Search

Based on the concept of explanation sheets, we present an approach to make spreadsheets easier to understand and thus easier to use and maintain. We identify the notion of explanation soundness and show that explanation sheets which conform to simple rules of formula coverage provide sound explanations. We also present a practical evaluation of explanation sheets based on samples drawn from widely used spreadsheet corpora and based on a small user study.In addition to supporting spreadsheet understanding and maintenance, our work on explanation sheets has also uncovered several general principles of explanation languages that can help guide the design of explanations for other programming and domain-specific languages., This work is partially supported by the National Science Foundation under the grant CCF-1717300. Work financed by European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization COMPETE 2020 Programme and by National Funds through the Portuguese funding agency FCT project POCI-01-0145-FEDER-016718 and NOVA LINCS UID/CEC/04516/2013, and by FLAD project 233/2014.

In literature some approaches have been proposed to partition software systems into meaningful subsystems exploiting the lexical information provided by programmers into the source code. However these techniques usually do not consider the programming language constructs in which the lexicon appears (e.g.: comments, class names, method names) even if it is a common experience that programmers place di erent care in choosing terms for different constructs. In this paper we present a novel lexical-based software clustering technique which exploits the contribution of terms placed in six different parts of the source code (i.e. zones), namely Class Names, Attribute Names, Method Names, Parameter Names, Comments and Source Code Statements. These zones convey information with different levels of relevance, and so their contribution should be di erently weighted according to the specificities of the analyzed software system. To this aim we dene a probabilistic model of the data whose parameters are estimated automatically by the Expectation-Maximization algorithm. These weights are then exploited to generate the software partitions with two distinct clustering algorithms properly customized to make them more suitable for the specic domain. The overall technique has been assessed in a case study conducted on a dataset of 16 open source software systems whose results are presented in the paper. In particular, we experimentally observed that the use of both the dened zones and the Expectation-Maximization algorithm improves the overall quality of results.

Formal Concept Analysis is a technique to identify possible groups sharing common propertiesof the target objects. With Formal Concept Analysis, we present a grouping method for C program functions by “use of struct types” and apply the method to the middle-size open-source software, such as Gzip and Bison. As an example, by combining function call graphs and groupings, we present program overviews. Program overviews are used as a map for program exploration in software understanding tools. We develop a generator of the program overviews from C programs and demonstrate that our method can be efficiently applied to software understanding.

In this essay, I argue that linguistic abstraction should be used systematically as a tool to capture our emerging understanding of domains of computation. Moreover, to enable that systematic application, we need to capture our understanding of the domain of linguistic abstraction itself in higher-level meta languages. The argument is illustrated with examples from the SDF, Stratego, Spoofax, and WebDSL projects in which I explore these ideas.

Preprint submitted to "Science of Computer Programming", Elsevier, http://dx.doi.org/10.1016/j.scico.2013.12.001 In this essay, I argue that linguistic abstraction should be used systematically as a tool to capture our emerging understanding of domains of computation. Moreover, to enable that systematic application, we need to capture our understanding of the domain of linguistic abstraction itself in higher-level meta languages. The argument is illustrated with examples from the SDF, Stratego, Spoofax, and WebDSL projects in which I explore these ideas.

Preprint submitted to "Science of Computer Programming", Elsevier, http://dx.doi.org/10.1016/j.scico.2013.12.001 In this essay, I argue that linguistic abstraction should be used systematically as a tool to capture our emerging understanding of domains of computation. Moreover, to enable that systematic application, we need to capture our understanding of the domain of linguistic abstraction itself in higher-level meta languages. The argument is illustrated with examples from the SDF, Stratego, Spoofax, and WebDSL projects in which I explore these ideas.

