Abstract
Algorithmic 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.
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Notes
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- 2.
In the ET, nodes represent computations. Hence, depending on the underlying paradigm, they can represent methods, functions, procedures, clauses, etc. Our discussions in this paper can be applied to both the imperative and the declarative paradigms, but, for the sake of concreteness, we will focuss the discussion on the imperative paradigm and our examples on Java.
- 3.
Note the careful use of the word “statement" to refer to either imperative instructions, declarative expressions, etc.
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Acknowledgements
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. The authors thank the anonymous referees of LOPSTR for their constructive feedback that has contributed to improve this work. They also thank Ehud Shapiro for providing historical information about algorithmic debugging.
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Insa, D., Silva, J. (2015). A Generalized Model for Algorithmic Debugging. In: Falaschi, M. (eds) Logic-Based Program Synthesis and Transformation. LOPSTR 2015. Lecture Notes in Computer Science(), vol 9527. Springer, Cham. https://doi.org/10.1007/978-3-319-27436-2_16
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