging lazy functional programs by asking the oracle. In: Chitil, O., Horváth, Z., Zsók, V. (eds.) IFL 2007. LNCS, vol. 5083, pp. 183–200. Springer, Heidelberg (2008)Caballero, R.: A declarative debugger of incorrect answers for constraint functional-logic programs. In: Proceedings of the 2005 ACM-SIGPLAN Workshop on Curry and Functional Logic Programming (WCFLP 2005), pp. 8–13. ACM Press, New York, USA (2005)Caballero, R., Martin-Martin, E., Riesco, A., Tamarit, S.: EDD: A declarative debugger for sequential erlang programs. In: Ábrahám, E., Havelund, K. (eds.) TACAS 2014 (ETAPS). LNCS, vol. 8413, pp. 581–586. Springer, Heidelberg (2014)Caballero, R., Riesco, A., Verdejo, A., Martí-Oliet, N.: Simplifying questions in maude declarative debugger by transforming proof trees. In: Vidal, G. (ed.) LOPSTR 2011. LNCS, vol. 7225, pp. 73–89. Springer, Heidelberg (2012)Cheda, D., Silva, J.: State of the practice in algorithmic debugging. Electron. Notes Theor. Comput. Sci. 246, 55–70 (2009)Davie, T., Chitil, O.: Hat-delta: one right does make a wrong. In: Butterfield, A., (ed.) Proceedings of the 17th International Workshop on Implementation and Application of Functional Languages (IFL 2005), p. 11, September 2005Davie, T., Chitil, O.: Hat-delta: One right does make a wrong. In: Proceedings of the 7th Symposium on Trends in Functional Programming (TFP 2006), April 2006Fritzson, P., Shahmehri, N., Kamkar, M., Gyimóthy, T.: Generalized algorithmic debugging and testing. ACM Lett. Program. Lang. Syst. (LOPLAS) 1(4), 303–322 (1992)González, J., Insa, D., Silva, J.: A new hybrid debugging architecture for eclipse. In: Gupta, G., Peña, R. (eds.) LOPSTR 2013, LNCS 8901. LNCS, vol. 8901, pp. 183–201. Springer, Heidelberg (2014)Hermanns, C., Kuchen, H.: Hybrid debugging of java programs. In: Escalona, M.J., Cordeiro, J., Shishkov, B. (eds.) ICSOFT 2011. CCIS, vol. 303, pp. 91–107. Springer, Heidelberg (2013)Insa, D., Silva, J.: An algorithmic debugger for java. In: Proceedings of the 26th IEEE International Conference on Software Maintenance (ICSM 2010), pp. 1–6 (2010)Insa, D., Silva, J.: Automatic transformation of iterative loops into recursive methods. Inf. Soft. Technol. 58, 95–109 (2015)Insa, D., Silva, J., Riesco, A.: Speeding up algorithmic debugging using balanced execution trees. In: Veanes, M., Viganò, L. (eds.) TAP 2013. LNCS, vol. 7942, pp. 133–151. Springer, Heidelberg (2013)Insa, D., Silva, J., Tomás, C.: Enhancing declarative debugging with loop expansion and tree compression. In: Albert, E. (ed.) LOPSTR 2012. LNCS, vol. 7844, pp. 71–88. Springer, Heidelberg (2013)Lloyd, J.: Declarative error diagnosis. New Gener. Comput. 5(2), 133–154 (1987)Lux, M.: Münster Curry User’s Guide, May 2006. http://danae.uni-muenster.de/lux/curry/user.pdf ,MacLarty, I.D.: Practical Declarative Debugging of Mercury Programs. Ph.D. thesis, University of Melbourne (2005)Naish, L., Dart, P.W., Zobel, J.: The NU-Prolog debugging environment. In: Porto, A. (ed.) Proceedings of the 6th International Conference on Logic Programming (ICLP 1989), pp. 521–536. Lisboa, Portugal (1989)Nilsson, H.: Declarative Debugging for Lazy Functional Languages. Ph.D. thesis, Linköping, Sweden, May 1998Nilsson, H.: How to look busy while being as lazy as ever: the implementation of a lazy functional debugger. J. Funct. Program. 11(6), 629–671 (2001)Nilsson, H., Fritzson, P.: Algorithmic debugging for lazy functional languages. J. Funct. Program. 4(3), 337–370 (1994)Nilsson, H., Sparud, J.: The evaluation dependence tree: an execution record for lazy functional debugging. Technical report, Department of Computer and Information Science, Linköping (1996)Nilsson, H., Sparud, J.: The evaluation dependence tree as a basis for lazy functional debugging. Autom. Softw. Eng. 4(2), 121–150 (1997)Pope, B.: A Declarative Debugger for Haskell. Ph.D. thesis, The University of Melbourne, Australia (2006)Shapiro, E.: Algorithmic Program Debugging. MIT Press, Cambridge (1982)Shapiro, E.Y.: Inductive inference of theories from facts. Technical report RR 192, Yale University (New Haven, CT US) (1981)Silva, J.: A survey on algorithmic debugging strategies. Adv. Eng. Softw. 42(11), 976–991 (2011)Silva, J.: A vocabulary of program slicing-based techniques. ACM Comput. Surv. 44(3), 1–12 (2012)Thompson, B., Naish, L.: A guide to the nu-prolog debugging environment. Technical report, University of Melbourne (1997