Los sistemas legados son sistemas que han tenido una larga evolución, más larga que el tiempo típico de los desarrolladores en una empresa. Estos sistemas son esenciales para el negocio y contienen grandes cantidades de información sobre los procesos de negocio. Sin embargo, los cambios continuos en el dominio de algunos sistemas, la falta de procesos estrictos de mantenimiento, y los cambios de desarrolladores conducen de manera inevitable a pérdidas graduales de conocimiento del sistema y su dominio, lo cual es corroborado por el hecho de que la documentación externa es rara vez actualizada, de acuerdo con el código y otros artefactos. SIFI, un sistema de información legado desarrollado y mantenido por la empresa de desarrollo de software IT Consultores S.A.S, presenta tales problemas de mantenimiento: alto acoplamiento, decaimiento de la arquitectura, sin documentación formal y con pérdida de conocimiento acerca de su dominio e implementación, lo cual hace que su evolución sea difícil. En esta tesis se construyó una herramienta de ingeniería inversa para sistemas de información en Oracle Forms y PL/SQL, con el objetivo de apoyar el proceso de mantenimiento de SIFI. La herramienta es capaz de extraer y visualizar información estructural y comporta mental del sistema, e implementa la técnica que hemos propuesto para extraer automáticamente reglas de negocio estructurales de bases de datos legados. A través de una encuesta se evaluó la efectividad de la herramienta considerando el mantenimiento y entendimiento de SIFI. Los resultados muestran que la herramienta es muy útil porque mejora la productividad de los desarrolladores en completar sus tareas y ahora el proceso de mantenimiento de SIFI es menos complicado. Asimismo, la técnica de extracción de reglas de negocio fue evaluada a través de un estudio con 4 colaboradores de ITC. Los resultados muestran que la técnica es práctica, habiendo posibilidad de mejora, y será usada como base para recuperar información adicional. Abstract. Legacy information systems are systems that have had a long evolution, longer than the typical turnaround time of the developers in the company. They are essential to the business and encode large amounts of essential information related to the business processes. However, continuous changes in the domain of some systems, the lack of strict maintenance processes, and the turnaround of developers inevitably leads to gradual loss of knowledge about the system and its domain, most often corroborated by the fact that external documentation is rarely updated in synch with the code and other artifacts. SIFI, financial legacy information system owned by the software development company IT Consultores S.A.S., presents such a maintenance issues: high coupling, architecture decay, no formal documentation and loss of domain and implementation knowledge, making its evolution very difficult. Within this thesis, a reverse engineering tool for Oracle Forms and PL/SQL information systems was built, aiming at supporting the maintenance process on SIFI. The tool is able to extract and visualize structural and behavioral information about the system, and implements the approach we proposed for automatically extracting structural business rules from legacy databases. The effectiveness of the tool was assessed under the understanding and maintenance of SIFI, through a survey. The results show that tool is very useful, as it improves the productivity of developers to complete their tasks and the maintenance process of SIFI is now easier for them. In addition, the implemented business rule extraction approach was assessed though a study with 4 ITC employees. The results show that the recovery technique is practical, while there is room for improvement, and it will be used as basis for the recovery of additional knowledge. Maestría

Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis. While many such approaches have been proposed in the literature, their empirical evaluation is often missing or inconclusive, and their added values to existing solutions are seldomly quantified. This dissertation aims to characterize, and extend upon, the existing work on program comprehension through dynamic analysis. A strong emphasis in our research is put on empirical evaluation. To structure the current state of the art and to identify research opportunities, we first conduct a systematic survey of all publications on this topic in the past decades. We then propose both a traditional and a more advanced visualization technique, experiment with the necessary abstraction techniques, and provide tool implementations. Our approaches are validated through extensive case studies and a controlled experiment. Finally, we conclude with a set of recommendations for future directions.

Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis. While many such approaches have been proposed in the literature, their empirical evaluation is often missing or inconclusive, and their added values to existing solutions are seldomly quantified. This dissertation aims to characterize, and extend upon, the existing work on program comprehension through dynamic analysis. A strong emphasis in our research is put on empirical evaluation. To structure the current state of the art and to identify research opportunities, we first conduct a systematic survey of all publications on this topic in the past decades. We then propose both a traditional and a more advanced visualization technique, experiment with the necessary abstraction techniques, and provide tool implementations. Our approaches are validated through extensive case studies and a controlled experiment. Finally, we conclude with a set of recommendations for future directions.

A theoretical model of how an expert programmer goes about understanding a piece of software is presented. This understanding plays an especially critical role in software maintenance tasks. The model is based on three cognitive processes: CHUNKING, SLICING and HYPOTHESIS GENERATION and VERIFICATION. These processes are used in conjunction with a programmer's knowledge base and categories of information critical to program understanding are identified. The model also takes advantage of certain characteristics of an associative memory to describe, using a semantic net representation, the mechanisms behind these processes and the organization of memory resulting from their use. The benefits of documentation and the use of commenting and mnemonics are described in terms of the model and may be useful as a guide for incorporating these into the code. http://archive.org/details/howcognitiveproc1094521365 Lieutenant Commander, United States Navy Approved for public release; distribution is unlimited.