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Framework based software tends to get bloated by accumulating optional features (or concerns) just-in-case they are needed. The good news is that such feature bloat need not always cause runtime execution bloat. The bad news is that often enough, only a few statements from an optional concern may cause execution bloat that may result in as much as 50% runtime overhead.We present a novel technique to analyze the connection between optional concerns and the potential sources of execution bloat induced by them. Our analysis automatically answers questions such as (1) whether a given set of optional concerns could lead to execution bloat and (2) which particular statements are the likely sources of bloat when those concerns are not required. The technique combines coarse grain concern input from an external source with a fine-grained static analysis. Our experimental evaluation highlights the effectiveness of such concern augmented program analysis in execution bloat assessment of ten programs.

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Managing a combined store consisting of database data and file data in a robust and consistent manner is a challenge for database systems and content management systems. In such a hybrid system, images, videos, engineering drawings, etc. are stored as files on a file server while meta-data referencing/indexing such files is created and stored in a relational database to take advantage of efficient search. In this paper we describe solutions for two potentially problematic aspects of such a data management system: backup/recovery and data consistency. We present algorithms for performing backup and recovery of the DBMS data in a coordinated fashion with the files on the file servers. Our algorithms for coordinated backup and recovery have been implemented in the IBM DB2/DataLinks product [1]. We also propose an efficient solution to the problem of maintaining consistency between the content of a file and the associated metadata stored in the DBMS from a reader's point of view without holding long duration locks on meta-data tables. In the model, an object is directly accessed and edited in-place through normal file system APIs using a reference obtained via an SQL Query on the database. To relate file modifications to meta-data updates, the user issues an update through the DBMS, and commits both file and meta-data updates together.

In large flexible software systems, bloat occurs in many forms, causing excess resource utilization and resource bottlenecks. This results in lost throughput and wasted joules. However, mitigating bloat is not easy; efforts are best applied where savings would be substantial. To aid this we develop an analytical model establishing the relation between bottleneck in resources, bloat, performance and power.Analyses with the model places into perspective results from the first experimental study of the powerperformance implications of bloat. In the experiments we find that while bloat reduction can provide as much as 40% energy savings, the degree of impact depends on hardware and software characteristics. We confirm predictions from our model with selected results from our experimental study.Our findings show that a software-only view is inadequate when assessing the effects of bloat. The impact of bloat on physical resource usage and power should be understood for a full systems perspective to properly deploy bloat reduction solutions and reap their power-performance benefits.