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Ashish Tiwari
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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Programming-by-Example (PBE) systems synthesize an intended program in some (relatively constrained) domain-specific language from a small number of input-output examples provided by the user. In this paper, we motivate and define the problem of quantitative PBE (qPBE) that relates to synthesizing an intended program over an underlying (real world) programming language that also minimizes a given quantitative cost function. We present a modular approach for solving qPBE that consists of three phases: intent disambiguation, global search, and local search. On two concrete objectives, namely program performance and size, our qPBE procedure achieves $1.53 X$ and $1.26 X$ improvement respectively over the baseline FlashFill PBE system, averaged over $701$ benchmarks. Our detailed experiments validate the design of our procedure and show the value of combining global and local search for qPBE.
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This volume of the EPTCS contains the proceedings of the 15th international workshop on Qualitative Aspects of Programming Languages and Systems, QAPL 2017, held at April 23, 2017 in Uppsala, Sweden as a satellite event of ETAPS 2017, the 20th European Joint Conferencec on Theory and Practice of Software. The volume contains two invited contributions by Erika Abraham and by Andrea Vandin as well as six technical papers selected by the QAPL 2017 program committee.
This volume contains the proceedings of the Eighth Workshop on Quantitative Aspects of Programming Languages (QAPL 2010), held in Paphos, Cyprus, on March 27-28, 2010. QAPL 2010 is a satellite event of the European Joint Conferences on Theory and Practice of Software (ETAPS 2010). The workshop theme is on quantitative aspects of computation. These aspects are related to the use of physical quantities (storage space, time, bandwidth, etc.) as well as mathematical quantities (e.g. probability and measures for reliability, security and trust), and play an important (sometimes essential) role in characterising the behavior and determining the properties of systems. Such quantities are central to the definition of both the model of systems (architecture, language design, semantics) and the methodologies and tools for the analysis and verification of the systems properties. The aim of this workshop is to discuss the explicit use of quantitative information such as time and probabilities either directly in the model or as a tool for the analysis of systems.
This EPTCS volume contains the proceedings of the 16th Workshop on Quantitative Aspects of Programming Languages and Systems (QAPL 2019) held in Prague, Czech Republic, on Sunday 7 April 2019. QAPL 2019 was a satellite event of the European Joint Conferences on Theory and Practice of Software (ETAPS 2019). QAPL focuses on quantitative aspects of computations, which may refer to the use of physical quantities (time, bandwidth, etc.) as well as mathematical quantities (e.g., probabilities) for the characterisation of the behaviour and for determining the properties of systems. Such quantities play a central role in defining both the model of systems (architecture, language design, semantics) and the methodologies and tools for the analysis and verification of system properties. The aim of the QAPL workshop series is to discuss the explicit use of time and probability and general quantities either directly in the model or as a tool for the analysis or synthesis of systems. The 16th edition of QAPL also focuses on discussing the developments, challenges and results in this area covered by our workshop in its nearly 20-year history.
This volume contains the post-proceedings of the 14th International Workshop on Quantitative Aspects of Programming Languages and Systems (QAPL), held as a satellite workshop of ETAPS 2016 in Eindhoven, The Netherlands, on 2-3 April 2016.
LaTeX is a widely-used document preparation system. Its powerful ability in mathematical equation editing is perhaps the main reason for its popularity in academia. Sometimes, however, even an expert user may spend much time on fixing an erroneous equation. In this paper, we present EqFix, a synthesis-based repairing system for LaTeX equations. It employs a set of fixing rules, and can suggest possible repairs for common errors in LaTeX equations. A domain specific language is proposed for formally expressing the fixing rules. The fixing rules can be automatically synthesized from a set of input-output examples. An extension of relaxer is also introduced to enhance the practicality of EqFix. We evaluate EqFix on real-world examples and find that it can synthesize rules with high generalization ability. Compared with a state-of-the-art string transformation synthesizer, EqFix solved 37% more cases and spent only one third of their synthesis time.
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