Debugging of Web Applications with Web-TLR

Web-TLR is a Web verification engine that is based on the well-established Rewriting Logic--Maude/LTLR tandem for Web system specification and model-checking. In Web-TLR, Web applications are expressed as rewrite theories that can be formally verified by using the Maude built-in LTLR model-checker. Whenever a property is refuted, a counterexample trace is delivered that reveals an undesired, erroneous navigation sequence. Unfortunately, the analysis (or even the simple inspection) of such counterexamples may be unfeasible because of the size and complexity of the traces under examination. In this paper, we endow Web-TLR with a new Web debugging facility that supports the efficient manipulation of counterexample traces. This facility is based on a backward trace-slicing technique for rewriting logic theories that allows the pieces of information that we are interested to be traced back through inverse rewrite sequences. The slicing process drastically simplifies the computation trace by dropping useless data that do not influence the final result. By using this facility, the Web engineer can focus on the relevant fragments of the failing application, which greatly reduces the manual debugging effort and also decreases the number of iterative verifications.Comment: In Proceedings WWV 2011, arXiv:1108.208

Bringing Back-in-Time Debugging Down to the Database

With back-in-time debuggers, developers can explore what happened before observable failures by following infection chains back to their root causes. While there are several such debuggers for object-oriented programming languages, we do not know of any back-in-time capabilities at the database-level. Thus, if failures are caused by SQL scripts or stored procedures, developers have difficulties in understanding their unexpected behavior. In this paper, we present an approach for bringing back-in-time debugging down to the SAP HANA in-memory database. Our TARDISP debugger allows developers to step queries backwards and inspecting the database at previous and arbitrary points in time. With the help of a SQL extension, we can express queries covering a period of execution time within a debugging session and handle large amounts of data with low overhead on performance and memory. The entire approach has been evaluated within a development project at SAP and shows promising results with respect to the gathered developer feedback.Comment: 24th IEEE International Conference on Software Analysis, Evolution, and Reengineerin

Building Efficient Query Engines in a High-Level Language

Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database system designed according to this vision offers both increased productivity and high performance, instead of sacrificing the former for the latter as is the case with existing, monolithic implementations that are hard to maintain and extend. In this article, we realize this vision in the domain of analytical query processing. We present LegoBase, a query engine written in the high-level language Scala. The key technique to regain efficiency is to apply generative programming: LegoBase performs source-to-source compilation and optimizes the entire query engine by converting the high-level Scala code to specialized, low-level C code. We show how generative programming allows to easily implement a wide spectrum of optimizations, such as introducing data partitioning or switching from a row to a column data layout, which are difficult to achieve with existing low-level query compilers that handle only queries. We demonstrate that sufficiently powerful abstractions are essential for dealing with the complexity of the optimization effort, shielding developers from compiler internals and decoupling individual optimizations from each other. We evaluate our approach with the TPC-H benchmark and show that: (a) With all optimizations enabled, LegoBase significantly outperforms a commercial database and an existing query compiler. (b) Programmers need to provide just a few hundred lines of high-level code for implementing the optimizations, instead of complicated low-level code that is required by existing query compilation approaches. (c) The compilation overhead is low compared to the overall execution time, thus making our approach usable in practice for compiling query engines

Proof Theory, Transformations, and Logic Programming for Debugging Security Protocols

We define a sequent calculus to formally specify, simulate, debug and verify security protocols. In our sequents we distinguish between the current knowledge of principals and the current global state of the session. Hereby, we can describe the operational semantics of principals and of an intruder in a simple and modular way. Furthermore, using proof theoretic tools like the analysis of permutability of rules, we are able to find efficient proof strategies that we prove complete for special classes of security protocols including Needham-Schroeder. Based on the results of this preliminary analysis, we have implemented a Prolog meta-interpreter which allows for rapid prototyping and for checking safety properties of security protocols, and we have applied it for finding error traces and proving correctness of practical examples

Holistic debugging - enabling instruction set simulation for software quality assurance

We present holistic debugging, a novel method for observing execution of complex and distributed software. It builds on an instruction set simulator, which provides reproducible experiments and non-intrusive probing of state in a distributed system. Instruction set simulators, however, only provide low-level information, so a holistic debugger contains a translation framework that maps this information to higher abstraction level observation tools, such as source code debuggers. We have created Nornir, a proof-of-concept holistic debugger, built on the simulator Simics. For each observed process in the simulated system, Nornir creates an abstraction translation stack, with virtual machine translators that map machine-level storage contents (e.g. physical memory, registers) provided by Simics, to application-level data (e.g. virtual memory contents) by parsing the data structures of operating systems and virtual machines. Nornir includes a modified version of the GNU debugger (GDB), which supports non-intrusive symbolic debugging of distributed applications. Nornir's main interface is a debugger shepherd, a programmable interface that controls multiple debuggers, and allows users to coherently inspect the entire state of heterogeneous, distributed applications. It provides a robust observation platform for construction of new observation tools

Description and Optimization of Abstract Machines in a Dialect of Prolog

In order to achieve competitive performance, abstract machines for Prolog and related languages end up being large and intricate, and incorporate sophisticated optimizations, both at the design and at the implementation levels. At the same time, efficiency considerations make it necessary to use low-level languages in their implementation. This makes them laborious to code, optimize, and, especially, maintain and extend. Writing the abstract machine (and ancillary code) in a higher-level language can help tame this inherent complexity. We show how the semantics of most basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog, the abstract machine description can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of state-of-the-art, highly-tuned, hand-crafted emulators.Comment: 56 pages, 46 figures, 5 tables, To appear in Theory and Practice of Logic Programming (TPLP