Software engineers will possibly never see the perfect source code in their lifetime, but they are seeing much better analysis tools for finding defects in software. The approaches used in static code analysis emerged from simple code crawling to usage of statistical and probabilistic frameworks. This work presents a new technique that incorporates machine learning and information visualization into static code analysis. The technique learns patterns in a program’s source code using a normalized compression distance and applies them to classify code fragments into faulty or correct. Since the classification frequently is not perfect, the training process plays an essential role. A visualization element is used in the hope that it lets the user better understand the inner state of the classifier making the learning process transparent. An experimental evaluation is carried out in order to prove the efficacy of an implementation of the technique, the Code Distance Visualizer. The outcome of the evaluation indicates that the proposed technique is reasonably effective in learning to differentiate between faulty and correct code fragments, and the visualization element enables the user to discern when the tool is correct in its output and when it is not, and to take corrective action (further training or retraining) interactively, until the desired level of performance is reached.

A major problem during development and maintenance of software is lack of quality documentation. Many programers have problems identifying which infor- mation is relevant for someone with no knowledge of the system and therefore write incomplete documentation. One way to get around these problems would be to use a tool that extracts information from both comments and the actual source code and presents the structure of the program visually. This thesis aims to design an XML-driven system for the extraction and pre- sentation of meta information about source code to that purpose. Relevant meta information in this case is, for example, which entities (classes, methods, variables, etc.) exist in the program and how they interact with each other. The result is a prototype implemented to manage two company developed lan- guages. The prototype demonstrates how the system can be implemented and show that the approach is scalable. The prototype is not suitable for commercial use due to its abstraction level, but with the help of qualified XML databases there are great possibilities to build a usable system using the same techniques in the future. / Ett stort problem under utvecklingen och underhållet av mjukvara är bristande dokumentation av källkoden. Många programmerare har svårt att identifiera vilken information som är viktig för någon som inte är insatt i systemet och skriver därför bristfällig dokumentation. Ett sätt att komma runt dessa problem skulle vara att använda verktyg som extraherar information från såväl kommentarer som faktisk källkod och presenterar programmets struktur påett tydligt och visuellt sätt. Det här examensarbetet ämnar att designa ett system för XML-driven extra- hering och presentation av metainformation om källkoden med just det syftet. Metainformationen som avses här är exempelvis vilka entiteter (klasser, metoder, variabler, mm.) som finns i källkoden samt hur dessa interagerar med varandra. Resultatet är en prototyp implementerad för att hantera tvåföretagsutvecklade språk. Prototypen demonstrerar hur systemet kan implementeras och visar att me- toden är skalbar. Prototypen är abstraktionsmässigt inte lämplig för kommersiellt bruk men med hjälp av kvalificerade XML-databaser finns det stora möjligheter att i framtiden bygga ett praktiskt användbart system baserat på samma tekniker.

Nous proposons une approche qui génère des scénarios de visualisation à partir des descriptions de tâches d'analyse de code. La dérivation de scénario est considérée comme un processus d'optimisation. Dans ce contexte, nous évaluons différentes possibilités d'utilisation d'un outil de visualisation donnée pour effectuer la tâche d'analyse, et sélectionnons le scénario qui nécessite le moins d'effort d'analyste. Notre approche a été appliquée avec succès à diverses tâches d'analyse telles que la détection des défauts de conception. / We propose an approach that derives interactive visualization scenarios from descriptions of code analysis tasks. The scenario derivation is treated as an optimization process. In this context, we evaluate different possibilities of using a given visualization tool to perform the analysis task, and select the scenario that requires the least effort from the analyst. Our approach was applied successfully to various analysis tasks such as design defect detection and feature location.