An important issue in software evolution is the time and effort needed to understand existing applications. Reverse engineering software to recover behavioural models is difficult and is complicated due to the lack of a standardized way of extracting and visualizing knowledge. In this thesis, we study a technique for automatically extracting static and dynamic data from software, filtering and analysing the data, and visualizing the behavioural model of a selected feature of a software application. We also investigate the usefulness of the generated diagrams as documentation for the software. We present a literature review of studies that have used static and dynamic data analysis for software comprehension. A set of criteria is created, and each approach, including this thesis’ technique, is compared using those criteria. We propose an approach to simplify lengthy traces by filtering out software components that are too low level to give a high-level picture of the selected feature. We use static information to identify and remove small and simple (or uncomplicated) software components from the trace. We define a utility method as any element of a program designed for the convenience of the designer and implementer and intended to be accessed from multiple places within a certain scope of the program. Utilityhood is defined as the extent to which a particular method can be considered a utility. Utilityhood is calculated using different combinations of selected dynamic and static variables. Methods with high utilityhood values are detected and removed iteratively. By eliminating utilities, we are left with a much smaller trace which is then visualized using the Use Case Map (UCM) notation. UCM is a scenario language used to specify and explain behaviour of complex systems. By doing so, we can identify the algorithm that generates a UCM closest to the mental model of the designers. Although when analysing our results we did not identify an algorithm that was best in all cases, there is a trend in that three of the best four algorithms (out of a total of eight algorithms investigated) used method complexity and method lines of code in their parameters. We also validated the algorithm results by doing a comparison with a list of methods given to us by the creators of the software and doing precision and recall calculations. Seven out of the eight participants agreed or strongly agreed that using UCM diagrams to visualize reduced traces is valid approach, with none who disagreed.

An important issue in software evolution is the time and effort needed to understand existing applications. Reverse engineering software to recover behavioural models is difficult and is complicated due to the lack of a standardized way of extracting and visualizing knowledge. In this thesis, we study a technique for automatically extracting static and dynamic data from software, filtering and analysing the data, and visualizing the behavioural model of a selected feature of a software application. We also investigate the usefulness of the generated diagrams as documentation for the software. We present a literature review of studies that have used static and dynamic data analysis for software comprehension. A set of criteria is created, and each approach, including this thesis’ technique, is compared using those criteria. We propose an approach to simplify lengthy traces by filtering out software components that are too low level to give a high-level picture of the selected feature. We use static information to identify and remove small and simple (or uncomplicated) software components from the trace. We define a utility method as any element of a program designed for the convenience of the designer and implementer and intended to be accessed from multiple places within a certain scope of the program. Utilityhood is defined as the extent to which a particular method can be considered a utility. Utilityhood is calculated using different combinations of selected dynamic and static variables. Methods with high utilityhood values are detected and removed iteratively. By eliminating utilities, we are left with a much smaller trace which is then visualized using the Use Case Map (UCM) notation. UCM is a scenario language used to specify and explain behaviour of complex systems. By doing so, we can identify the algorithm that generates a UCM closest to the mental model of the designers. Although when analysing our results we did not identify an algorithm that was best in all cases, there is a trend in that three of the best four algorithms (out of a total of eight algorithms investigated) used method complexity and method lines of code in their parameters. We also validated the algorithm results by doing a comparison with a list of methods given to us by the creators of the software and doing precision and recall calculations. Seven out of the eight participants agreed or strongly agreed that using UCM diagrams to visualize reduced traces is valid approach, with none who disagreed.

Multi-threading is commonly applied in modern computer programs, bringing many conveniences but also causing concurrency issues. Among the various error debugging tools, Java Pathfinder (JPF) can detect latent errors of multithreaded Java programs through model checking. However, the text-based format of the output trace is hard to read, and previous attempts in visualizing JPF traces show limitations. For long-term development, popular trace analytic platform such as Trace Compass (TC) is extended to adapt to JPF traces. In this thesis, the development of JPF and TC makes it possible to analyze JPF traces on TC with a user interface including visual diagrams. The development solves the conceptual differences between the tools and successfully visualize important trace data. The implementation can help provide a generic approach for analyzing JPF traces with visualization. / Multitrådning används ofta i moderna datorprogram, vilket har många fördelar men kan också orsaka samtidighetsproblem. Bland olika felsökningsverktyg kan Java Pathfinder (JPF) upptäcka latenta fel hos multitrådade Javaprogram genom modellkontroll. Spårningsinformationen i form av text har låg läsbarhet, och tidigare försök att visualsera JPF-spår har visat begränsningar. För långsiktig utveckling har populära spårningsanalysplattformar som Trace Compass (TC) utvidgats för att anpassas till JPF-spår. I examensprojektet gör utvecklingen av JPF och TC det möjligt att analysera JPF-spår på TC med ett användargränssnitt baserat på visuella diagram. Utvecklingen löser den konceptuella skillnaden mellan verktygen och visualiserar spårdata på ett framgångsrikt sätt. Implementeringen bidrar med ett generiskt tillvägagångssätt för att analysera JPF spår med hjälp av visualisering.

The Radio Access Network (RAN) plays a vital role in enabling mobile network connectivity using radio waves. Gaining a comprehensive understanding of RAN applications is crucial, and trace analysis provides valuable insights into their operations. Modern RAN applications can be deployed on different platforms and this can lead to the generation of different trace formats, which complicates the analysis process. Trace analysis and visualization tools, such as Trace Compass, can be used to ease the process, but for each new trace format the user often needs to create new code and visualizations. This is needed also when different trace formats generated by the same application contain similar information. To overcome this limitation, this thesis introduces an innovative approach to generalize the interpretation of traces, enabling to reuse existing analysis and visualization independently of the trace format. Moreover, a Domain Specific Language (DSL) is introduced to simplify the trace analysis procedure. The proposed thesis contributes to a generic approach for analyzing different trace formats, thereby facilitating the analysis of RAN applications deployed across diverse platforms. / Radio Access Network (RAN) spelar en viktig roll när det gäller att möjliggöra anslutning till mobilnät med hjälp av radiovågor. Att få en omfattande förståelse för RAN-applikationer är avgörande, och trace-analys ger värdefulla insikter i deras verksamhet. Moderna RAN-applikationer kan driftsättas på olika plattformar, vilket kan leda till att olika trace-format genereras, vilket komplicerar analysprocessen. Verktyg för trace-analys och visualisering, som Trace Compass, kan användas för att underlätta processen, men för varje nytt trace-format måste användaren ofta skapa ny kod och nya visualiseringar. Detta behövs även när olika traceformat som genereras av samma applikation innehåller liknande information. För att övervinna denna begränsning introducerar denna avhandling en innovativ metod för att generalisera tolkningen av trace-data, vilket gör det möjligt att återanvända befintlig analys och visualisering oberoende av traceformatet. Dessutom introduceras ett domänspecifikt språk (DSL) för att förenkla trace-analysförfarandet. Den föreslagna avhandlingen bidrar till en generisk metod för analys av olika trace-format, vilket underlättar analysen av RANapplikationer somanvänds på olika plattformar.