Optimal divide and query

Algorithmic debugging is a semi-automatic debugging technique that allows the programmer to precisely identify the location of bugs without the need to inspect the source code. The technique has been successfully adapted to all paradigms and mature implementations have been released for languages such as Haskell, Prolog or Java. During three decades, the algorithm introduced by Shapiro and later improved by Hirunkitti has been thought optimal. In this paper we first show that this algorithm is not optimal, and moreover, in some situations it is unable to find all possible solutions, thus it is incomplete. Then, we present a new version of the algorithm that is proven optimal, and we introduce some equations that allow the algorithm to identify all optimal solutions.This work has been partially supported by the Spanish Ministerio de Ciencia e Innovación under grant TIN2008-06622-C03-02 and by the Generalitat Valenciana under grant PROMETEO/2011/052.Insa Cabrera, D.; Silva Galiana, JF. (2011). Optimal divide and query. En Progress in Artificial Intelligence. Springer Verlag (Germany). 7026:224-238. https://doi.org/10.1007/978-3-642-24769-9_17S2242387026Braßel, B., Huch, F.: The Kiel Curry system KiCS. In: Proc of 17th International Conference on Applications of Declarative Programming and Knowledge Management (INAP 2007) and 21st Workshop on (Constraint) Logic Programming (WLP 2007), pp. 215–223. Technical Report 434, University of Würzburg (2007)Caballero, R.: A Declarative Debugger of Incorrect Answers for Constraint Functional-Logic Programs. In: Proc. of the 2005 ACM SIGPLAN Workshop on Curry and Functional Logic Programming (WCFLP 2005), pp. 8–13. ACM Press, New York (2005)Caballero, R.: Algorithmic Debugging of Java Programs. In: Proc. of the 2006 Workshop on Functional Logic Programming (WFLP 2006). Electronic Notes in Theoretical Computer Science, pp. 63–76 (2006)Caballero, R., Martí-Oliet, N., Riesco, A., Verdejo, A.: A Declarative Debugger for Maude Functional Modules. Electronic Notes in Theoretical Computer Science 238, 63–81 (2009)Davie, T., Chitil, O.: Hat-delta: One Right Does Make a Wrong. In: Seventh Symposium on Trends in Functional Programming, TFP 2006 (April 2006)Fritzson, P., Shahmehri, N., Kamkar, M., Gyimóthy, T.: Generalized Algorithmic Debugging and Testing. LOPLAS 1(4), 303–322 (1992)Hirunkitti, V., Hogger, C.J.: A Generalised Query Minimisation for Program Debugging. In: Adsul, B. (ed.) AADEBUG 1993. LNCS, vol. 749, pp. 153–170. Springer, Heidelberg (1993)Insa, D., Silva, J.: An Algorithmic Debugger for Java. In: Proc. of the 26th IEEE International Conference on Software Maintenance, pp. 1–6 (2010)Insa, D., Silva, J.: Optimal Divide and Query (extended version). Available in the Computing Research Repository (July 2011), http://arxiv.org/abs/1107.0350Lloyd, J.W.: Declarative Error Diagnosis. New Gen. Comput. 5(2), 133–154 (1987)Luo, Y., Chitil, O.: Algorithmic debugging and trusted functions. Technical report 10-07, University of Kent, Computing Laboratory, UK (August 2007)Lux, W.: Münster Curry User’s Guide (release 0.9.10 of May 10, 2006), http://danae.uni-muenster.de/~lux/curry/user.pdfMacLarty, I.: Practical Declarative Debugging of Mercury Programs. PhD thesis, Department of Computer Science and Software Engineering, The University of Melbourne (2005)Naish, L., Dart, P.W., Zobel, J.: The NU-Prolog Debugging Environment. In: Porto, A. (ed.) Proceedings of the Sixth International Conference on Logic Programming, Lisboa, Portugal, pp. 521–536 (June 1989)Nilsson, H.: Declarative Debugging for Lazy Functional Languages. PhD thesis, Linköping, Sweden (May 1998)Pope, B.: A Declarative Debugger for Haskell. PhD thesis, The University of Melbourne, Australia (2006)Shapiro, E.: Algorithmic Program Debugging. MIT Press (1982)Silva, J.: A Comparative Study of Algorithmic Debugging Strategies. In: Puebla, G. (ed.) LOPSTR 2006. LNCS, vol. 4407, pp. 143–159. Springer, Heidelberg (2007)Silva, J.: An Empirical Evaluation of Algorithmic Debugging Strategies. Technical Report DSIC-II/10/09, UPV (2009), http://www.dsic.upv.es/~jsilva/research.htm#tech

