The task to this thesis has been to create an application, Katana-databas 1.0, for analysing c-code. The generated output gets stored in a data structure which content in the end of the program run gets written in a textfile which gets used by Katana. It's a tool for reverse engineering, developed by Johan Kraft at Mälardalens institute. Katana-databas has got the following limitations. (1) It can only handle preprocessed files, meaning it doesn't contain any rows beginning with "#". (2) Only complete files can be handled. (3) No references to unknown functions or variables are allowed. (4) A further limitation is that the application can't handle any ADT's. It can only handle primitive types. (5) Finally the application is only written for pure c-code, and thus doesn't handle code written C++. The task has been solved by creating an automatically generated lexer with Flex and Bison rules in Visual Studio. There after a limited parser has been developed which purpose is to process the lexemes which the lexer generates. The underlying causes for the thesis is to replace Understand with Katana-databas. Katana has this far used the database in Understand, but it contains closed source code. What is seeked is open source code, which Katana-databas is based on. / Programmeringsuppgiften till detta arbete har bestått i att skapa en applikation, Katana-databas 1.0, för analys av C-kod. Utflödet som applikationen skapar sparas i en datastruktur vars innehåll i slutet av programkörningen skrivs ut i en textfil som används av Katana. Det är ett verktyg för reverse engineering, utvecklat av Johan Kraft på Mälardalens högskola. Katana-databas har fått följande begränsningar. (1) Den kan bara hantera filer som är preprocessade, dvs. den innehåller inga rader som inleds med ”#”. (2) Endast kompletta filer kan hanteras. (3) Inga referenser till okända funktioner eller variabler är tillåtna. (4) En ytterligare begränsning är att applikationen inte kan hantera ADT:er. Den kan bara hantera primitiva typer. (5) Tillsist är applikationen endast skriven för ren c-kod, och klarar således inte av att hantera kod skriven i C++. Uppgiften har lösts genom att skapa en automatgenererad lexer med Flex och Bisonrules i Visual Studio. Därefter har en limiterad parser utvecklats vars syfte är att bearbeta de lexem som lexern genererar. Det bakomliggande syftet med arbetet är att ersätta Understand med Katana-databas. Katana har hittills använt sig av databasen i Understand, men den består av sluten källkod. Det som eftersträvas är öppen källkod, vilket Katana-databas baseras på.

Over the years, packed malware have started to appear at a more rapid pace.Hackers are modifying the source code of popular packers to create new typesof compressors which can fool the Anti Virus software. Due to the sheer vol-ume of packer variations, creating unpacking scripts based on the packer’ssignature has become a tedious task. In this paper we will analyse genericunpacking techniques and apply them on ten popular compression software.The techniques prove to be successful in nine out of ten cases, providing aneasy and accessible way to unpack the provided samples

This diploma thesis in theoretical part describes methods of Reverse engineering and Rapid prototyping. Each method describes its characteristics, pros and cons and usability. Practical part deals with application of these methods on part of a ledge of Škoda 1000 MB, digitalization of object, creating a new volume model, analyzing its dimensions and geometry using deviation analysis, creating prototype, choosing suitable manufacturing technology and technical-economical aspects.

Inom området maskinteknik finns idag ett stort intresse för Reverse Engineering med hjälp av 3Dskanning. Tekniken utgår ifrån att skapa Computer-Aided-Design (CAD) modeller av reala objekt. Föreliggande projekt utfördes vid institutionen för tillämpad fysik och elektronik vid Umeå universitetet i syfte att utvärdera prestationen av Reverse Engineering av objekt som är utmanade at rita direkt i CAD-program. Fyra olika fysiska objekt valdes för analys: en bult, en tolvkantshylsa, en propeller och ett snäckhjul; det sistnämnda tillhandahållen av företaget Rototilt Group AB. Objekten avbildades med en 3D-skannare som använder sig av metoden strukturerat ljus för att läsa in objektens form och har en noggrannhet på 0,04 mm. De 3Davbildade objekten redigerades sedan och CAD-ritningar skapades. Slutligen skrevs CADmodellerna ut med hjälp av en 3D-skrivare och en toleransanalys med gränsvärdet 0,2 mmutfördes för att jämföra dimensionerna av originalobjekten, de olika digitala modellerna samt de utskrivna objekten. Resultatet visar att Reverse Engineering (med vissa begränsningar) är en bra metod för objekt som är utmanade att modellera i CAD. Med tekniken kan fysiska objektrekonstrueras till CAD-modeller snabbt och med hög noggrannhet. / In the field of mechanical engineering, there is an increasing interest in Reverse Engineering using 3D-scanning. The technology is based on creating Computer-Aided-Design (CAD) models of real objects. The present project was carried out at the Department of Applied Physics and Electronics at Umeå University in order to evaluate the performance of Reverse Engineering of objects that are challenging to draw directly in CAD programs. Four different physical objects were selected for analysis: a bolt, a hex socket, a propeller and a worm wheel; the latter provided by the company Rototilt Group AB. A structured light 3D-scanner with a specified accuracy of 0,04 mm was used to image the objects. The 3D images were then post-processed and transferred to CAD software to create the CAD drawings. Finally, the CAD-models were printed with a 3D printer and a tolerance analysis with a limit of 0,2 mm was performed to compare the dimensions of the original objects, the different digital models and the printed objects. The results show that Reverse Engineering (with some limitations) is a good method for objects that are difficult to model in CAD. The technique is well-suited to reconstruct physical objects into CAD-models quickly and with high accuracy.

