Commercial software development is a complex task that requires a thorough understanding of the architecture of the software system. We analyze the Windows Server 2003 operating system in order to assess the relationship between its software dependences, churn metrics and post-release failures. Our analysis indicates the ability of software dependences and churn metrics to be efficient predictors of post-release failures. Further, we investigate the relationship between the software dependences and churn metrics and their ability to assess failure-proneness probabilities at statistically significant levels.

Verification and validation techniques often generate various forms of software development artifacts. Change records created from verification and validation efforts show how files in the system tend to change together in response to fixes for identified faults and failures. We propose a methodology for determining the impact of a new system modification by analyzing software change records through singular value decomposition. This methodology generates clusters of files that historically tend to change together to address faults and failures found in the code base. We performed a post hoc case study using this technique on five open source software systems. We determined that our technique was effective in identifying impacted files in a system from an introduced change when the developers tended to make small, targeted updates to the source system regularly. We further compared our technique against two other impact analysis techniques (PathImpact and CoverageImpact) and found that our technique provided comparable results, while also identifying non-source files that could be impacted by the change. 1.

To support debugging, maintenance, verification and validation (V&V) and/or Independent V&V (IV&V), it is necessary to understand the relationship between defect reports and their related artifacts. For example, one cannot correct a code-related defect report wihtout being able to find the code that is affected. Information Retrieval (IR) techniques have been used effectively to trace textual artifacts to each other. This has generally been applied to the problem of dynamically generating a trace between artifacts in the software document hierarchy „after the fact “ (after development has proceeded to at least the next lifecycle phase). The same techniques can also be used to trace textual artifacts of the software engineering lifecycle to defect reports. We have applied the term frequency- inverse document frequency (TF-IDF) technique with relevance feedback, as implemented in our tool RETRO (REquirements TRacing On-target), to the problem of tracing textual requirement elements to related textual defect reports. We have evaluated the technique using a dataset for a NASA scientific instrument. We found that recall of over 85 % and

Many of todays systems evolve through a series of releases that add new functionality and features, in addition to corrective maintenance. As the systems evolve over time it is necessary to keep track of and manage their problematic components. Our focus is to track system evolution and to react before the systems become difficult to manage. We apply a method based on a collection of statistical methods to perform the tracking. The method is applied in a case study covering four releases of a system consisting of 130 components. In each release components are classied as fault-prone if the number of defect reports written against them are above a certain threshold. The outcome from the study indicates stabilising principal components over the releases and classification trees with lower thresholds in the decision nodes. Also, the variables used in the classification trees decision nodes are related to changes in the same files. The discriminant functions used more variables than the classification trees and were more difficult to interpret. Box plots highlight the findings from the other analyses. The results show that PCA together with classification trees are good descriptors of software evolution due to their ability to visualise.

To support debugging, maintenance, verification and validation (V&V) and/or Independent V&V (IV&V), it is necessary to understand the relationship between defect reports and their related artifacts. For example, one cannot correct a code-related defect report wihtout being able to find the code that is affected. Information Retrieval (IR) techniques have been used effectively to trace textual artifacts to each other. This has generally been applied to the problem of dynamically generating a trace between artifacts in the software document hierarchy „after the fact “ (after development has proceeded to at least the next lifecycle phase). The same techniques can also be used to trace textual artifacts of the software engineering lifecycle to defect reports. We have applied the term frequency- inverse document frequency (TF-IDF) technique with relevance feedback, as implemented in our tool RETRO (REquirements TRacing On-target), to the problem of tracing textual requirement elements to related textual defect reports. We have evaluated the technique using a dataset for a NASA scientific instrument. We found that recall of over 85 % and

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