Speeding Up Algorithmic Debugging Using Balanced Execution Trees

Algorithmic debugging is a debugging technique that uses a data structure representing all computations performed during the execution of a program. This data structure is the so-called Execution Tree and it strongly influences the performance of the technique. In this work we present a transformation that automatically improves the structure of the execution trees by collapsing and projecting some strategic nodes. This improvement in the structure implies a better behavior and performance of the standard algorithms that traverse it. We prove that the transformation is sound in the sense that all the bugs found after the transformation are real bugs; and if at least one bug is detectable before the transformation, then at least one bug will also be detectable after the transformation. We have implemented the technique and performed several experiments with real applications. The experimental results confirm the usefulness of the technique.This work has been partially supported by the Spanish Ministerio de Ciencia e Innovación under grants TIN2008-06622-C03-02 and TIN2012-39391-004-04, by the Generalitat Valenciana under grant ACOMP/2009/017, and by the Comunidad de Madrid under grant S2009/TIC-1465. David Insa has been partially supported by the Spanish Ministerio de Educación under grant AP2010-4415.Silva, J.; Insa Cabrera, D.; Riesco, A. (2013). Speeding Up Algorithmic Debugging Using Balanced Execution Trees. En Tests and Proofs. Springer. 133-151. https://doi.org/10.1007/978-3-642-38916-0_8S133151Binks, D.: Declarative Debugging in Gödel. PhD thesis, University of Bristol (1995)Caballero, R.: A Declarative Debugger of Incorrect Answers for Constraint Functional-Logic Programs. In: Proc. of the 2005 ACM SIGPLAN Workshop on Curry and Functional Logic Programming, WCFLP 2005, pp. 8–13. ACM Press (2005)Caballero, R., Hermanns, C., Kuchen, H.: Algorithmic debugging of Java programs. In: López-Fraguas, F.J. (ed.) Proc. of the 15th Workshop on Functional and (Constraint) Logic Programming, WFLP 2006, Madrid, Spain. ENTCS, vol. 177, pp. 75–89. Elsevier (2007)Calejo, M.: A Framework for Declarative Prolog Debugging. PhD thesis, New University of Lisbon (1992)Davie, T., Chitil, O.: Hat-delta: One Right Does Make a Wrong. In: Seventh Symposium on Trends in Functional Programming, TFP 2006 (April 2006)Hirunkitti, V., Hogger, C.J.: A Generalised Query Minimisation for Program Debugging. In: Fritzson, P.A. (ed.) AADEBUG 1993. LNCS, vol. 749, pp. 153–170. Springer, Heidelberg (1993)Insa, D., Silva, J.: Scaling up algorithmic debugging with virtual execution trees. In: Alpuente, M. (ed.) LOPSTR 2010. LNCS, vol. 6564, pp. 149–163. Springer, Heidelberg (2011)Insa, D., Silva, J., Riesco, A.: Speeding up algorithmic debugging using balanced execution trees—detailed results. Technical Report 04/13, Departamento de Sistemas Informáticos y Computación (April 2013)Kokai, G., Nilson, J., Niss, C.: GIDTS: A Graphical Programming Environment for Prolog. In: Workshop on Program Analysis For Software Tools and Engineering, PASTE 1999, pp. 95–104. ACM Press (1999)MacLarty, I.: Practical Declarative Debugging of Mercury Programs. PhD thesis, Department of Computer Science and Software Engineering, University of Melbourne (2005)Maeji, M., Kanamori, T.: Top-Down Zooming Diagnosis of Logic Programs. Technical Report TR-290, Japan (1987)Nilsson, H.: Declarative Debugging for Lazy Functional Languages. PhD thesis, Linköping, Sweden (May 1998)Nilsson, H., Fritzson, P.: Algorithmic Debugging for Lazy Functional Languages. Journal of Functional Programming 4(3), 337–370 (1994)Shapiro, E.Y.: Algorithmic Program Debugging. MIT Press (1982)Silva, J.: A Survey on Algorithmic Debugging Strategies. Advances in Engineering Software 42(11), 976–991 (2011