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A majority of software development today involves maintenance or evolution of legacy systems. Evolving these legacy systems, while maintaining good software design principles, is a significant challenge. Research has shown the benefits of using software architecture as an abstraction to analyze quality attributes of proposed designs. Unfortunately, for most legacy systems, a documented software architecture does not exist. Developing a good architectural description frequently requires extensive experience on the part of the developer trying to recover the legacy system's architecture. This work first describes a four-phase process that provides a framework within which architectural recovery activities can be automated. These phases consist of: extraction (obtaining a subset of information about the legacy system from a single source), classification (partitioning the information based upon its viewpoint), union (combining all the information in a particular viewpoint into a candidate view), and fusion (cross-checking all candidate views for consistency. The work then concentrates on the major problem facing automated architectural recovery---the concept assignment problem. To overcome this problem, a technique called semantic approximation is presented and validated via experimental results. Semantic approximation uses a combination of text data mining and a mathematical technique called concept analysis to build a lattice of similar concepts between higher-level domain information and low-level code concepts. The experimental data reveals that while semantic approximation does improve results over the more traditional lexical and topological approaches, it does not yet fully solve the concept assignment problem.

Seit geraumer Zeit wird im Maschinenbau (und nicht nur dort) mit Reverse Engineering ein komplexes Vorgehen im Entwicklungsprozess bezeichnet. Bislang getrennt und in Etappen ablaufende Vorgehensweisen werden durch den Rechnereinsatz integriert. Schlüssel dafür sind computergrafische Algorithmen, die es erlauben, aus Scan-, Röntgen- und Messdaten (Punktwolken) Oberflächen zu rekonstruieren. Die als Polygonnetze beschriebenen Oberflächen können für CAD und CAM, für Optimierungsverfahren (FEM) oder für die Qualitätssicherung (Werkstoffprüfung) genutzt werden. [... aus der Einleitung]

Reverse engineering, defined as extracting information about a product from the product itself, is a common industry practice for gaining insight into innovative products. Both the original designer and those reverse engineering the original design can benefit from estimating the time and barrier to reverse engineer a product. This thesis presents a set of metrics and parameters that can be used to calculate the barrier to reverse engineer any product as well as the time required to do so. To the original designer, these numerical representations of the barrier and time can be used to strategically identify and improve product characteristics so as to increase the difficulty and time to reverse engineer them. One method for increasing the time and barrier to reverse engineer a product – presented in this thesis – is to treat material microstructures (crystallographic grain size, orientation, and distribution) as continuous design variables that can be manipulated to identify unusual material properties and to design devices with unexpected mechanical performance. A practical approach, carefully tied to proven manufacturing strategies, is used to tailor material microstructures by strategically orienting and laminating thin anisotropic metallic sheets. This approach, coupled with numerical optimization, manipulates material microstructures to obtain desired material properties at designer-specified locations (heterogeneously) or across the entire part (homogeneously). As the metrics and parameters characterizing the reverse engineering time and barrier are also quantitative in nature, they can also be used in conjunction with numerical optimization techniques, thereby enabling products to be developed with a maximum reverse engineering barrier and time – at a minimum development cost. On the other hand, these quantitative measures enable competitors who reverse engineer original designs to focus their efforts on products that will result in the greatest return on investment. While many products were analyzed in an empirical study demonstrating that the characterization of the time to reverse engineer a product has an average error of 12.2%, we present the results of three different products. Two additional examples are also presented showing how microstructure manipulation leads to product hardware with unexpected mechanical performance effectively increasing reverse engineering time and barrier.

The future of companies that are founded on the development of new and innovative products is threatened when competitors reverse engineer and imitate the products. If the original developers could predict how long it would take a competitor to reverse engineer a product, it may be possible for them to delay, if not prevent, that competitor's entry into the market. Metrics and measures have been developed that can estimate the time it would take an individual to reverse engineer a product. The main purpose of these metrics and measures is to help designers determine how quickly a competitor could reverse engineer a product and develop and market a competing product. A critical parameter of these metrics is the flow rate of information (how quickly information can be extracted from a product), which is a parameter unique to each individual. This thesis seeks to establish a method for creating probability distributions that could be used to select a reasonable flow rate for an individual, by using data collected on the initial flow rate of multiple individuals.

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