An Exploration of the challenges associated with software logging in large systems

Over the past few years, logging has evolved from from simple printf statements to more complex and widely used logging libraries. Today logging information is used to support various development activities such as fixing bugs, analyzing the results of load tests, monitoring performance and transferring knowledge. Recent research has examined how to improve logging practices by informing developers what to log and where to log. Furthermore, the strong dependence on logging has led to the development of logging libraries that have reduced the intricacies of logging, which has resulted in an abundance of log information. Two recent challenges have emerged as modern software systems start to treat logging as a core aspect of their software. In particular, 1) infrastructural challenges have emerged due to the plethora of logging libraries available today and 2) processing challenges have emerged due to the large number of log processing tools that ingest logs and produce useful information from them. In this thesis, we explore these two challenges. We first explore the infrastructural challenges that arise due to the plethora of logging libraries available today. As systems evolve, their logging infrastructure has to evolve (commonly this is done by migrating to new logging libraries). We explore logging library migrations within Apache Software Foundation (ASF) projects. We i find that close to 14% of the pro jects within the ASF migrate their logging libraries at least once. For processing challenges, we explore the different factors which can affect the likelihood of a logging statement changing in the future in four open source systems namely ActiveMQ, Camel, Cloudstack and Liferay. Such changes are likely to negatively impact the log processing tools that must be updated to accommodate such changes. We find that 20%-45% of the logging statements within the four systems are changed at least once. We construct random forest classifiers and Cox models to determine the likelihood of both just-introduced and long-lived logging statements changing in the future. We find that file ownership, developer experience, log density and SLOC are important factors in determining the stability of logging statements.

Preparation of Polymer Nanoparticles by Ring Opening Metathesis Polymerization in Aqueous Dispersed Systems with Water-Soluble Ruthenium-based Catalyst

Ring opening metathesis polymerization (ROMP) is a variant of olefin metathesis used to polymerize strained cyclic olefins. Ruthenium-based Grubbs’ catalysts are widely used in ROMP to produce industrially important products. While highly efficient in organic solvents such as dichloromethane and toluene, these hydrophobic catalysts are not typically applied in aqueous systems. With the advancements in emulsion and miniemulsion polymerization, it is promising to conduct ROMP in an aqueous dispersed phase to generate well-defined latex nanoparticles while improving heat transfer and reducing the use of volatile organic solvents (VOCs). Herein I report the efforts made using a PEGylated ruthenium alkylidene as the catalyst to initiate ROMP in an oil-in-water miniemulsion. 1H NMR revealed that the synthesized PEGylated catalyst was stable and reactive in water. Using 1,5-cyclooctadiene (COD) as monomer, we showed the highly efficient catalyst yielded colloidally stable polymer latexes with ~ 100% conversion at room temperature. Kinetic studies demonstrated first-order kinetics with good livingness as confirmed by the shift of gel permeation chromatography (GPC) traces. Depending on the surfactants used, the particle sizes ranged from 100 to 300 nm with monomodal distributions. The more strained cyclic olefin norbornene (NB) could also be efficiently polymerized with a PEGylated ruthenium alkylidene in miniemulsion to full conversion and with minimal coagulum formation.