A Generalization and Paradigm-Independent Reformulation of Algorithmic Debugging

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-27436-2_16Algorithmic debugging is a semi-automatic debugging technique that is present in practically all mature programming languages. In this paper we claim that the state of the practice in algorithmic debugging is a step forward compared to the state of the theory. In particular, we argue that novel techniques for algorithmic debugging cannot be supported by the standard internal data structures used in this technique, and a generalization of the standard definitions and algorithms is needed. We identify two specific problems of the standard formulation and implementations of algorithmic debugging, and we propose a reformulation to solve both problems. The reformulation has been done in a paradigm-independent manner to make it useful and reusable in different programming languages.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economía y Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under Grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under Grant PROMETEOII/2015/013. David Insa was partially supported by the Spanish Ministerio de Educación under FPU Grant AP2010-4415.Insa Cabrera, D.; Silva, J. (2015). A Generalization and Paradigm-Independent Reformulation of Algorithmic Debugging. Springer. 261-276. http://hdl.handle.net/10251/71738S261276Eclipse (2003). http://www.eclipse.org/Barbour, T., Naish, L.: Declarative debugging of a logical-functional language. Technical report, University of Melbourne (1994)Braßel, B., Siegel, H.: Debugging lazy functional programs by asking the oracle. In: Chitil, O., Horváth, Z., Zsók, V. (eds.) IFL 2007. LNCS, vol. 5083, pp. 183–200. Springer, Heidelberg (2008)Caballero, R.: A declarative debugger of incorrect answers for constraint functional-logic programs. In: Proceedings of the 2005 ACM-SIGPLAN Workshop on Curry and Functional Logic Programming (WCFLP 2005), pp. 8–13. ACM Press, New York, USA (2005)Caballero, R., Martin-Martin, E., Riesco, A., Tamarit, S.: EDD: A declarative debugger for sequential erlang programs. In: Ábrahám, E., Havelund, K. (eds.) TACAS 2014 (ETAPS). LNCS, vol. 8413, pp. 581–586. Springer, Heidelberg (2014)Caballero, R., Riesco, A., Verdejo, A., Martí-Oliet, N.: Simplifying questions in maude declarative debugger by transforming proof trees. In: Vidal, G. (ed.) LOPSTR 2011. LNCS, vol. 7225, pp. 73–89. Springer, Heidelberg (2012)Cheda, D., Silva, J.: State of the practice in algorithmic debugging. Electron. Notes Theor. Comput. Sci. 246, 55–70 (2009)Davie, T., Chitil, O.: Hat-delta: one right does make a wrong. In: Butterfield, A., (ed.) Proceedings of the 17th International Workshop on Implementation and Application of Functional Languages (IFL 2005), p. 11, September 2005Davie, T., Chitil, O.: Hat-delta: One right does make a wrong. In: Proceedings of the 7th Symposium on Trends in Functional Programming (TFP 2006), April 2006Fritzson, P., Shahmehri, N., Kamkar, M., Gyimóthy, T.: Generalized algorithmic debugging and testing. ACM Lett. Program. Lang. Syst. (LOPLAS) 1(4), 303–322 (1992)González, J., Insa, D., Silva, J.: