Abstract
Quality assessment of open source software is becoming an important and active research area. One of the reasons for this recent interest is the consequence of Internet popularity. Nowadays, programming also involves looking for the large set of open source libraries and tools that may be reused when developing our software applications. In order to reuse such open source software artifacts, programmers not only need the guarantee that the reused artifact is certified, but also that independently developed artifacts can be easily combined into a coherent piece of software. In this paper we describe a domain specific language that allows programmers to describe in an abstract level how software artifacts can be combined into powerful software certification processes. This domain specific language is the building block of a web-based, open-source software certification portal. This paper introduces the embedding of such domain specific language as combinator library written in the Haskell programming language. The semantics of this language is expressed via attribute grammars that are embedded in Haskell, which provide a modular and incremental setting to define the combination of software artifacts.

Abstract
This paper presents a web portal for the certification of open source software. The portal aims at helping programmers in the internet age, when there are (too) many open source reusable libraries and tools available. Our portal offers programmers a web-based and easy setting to analyze and certify open source software, which is a crucial step to help programmers choosing among many available alternatives, and to get some guarantees before using one piece of software. The paper presents our first prototype of such web portal. It also describes in detail a domain specific language that allows programmers to describe with a high degree of abstraction specific open source software certifications. The design and implementation of this language is the core of the web portal. © Springer-Verlag Berlin Heidelberg 2014.

Abstract
Although spreadsheets can be seen as a flexible programming environment, they lack some of the concepts of regular programming languages, such as structured data types. This can lead the user to edit the spreadsheet in a wrong way and perhaps cause corrupt or redundant data. We devised a method for extraction of a relational model from a spreadsheet and the subsequent embedding of the model back into the spreadsheet to create a model-based spreadsheet programming environment. The extraction algorithm is specific for spreadsheets since it considers particularities such as layout and column arrangement. The extracted model is used to generate formulas and visual elements that are then embedded in the spreadsheet helping the user to edit data in a correct way. We present preliminary experimental results from applying our approach to a sample of spreadsheets from the EUSES Spreadsheet Corpus. © 2012 Springer-Verlag.

Abstract
Spreadsheets are widely recognized as popular programming systems with a huge number of spreadsheets being created every day. Also, spreadsheets are often used in the decision processes of profit-oriented companies. While this illustrates their practical importance, studies have shown that up to 90% of real-world spreadsheets contain errors. © 2012 IEEE.

Abstract
Spreadsheets are among the most popular programming languages in the world. Unfortunately, spreadsheet systems were not tailored from scratch with modern programming language features that guarantee, as much as possible, program correctness. As a consequence, spreadsheets are populated with unacceptable amounts of errors. In other programming language settings, model-based approaches have been proposed to increase productivity and program effectiveness. Within spreadsheets, this approach has also been followed, namely by ClassSheets. In this paper, we propose an extension to ClassSheets to allow the specification of spreadsheets that can be viewed as relational databases. Moreover, we present a transformation from ClassSheet models to UML class diagrams enriched with OCL constraints. This brings to the spreadsheet realm the entire paraphernalia of model validation techniques that are available for UML. © 2012 ACM.

Abstract
This tool demo paper presents SmellSheet Detective: a tool for automatically detecting bad smells in spreadsheets. We have defined a catalog of bad smells in spreadsheet data which was fully implemented in a reusable library for the manipulation of spreadsheets. This library is the building block of the SmellSheet Detective tool, that has been used to detect smells in large, real-world spreadsheets within the EUSES corpus, in order to validate and evolve our bad smells catalog.