A new hybrid debugging architecture for eclipse. In: Gupta, G., Peña, R. (eds.) LOPSTR 2013, LNCS 8901. LNCS, vol. 8901, pp. 183–201. Springer, Heidelberg (2014)Hermanns, C., Kuchen, H.: Hybrid debugging of java programs. In: Escalona, M.J., Cordeiro, J., Shishkov, B. (eds.) ICSOFT 2011. CCIS, vol. 303, pp. 91–107. Springer, Heidelberg (2013)Insa, D., Silva, J.: An algorithmic debugger for java. In: Proceedings of the 26th IEEE International Conference on Software Maintenance (ICSM 2010), pp. 1–6 (2010)Insa, D., Silva, J.: Automatic transformation of iterative loops into recursive methods. Inf. Soft. Technol. 58, 95–109 (2015)Insa, D., Silva, J., Riesco, A.: Speeding up algorithmic debugging using balanced execution trees. In: Veanes, M., Viganò, L. (eds.) TAP 2013. LNCS, vol. 7942, pp. 133–151. Springer, Heidelberg (2013)Insa, D., Silva, J., Tomás, C.: Enhancing declarative debugging with loop expansion and tree compression. In: Albert, E. (ed.) LOPSTR 2012. LNCS, vol. 7844, pp. 71–88. Springer, Heidelberg (2013)Lloyd, J.: Declarative error diagnosis. New Gener. Comput. 5(2), 133–154 (1987)Lux, M.: Münster Curry User’s Guide, May 2006. http://danae.uni-muenster.de/lux/curry/user.pdf ,MacLarty, I.D.: Practical Declarative Debugging of Mercury Programs. Ph.D. thesis, University of Melbourne (2005)Naish, L., Dart, P.W., Zobel, J.: The NU-Prolog debugging environment. 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Site-Level Web Template Extraction Based on DOM Analysis

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-41579-6_4One of the main development resources for website engineers are Web templates. Templates allow them to increase productivity by plugin content into already formatted and prepared pagelets. For the final user templates are also useful, because they provide uniformity and a common look and feel for all webpages. However, from the point of view of crawlers and indexers, templates are an important problem, because templates usually contain irrelevant information such as advertisements, menus, and banners. Processing and storing this information leads to a waste of resources (storage space, bandwidth, etc.). It has been measured that templates represent between 40 % and 50 % of data on the Web. Therefore, identifying templates is essential for indexing tasks. In this work we propose a novel method for automatic web template extraction that is based on similarity analysis between the DOM trees of a collection of webpages that are detected using an hyperlink analysis. Our implementation and experiments demonstrate the usefulness of the technique.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Econom´ıa y Competitividad (Secretar´ıa de Estado de Investigaci´on, Desarrollo e Innovaci´on) under grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under grant PROMETEOII/2015/013. David Insa was partially supported by the Spanish Ministerio de Eduaci´on under FPU grant AP2010-4415.Alarte-Aleixandre, J.; Insa Cabrera, D.; Silva, J.; Tamarit Muñoz, S. (2016). Site-Level Web Template Extraction Based on DOM Analysis. Lecture Notes in Computer Science. 9609:36-49. https://doi.org/10.1007/978-3-319-41579-6S3649960

Corrección Semi-Automática de Programas Java

[ES] La evaluación es una parte fundamental de la enseñanza. Permite tanto a los estudiantes como a los profesores medir el grado de éxito obtenido en el proceso de aprendizaje. De hecho, la evaluación no debería usarse solo para puntuar, sino que debe ser parte integral de la educación, y proporcionar a los alumnos retroalimentación inmediata. Obviamente, la evaluación debe ser objetiva y justa, y tratar a todos los alumnos por igual. Esto ocurre, p.e., en exámenes de respuesta múltiple, pero, desafortunadamente, no está asegurado en la evaluación de código programado por alumnos, puesto que su corrección es todavía un proceso manual y propenso a errores e interpretaciones. En este artículo proponemos un sistema semi-automático de evaluación de código que utiliza técnicas de caja negra (basadas en output-comparison) y técnicas de caja blanca (que observan las propiedades internas del código). El método propuesto incluye nuevas ideas y técnicas que le permiten evaluar incluso código que no compila.Proyecto financiado por EU (FEDER) y el Ministerio de Econom´ıa y Competitividad (TIN2013- 44742-C4-1-R), por la Generalitat Valenciana (PROMETEO-II/2015/013), y por la Universitat Polit`ecnica de Val`encia (PIME B16). Los autores agradecen el respaldo de la acci´on COST IC1405.Insa Cabrera, D.; Silva Galiana, JF. (2016). Corrección Semi-Automática de Programas Java. En In-Red 2016. II Congreso nacional de innovación educativa y docencia en red. Editorial Universitat Politècnica de València. https://doi.org/10.4995/INRED2016.2016.4326OC

TeMex: The Web Template Extractor

"© ACM} 2015. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM, In Proceedings of the 24th International Conference on World Wide Web (pp. 155-158), http://dx.doi.org/10.1145/2740908.2742835This paper presents and describes TeMex, a site-level web template extractor. TeMex is fully automatic, and it can work with online webpages without any preprocessing stage (no information about the template or the associated webpages is needed) and, more importantly, it does not need a prede- fined set of webpages to perform the analysis. TeMex only needs a URL. Contrarily to previous approaches, it includes a mechanism to identify webpage candidates that share the same template. This mechanism increases both recall and precision, and it also reduces the amount of webpages loaded and processed. We describe the tool and its internal architecture, and we present the results of its empirical evaluation.This work has been partially supported by the EU (FEDER) and the Spanish Ministerio de Economía y Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under Grant TIN2013-44742-C4-1-R and by the Generalitat Valenciana under Grant PROMETEOII/2015/013. David Insa was partially supported by the Spanish Ministerio de Educación under FPU Grant AP2010-4415. Salvador Tamarit was partially supported by research project POLCA, Programming Large Scale Heterogeneous Infrastructures (610686), funded by the European Union, STREP FP7.Alarte, J.; Insa Cabrera, D.; Silva Galiana, JF.; Tamarit Muñoz, S. (2015). TeMex: The Web Template Extractor. ACM. https://doi.org/10.1145/2740908.2742835SOverlay extension. Available from URL: https://developer.mozilla.org/en-US/Add-ons/Overlay_Extensions, 2005.J. Alarte, D. Insa, J. Silva, and S. Tamarit. Automatic Detection of Webpages that Share the Same Web Template. In M. H. ter Beek and A. Ravara, editors, Proceedings of the 10th International Workshop on Automated Specification and Verification of Web Systems (WWV 14), volume 163 of Electronic Proceedings in Theoretical Computer Science, pages 2--15. Open Publishing Association, July 2014.J. Alarte, D. Insa, J. Silva, and S. Tamarit. A Benchmark Suite for Template Detection and Content Extraction. CoRR, abs/1409.6182, 2014.Z. Bar-Yossef and S. Rajagopalan. Template detection via data mining and its applications. In Proceedings of the 11th International Conference on World Wide Web (WWW'02), pages 580--591, New York, NY, USA, 2002. ACM.M. Baroni, F. Chantree, A. Kilgarriff, and S. Sharoff. Cleaneval: a Competition for Cleaning Web Pages. In Proceedings of the International Conference on Language Resources and Evaluation (LREC'08), pages 638--643. European Language Resources Association, may 2008.D. Gibson, K. Punera, and A. Tomkins. The volume and evolution of web page templates. In A. Ellis and T. Hagino, editors, Proceedings of the 14th International Conference on World Wide Web (WWW'05), pages 830--839. ACM, may 2005.T. Gottron. Evaluating content extraction on HTML documents. In V. Grout, D. Oram, and R. Picking, editors, Proceedings of the 2nd International Conference on Internet Technologies and Applications (ITA'07), pages 123--132. National Assembly for Wales, sep 2007.D. d. C. Reis, P. B. Golgher, A. S. Silva, and A. H. F. Laender. Automatic web news extraction using tree edit distance. In Proceedings of the 13th International Conference on World Wide Web (WWW'04), pages 502--511, New York, NY, USA, 2004. ACM.K. Vieira, A. L. da Costa Carvalho, K. Berlt, E. S. de Moura, A. S. da Silva, and J. Freire. On finding templates on web collections. World Wide Web, 12(2):171--211, 2009.K. Vieira, A. S. da Silva, N. Pinto, E. S. de Moura, J. a. M. B. Cavalcanti, and J. Freire. A fast and robust method for web page template detection and removal. In Proceedings of the 15th ACM International Conference on Information and Knowledge Management (CIKM'06), pages 258--267, New York, NY, USA, 2006. ACM.T. Weninger, W. Henry Hsu, and J. Han. CETR: Content Extraction via Tag Ratios. In M. Rappa, P. Jones, J. Freire, and S. Chakrabarti, editors, Proceedings of the 19th International Conference on World Wide Web (WWW'10), pages 971--980. ACM, apr 2010.L. Yi, B. Liu, and X. Li. Eliminating noisy information in web pages for data mining. In Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data mining (KDD'03), pages 296--305, New York, NY, USA, 2003. ACM

Enhancing Trace Debugging with Algorithmic and Omniscient Debugging

During many years, Print Debugging has been the most used method for debugging. Nowadays, however, industrial languages come with a trace debugger that allows programmers to trace computations step by step using breakpoints and state viewers. Almost all modern programming environments include a trace debugger that allows us to inspect the state of a computation in any given point. Nevertheless, this debugging method has been criticized for being completely manual and time-consuming. Other debugging techniques have appeared to solve some of the problems of Trace Debugging, but they suffer from other problems such as scalability. In this work we present a new hybrid debugging technique. It is based on a combination of Trace Debugging, Algorithmic Debugging and Omniscient Debugging to produce a synergy that exploits the best properties and strong points of each technique. We describe the architecture of our hybrid debugger and our implementation that has been integrated into Eclipse as a plugin.This work has been partially supported by the Spanish Ministerio de Economía y Competitividad (Secretaría de Estado de Investigación, Desarrollo e Innovación) under grant TIN2008-06622-C03-02 and by the Generalitat Valenciana under grant PROMETEO/2011/052. David Insa was partially supported by the Spanish Ministerio de Educación under FPU grant AP2010-4415.González, J.; Insa Cabrera, D.; Silva Galiana, JF. (2013). Enhancing Trace Debugging with Algorithmic and Omniscient Debugging. En Logic-Based Program Synthesis and Transformation. Springer. 183-201. http://hdl.handle.net/10251/72827S18320